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Papadourakis M, Cournia Z, Mey ASJS, Michel J. Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins. J Chem Theory Comput 2024; 20:9699-9707. [PMID: 39466712 PMCID: PMC11562378 DOI: 10.1021/acs.jctc.4c00942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 09/17/2024] [Accepted: 10/14/2024] [Indexed: 10/30/2024]
Abstract
Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the pathophysiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly, and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here, we compare alchemical absolute binding free energy calculations (ABFE) and Markov-State Modeling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.
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Affiliation(s)
- Michail Papadourakis
- EaStCHEM
School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Antonia S. J. S. Mey
- EaStCHEM
School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.
| | - Julien Michel
- EaStCHEM
School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K.
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2
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Fardel O, Moreau A, Carteret J, Denizot C, Le Vée M, Parmentier Y. The Competitive Counterflow Assay for Identifying Drugs Transported by Solute Carriers: Principle, Applications, Challenges/Limits, and Perspectives. Eur J Drug Metab Pharmacokinet 2024; 49:527-539. [PMID: 38958896 DOI: 10.1007/s13318-024-00902-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2024] [Indexed: 07/04/2024]
Abstract
The identification of substrates for solute carriers (SLCs) handling drugs is an important challenge, owing to the major implication of these plasma membrane transporters in pharmacokinetics and drug-drug interactions. In this context, the competitive counterflow (CCF) assay has been proposed as a practical and less expensive approach than the reference functional uptake assays for discriminating SLC substrates and non-substrates. The present article was designed to summarize and discuss key-findings about the CCF assay, including its principle, applications, challenges and limits, and perspectives. The CCF assay is based on the decrease of the steady-state accumulation of a tracer substrate in SLC-positive cells, caused by candidate substrates. Reviewed data highlight the fact that the CCF assay has been used to identify substrates and non-substrates for organic cation transporters (OCTs), organic anion transporters (OATs), and organic anion transporting polypeptides (OATPs). The performance values of the CCF assay, calculated from available CCF study data compared with reference functional uptake assay data, are, however, rather mitigated, indicating that the predictability of the CCF method for assessing SLC-mediated transportability of drugs is currently not optimal. Further studies, notably aimed at standardizing the CCF assay and developing CCF-based high-throughput approaches, are therefore required in order to fully precise the interest and relevance of the CCF assay for identifying substrates and non-substrates of SLCs.
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Affiliation(s)
- Olivier Fardel
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, 35043, Rennes, France.
| | - Amélie Moreau
- Institut de R&D Servier, Paris-Saclay, 20 route 128, 91190, Gif-sur-Yvette, France
| | - Jennifer Carteret
- Univ Rennes, Inserm, EHESP, Irset - UMR_S 1085, 35043, Rennes, France
| | - Claire Denizot
- Institut de R&D Servier, Paris-Saclay, 20 route 128, 91190, Gif-sur-Yvette, France
| | - Marc Le Vée
- Univ Rennes, Inserm, EHESP, Irset - UMR_S 1085, 35043, Rennes, France
| | - Yannick Parmentier
- Institut de R&D Servier, Paris-Saclay, 20 route 128, 91190, Gif-sur-Yvette, France
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Tanaka J, Kuwajima H, Yuki R, Nakayama Y. Simvastatin activates the spindle assembly checkpoint and causes abnormal cell division by modifying small GTPases. Cell Signal 2024; 119:111172. [PMID: 38604342 DOI: 10.1016/j.cellsig.2024.111172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/06/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
Simvastatin is an inhibitor of 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductase, which is a rate-limiting enzyme of the cholesterol synthesis pathway. It has been used clinically as a lipid-lowering agent to reduce low-density lipoprotein (LDL) cholesterol levels. In addition, antitumor activity has been demonstrated. Although simvastatin attenuates the prenylation of small GTPases, its effects on cell division in which small GTPases play an important role, have not been examined as a mechanism underlying its cytostatic effects. In this study, we determined its effect on cell division. Cell cycle synchronization experiments revealed a delay in mitotic progression in simvastatin-treated cells at concentrations lower than the IC50. Time-lapse imaging analysis indicated that the duration of mitosis, especially from mitotic entry to anaphase onset, was prolonged. In addition, simvastatin increased the number of cells exhibiting misoriented anaphase/telophase and bleb formation. Inhibition of the spindle assembly checkpoint (SAC) kinase Mps1 canceled the mitotic delay. Additionally, the number of cells exhibiting kinetochore localization of BubR1, an essential component of SAC, was increased, suggesting an involvement of SAC in the mitotic delay. Enhancement of F-actin formation and cell rounding at mitotic entry indicates that cortical actin dynamics were affected by simvastatin. The cholesterol removal agent methyl-β-cyclodextrin (MβCD) accelerated mitotic progression differently from simvastatin, suggesting that cholesterol loss from the plasma membrane is not involved in the mitotic delay. Of note, the small GTPase RhoA, which is a critical factor for cortical actin dynamics, exhibited upregulated expression. In addition, Rap1 was likely not geranylgeranylated. Our results demonstrate that simvastatin affects actin dynamics by modifying small GTPases, thereby activating the spindle assembly checkpoint and causing abnormal cell division.
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Affiliation(s)
- Junna Tanaka
- Laboratory of Biochemistry and Molecular Biology, Kyoto Pharmaceutical University, Kyoto 607-8414, Japan
| | - Hiroki Kuwajima
- Laboratory of Biochemistry and Molecular Biology, Kyoto Pharmaceutical University, Kyoto 607-8414, Japan
| | - Ryuzaburo Yuki
- Laboratory of Biochemistry and Molecular Biology, Kyoto Pharmaceutical University, Kyoto 607-8414, Japan
| | - Yuji Nakayama
- Laboratory of Biochemistry and Molecular Biology, Kyoto Pharmaceutical University, Kyoto 607-8414, Japan.
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4
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Rollison HE, Mitra P, Chanteux H, Fang Z, Liang X, Park SH, Costales C, Hanna I, Thakkar N, Vergis JM, Bow DAJ, Hillgren KM, Brumm J, Chu X, Hop CECA, Lai Y, Li CY, Mahar KM, Salphati L, Sane R, Shen H, Taskar K, Taub M, Tohyama K, Xu C, Fenner KS. Survey of Pharmaceutical Industry's Best Practices around In Vitro Transporter Assessment and Implications for Drug Development: Considerations from the International Consortium for Innovation and Quality for Pharmaceutical Development Transporter Working Group. Drug Metab Dispos 2024; 52:582-596. [PMID: 38697852 DOI: 10.1124/dmd.123.001587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 04/29/2024] [Accepted: 04/29/2024] [Indexed: 05/05/2024] Open
Abstract
The International Consortium for Innovation and Quality in Pharmaceutical Development Transporter Working Group had a rare opportunity to analyze a crosspharma collation of in vitro data and assay methods for the evaluation of drug transporter substrate and inhibitor potential. Experiments were generally performed in accordance with regulatory guidelines. Discrepancies, such as not considering the impact of preincubation for inhibition and free or measured in vitro drug concentrations, may be due to the retrospective nature of the dataset and analysis. Lipophilicity was a frequent indicator of crosstransport inhibition (P-gp, BCRP, OATP1B, and OCT1), with high molecular weight (MW ≥500 Da) also common for OATP1B and BCRP inhibitors. A high level of overlap in in vitro inhibition across transporters was identified for BCRP, OATP1B1, and MATE1, suggesting that prediction of DDIs for these transporters will be common. In contrast, inhibition of OAT1 did not coincide with inhibition of any other transporter. Neutrals, bases, and compounds with intermediate-high lipophilicity tended to be P-gp and/or BCRP substrates, whereas compounds with MW <500 Da tended to be OAT3 substrates. Interestingly, the majority of in vitro inhibitors were not reported to be followed up with a clinical study by the submitting company, whereas those compounds identified as substrates generally were. Approaches to metabolite testing were generally found to be similar to parent testing, with metabolites generally being equally or less potent than parent compounds. However, examples where metabolites inhibited transporters in vitro were identified, supporting the regulatory requirement for in vitro testing of metabolites to enable integrated clinical DDI risk assessment. SIGNIFICANCE STATEMENT: A diverse dataset showed that transporter inhibition often correlated with lipophilicity and molecular weight (>500 Da). Overlapping transporter inhibition was identified, particularly that inhibition of BCRP, OATP1B1, and MATE1 was frequent if the compound inhibited other transporters. In contrast, inhibition of OAT1 did not correlate with the other drug transporters tested.
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Affiliation(s)
- Helen E Rollison
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Pallabi Mitra
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Hugues Chanteux
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Zhizhou Fang
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Xiaomin Liang
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Seong Hee Park
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Chester Costales
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Imad Hanna
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Nilay Thakkar
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - James M Vergis
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Daniel A J Bow
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Kathleen M Hillgren
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Jochen Brumm
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Xiaoyan Chu
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Cornelis E C A Hop
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Yurong Lai
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Cindy Yanfei Li
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Kelly M Mahar
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Laurent Salphati
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Rucha Sane
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Hong Shen
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Kunal Taskar
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Mitchell Taub
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Kimio Tohyama
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Christine Xu
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
| | - Katherine S Fenner
- Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom (H.E.R., K.S.F.); Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut (P.M., M.T.); Quantitative Clinical Pharmacology, Development Sciences, UCB Biopharma SRL, Braine-L'Alleud, Belgium (H.C.); NCE Drug Metabolism and Pharmacokinetics, the healthcare business of Merck KGaA, Darmstadt, Germany (Z.F.); Drug Metabolism, Gilead Sciences, Inc. Foster City, California (X.L., Y.L.); Preclinical Sciences and Translational Safety, Janssen R&D LLC, Spring House, Pennsylvania (S.H.P.); Pharmacokinetics, Dynamics and Metabolism, Medicine Design, Worldwide R&D, Pfizer Inc, Groton, Connecticut (C.C.); Pharmacokinetic Sciences, Novartis Institutes for Biomedical Research, East Hanover, New Jersey (I.H.); Clinical Pharmacology Modelling and Simulations, GlaxoSmithKline Research and Development, Collegeville, Pennsylvania (N.T., K.M.M.); IQ Secretariat, Faegre Drinker Biddle & Reath, LLP., Washington DC (J.M.V.); Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois (D.A.J.B.); Investigative Drug Disposition, Lilly Research Laboratories, Eli Lilly Inc, Indianapolis, Indiana (K.M.H.); Nonclinical Biostatistics, Genentech, Inc., South San Francisco, California (J.B.); ADME and Discovery Toxicity, Merck & Co., Inc., Rahway, New Jersey (X.C.); Departments of Drug Metabolism and Pharmacokinetics (C.E.C.A.H., L.S.) and Clinical Pharmacology (R.S.), Genentech, Inc., South San Francisco, California; Department of Pharmacokinetics and Drug Metabolism, Amgen Inc. South San Francisco, California (C.Y.L.); Department of Drug Metabolism and Pharmacokinetics, Bristol Myers Squibb Research and Development, Princeton, New Jersey (H.S.); DMPK Modeling, IVIVT, Research, GSK, Stevenage, United Kingdom (Ku.T.); Takeda Pharmaceutical Company Limited, Fujisawa, Japan (Ki.T.); and Pharmacokinetics, Dynamics, and Metabolism, Translational Medicine and Early Development, Sanofi US, Bridgewater, NJ (C.X.)
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5
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Chen X, Xiang W, Li L, Xu K. Copper Chaperone Atox1 Protected the Cochlea From Cisplatin by Regulating the Copper Transport Family and Cell Cycle. Int J Toxicol 2024; 43:134-145. [PMID: 37859596 DOI: 10.1177/10915818231206665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Antioxidant 1 copper chaperone (Atox1) may contribute to preventing DDP cochlear damage by regulating copper transport family and cell cycle proteins. A rat model of cochlear damage was developed by placing gelatin sponges treated with DDP in the cochlea. HEI-OC1 cells were treated with 133 μM DDP as a cell model. DDP-induced ototoxicity in rats was confirmed by immunofluorescence (IF) imaging. The damage of DDP to HEI-OC1 cells was assessed by using CCK-8, TUNEL, and flow cytometry. The relationship between Atox1, a member of the copper transport protein family, and the damage to in vivo/vitro models was explored by qRT-PCR, western blot, CCK-8, TUNEL, and flow cytometry. DDP had toxic and other side effects causing cochlear damage and promoted HEI-OC1 cell apoptosis and cell cycle arrest. The over-expression of Atox1 (oe-Atox1) was accomplished by transfecting lentiviral vectors into in vitro/vivo models. We found that oe-Atox1 increased the levels of Atox1, copper transporter 1 (CTR1), and SOD3 in HEI-OC1 cells and decreased the expression levels of ATPase copper transporting α (ATP7A) and ATPase copper transporting β (ATP7B). In addition, the transfection of oe-Atox1 decreased cell apoptosis rate and the number of G2/M stage cells. Similarly, the expression of myosin VI and phalloidin of cochlea cells in vivo decreased. Atox1 ameliorated DDP-induced damage to HEI-OC1 cells or rats' cochlea by regulating the levels of members of the copper transport family.
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Affiliation(s)
- Xubo Chen
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Weiren Xiang
- Department of Otolaryngology, Head and Neck Surgery, Jiu Jiang No.1 People's Hospital, Jiujiang, China
| | - Lihua Li
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Kai Xu
- Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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Kimani CN, Reuter H, Kotzé SH, Venter P, Ramharack P, Muller CJF. Pancreatic beta cell regenerative potential of Zanthoxylum chalybeum Engl. Aqueous stem bark extract. JOURNAL OF ETHNOPHARMACOLOGY 2024; 320:117374. [PMID: 37944876 DOI: 10.1016/j.jep.2023.117374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/18/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Zanthoxylum chalybeum Engl. is endemic to Africa and has been used traditionally to treat diabetes mellitus. Moreover, its pharmacological efficacy has been confirmed experimentally using in vitro and in vivo models of diabetes. However, the effects of Z. chalybeum extracts and its major constituent compounds on beta cell and islet regeneration are not clear. Further, the mechanisms associated with observed antidiabetic effects at the beta cell level are not fully elucidated. AIM OF THE STUDY We determined the beta cell regenerative efficacy of Z. chalybeum aqueous stem bark extract, identified the chemical compounds in Z. chalybeum aqueous stem bark extracts and explored their putative mechanisms of action. MATERIALS AND METHODS Phytochemical profiling of the Z. chalybeum extract was achieved using ultra high-performance liquid chromatography hyphenated to high-resolution mass spectrometry. Thereafter, molecular interactions of the compounds with beta cell regeneration targets were evaluated via molecular docking. In vitro, effects of the extract on cell viability, proliferation, apoptosis and oxidative stress were investigated in RIN-5F beta cells exposed to palmitate or streptozotocin. In vivo, pancreas tissue sections from streptozotocin-induced diabetic male Wistar rats treated with Z. chalybeum extract were stained for insulin, glucagon, pancreatic duodenal homeobox protein 1 (Pdx-1) and Ki-67. RESULTS Based on ligand target and molecular docking interactions diosmin was identified as a dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) inhibitor. In vitro, Z. chalybeum augmented cell viability and cell proliferation while in palmitate-pre-treated cells, the extract significantly increased cell activity after 72 h. In vivo, although morphometric analysis showed decreased islet and beta cell size and density, observation of increased Pdx-1 and Ki-67 immunoreactivity in extract-treated islets suggests that Z. chalybeum extract has mild beta cell regenerative potential mediated by increased cell proliferation. CONCLUSIONS Overall, the mitogenic effects observed in vitro, were not robust enough to elicit sufficient recovery of functional beta cell mass in our in vivo model, in the context of a sustained diabetic milieu. However, the identification of diosmin as a potential Dyrk1A inhibitor merits further inquiry into the attendant molecular interactions.
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Affiliation(s)
- Clare Njoki Kimani
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg, 7505, South Africa; Division of Clinical Pharmacology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa; Department of Non-communicable Diseases, Institute of Primate Research, PO Box 24481, Karen, Nairobi, Kenya.
| | - Helmuth Reuter
- Division of Clinical Pharmacology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa
| | - Sanet Henriët Kotzé
- Division of Clinical Anatomy, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, PO Box 241, Cape Town, 8000, South Africa; Division of Anatomy, Department of Biomedical Sciences, School of Veterinary Medicine, Ross University, PO Box 334, Basseterre, Saint Kitts and Nevis
| | - Pieter Venter
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg, 7505, South Africa
| | - Pritika Ramharack
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg, 7505, South Africa; Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Christo John Frederick Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Tygerberg, 7505, South Africa; Centre for Cardio-Metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, 7600, South Africa; Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa, 3886, South Africa
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7
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Imakura Y, Mima S, Yamazaki N, Inomata A, Mochizuki S, Iwao T, Matsunaga T. Utility of human induced pluripotent stem cell-derived small intestinal epithelial cells for pharmacokinetic, toxicological, and immunological studies. Biochem Biophys Res Commun 2024; 692:149356. [PMID: 38071890 DOI: 10.1016/j.bbrc.2023.149356] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 11/21/2023] [Accepted: 12/03/2023] [Indexed: 01/06/2024]
Abstract
The small intestine, which plays a crucial role in the absorption and metabolism of drugs and foods, serves as a target organ for drug-induced toxicity and immune interactions with functional foods and intestinal bacteria. Current alternative models of the human small intestine, such as Caco-2 cells and experimental animals, have limitations due to variations in the expression levels of metabolic enzymes, transporters, and receptors. This study presents investigations into the utility of human induced pluripotent stem cell-derived small intestinal epithelial cells (hiSIECs) for pharmacokinetic, toxicological, and immunological studies, respectively. While hiSIECs displayed small intestinal epithelial cell characteristics and barrier function, they demonstrated pharmacokinetic properties such as cytochrome P450 3A4/5 activity equivalent to human primary enterocytes and stable P-glycoprotein activity. These cells also demonstrated potential for assessing two forms of intestinal toxicity caused by anticancer drugs and gamma-secretase inhibitors, displaying immune responses mediated by toll-like and fatty acid receptors while serving as an inflammatory gut model through the addition of tumor necrosis factor alpha and interferon gamma. Overall, hiSIECs hold promise as an in vitro model for assessing pharmacokinetics, toxicity, and effects on the intestinal immunity of pharmaceuticals, functional foods, supplements, and intestinal bacteria.
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Affiliation(s)
- Yuki Imakura
- Bio Science & Engineering Laboratory, FUJIFILM Corporation, 577 Ushijima, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8577, Japan; Department of Clinical Pharmacy, Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya, 467-8603, Japan
| | - Shinji Mima
- Bio Science & Engineering Laboratory, FUJIFILM Corporation, 577 Ushijima, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8577, Japan
| | - Nao Yamazaki
- Bio Science & Engineering Laboratory, FUJIFILM Corporation, 577 Ushijima, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8577, Japan
| | - Akira Inomata
- Bio Science & Engineering Laboratory, FUJIFILM Corporation, 577 Ushijima, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8577, Japan
| | - Seiichi Mochizuki
- Bio Science & Engineering Laboratory, FUJIFILM Corporation, 577 Ushijima, Kaisei-machi, Ashigarakami-gun, Kanagawa, 258-8577, Japan
| | - Takahiro Iwao
- Department of Clinical Pharmacy, Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya, 467-8603, Japan.
| | - Tamihide Matsunaga
- Department of Clinical Pharmacy, Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya, 467-8603, Japan
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Nozaki Y, Izumi S. Preincubation Time-Dependent, Long-Lasting Inhibition of Drug Transporters and Impact on the Prediction of Drug-Drug Interactions. Drug Metab Dispos 2023; 51:1077-1088. [PMID: 36854606 DOI: 10.1124/dmd.122.000970] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 02/05/2023] [Accepted: 02/21/2023] [Indexed: 03/02/2023] Open
Abstract
Transporter-mediated drug-drug interaction (DDI) is of clinical concern, and the quantitative prediction of DDIs is an indispensable part of drug development. Cell-based inhibition assays, in which a representative probe substrate and a potential inhibitor are coincubated, are routinely performed to assess the inhibitory potential of new molecular entities on drug transporters. However, the inhibitory effect of cyclosporine A (CsA) on organic anion transporting polypeptide (OATP) 1B1 is substantially potentiated with CsA preincubation, and this effect is both long-lasting and dependent on the preincubation time. This phenomenon has also been reported with transporters other than OATP1Bs, but it is considered more prevalent among OATP1Bs and organic cation transporters. Regulatory agencies have also noted this preincubation effect and have recommended that pharmaceutical companies consider inhibitor preincubation when performing in vitro OATP1B1 and OATP1B3 inhibition studies. Although the underlying mechanisms responsible for the preincubation effect are not fully understood, a trans-inhibition mechanism was recently demonstrated for OATP1B1 inhibition by CsA, in which CsA inhibited OATP1B1 not only extracellularly (cis-inhibition) but also intracellularly (trans-inhibition). Furthermore, the trans-inhibition potency of CsA was much greater than that of cis-inhibition, suggesting that trans-inhibition might be a key driver of clinical DDIs of CsA with OATP1B substrate drugs. Although confidence in transporter-mediated DDI prediction is generally considered to be low, the predictability might be further improved by incorporating the trans-inhibition mechanism into static and dynamic models for preincubation-dependent inhibitors of OATP1Bs and perhaps other transporters. SIGNIFICANCE STATEMENT: Preincubation time-dependent, long-lasting inhibition has been observed for OATP1B1 and other solute carrier transporters in vitro. Recently, a trans-inhibition mechanism for the preincubation effect of CsA on OATP1B1 inhibition was identified, with the trans-inhibition potency being greater than that of cis-inhibition. The concept of trans-inhibition may allow us to further understand the mechanism of transporter-mediated DDIs not only for OATP1B1 but also for other transporters and to improve the accuracy and confidence of DDI predictions.
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Affiliation(s)
- Yoshitane Nozaki
- Global Drug Metabolism and Pharmacokinetics, Tsukuba Research Laboratories, Eisai Co., Ltd., 5-1-3, Tokodai, Tsukuba, Ibaraki, 300-2635, Japan (Y.N., S.I.)
| | - Saki Izumi
- Global Drug Metabolism and Pharmacokinetics, Tsukuba Research Laboratories, Eisai Co., Ltd., 5-1-3, Tokodai, Tsukuba, Ibaraki, 300-2635, Japan (Y.N., S.I.)
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Sagawa K, Lin J, Jaini R, Di L. Physiologically-Based Pharmacokinetic Modeling of PAXLOVID™ with First-Order Absorption Kinetics. Pharm Res 2023; 40:1927-1938. [PMID: 37231296 PMCID: PMC10212229 DOI: 10.1007/s11095-023-03538-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 05/15/2023] [Indexed: 05/27/2023]
Abstract
PURPOSE PAXLOVID™ is nirmatrelvir tablets co-packaged with ritonavir tablets. Ritonavir is used as a pharmacokinetics (PK) enhancer to reduce metabolism and increase exposure of nirmatrelvir. This is the first disclosure of Paxlovid physiologically-based pharmacokinetic (PBPK) model. METHODS Nirmatrelvir PBPK model with first-order absorption kinetics was developed using in vitro, preclinical, and clinical data of nirmatrelvir in the presence and absence of ritonavir. Clearance and volume of distribution were derived from nirmatrelvir PK obtained using a spray-dried dispersion (SDD) formulation where it is considered to be dosed as an oral solution, and absorption is near complete. The fraction of nirmatrelvir metabolized by CYP3A was estimated based on in vitro and clinical ritonavir drug-drug interaction (DDI) data. First-order absorption parameters were established for both SDD and tablet formulation using clinical data. Nirmatrelvir PBPK model was verified with both single and multiple dose human PK data, as well as DDI studies. Simcyp® first-order ritonavir compound file was also verified with additional clinical data. RESULTS The nirmatrelvir PBPK model described the observed PK profiles of nirmatrelvir well with predicted AUC and Cmax values within ± 20% of the observed. The ritonavir model performed well resulting in predicted values within twofold of observed. CONCLUSIONS Paxlovid PBPK model developed in this study can be applied to predict PK changes in special populations, as well as model the effect of victim and perpetrator DDI. PBPK modeling continues to play a critical role in accelerating drug discovery and development of potential treatments for devastating diseases such as COVID-19. NCT05263895, NCT05129475, NCT05032950 and NCT05064800.
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Affiliation(s)
- Kazuko Sagawa
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
| | - Jian Lin
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
| | - Rohit Jaini
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA
- Pharmaceutical Science, Pfizer Worldwide Research and Development, 1 Portland Street, Cambridge, MA, 02139, USA
| | - Li Di
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, 445 Eastern Point Road, Groton, CT, 06340, USA.
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10
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Kimani CN, Reuter H, Kotzé SH, Muller CJF. Regeneration of Pancreatic Beta Cells by Modulation of Molecular Targets Using Plant-Derived Compounds: Pharmacological Mechanisms and Clinical Potential. Curr Issues Mol Biol 2023; 45:6216-6245. [PMID: 37623211 PMCID: PMC10453321 DOI: 10.3390/cimb45080392] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/20/2023] [Accepted: 07/22/2023] [Indexed: 08/26/2023] Open
Abstract
Type 2 diabetes (T2D) is characterized by pancreatic beta-cell dysfunction, increased cell death and loss of beta-cell mass despite chronic treatment. Consequently, there has been growing interest in developing beta cell-centered therapies. Beta-cell regeneration is mediated by augmented beta-cell proliferation, transdifferentiation of other islet cell types to functional beta-like cells or the reprograming of beta-cell progenitors into fully differentiated beta cells. This mediation is orchestrated by beta-cell differentiation transcription factors and the regulation of the cell cycle machinery. This review investigates the beta-cell regenerative potential of antidiabetic plant extracts and phytochemicals. Various preclinical studies, including in vitro, in vivo and ex vivo studies, are highlighted. Further, the potential regenerative mechanisms and the intra and extracellular mediators that are of significance are discussed. Also, the potential of phytochemicals to translate into regenerative therapies for T2D patients is highlighted, and some suggestions regarding future perspectives are made.
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Affiliation(s)
- Clare Njoki Kimani
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Cape Town 7505, South Africa;
- Division of Clinical Pharmacology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
| | - Helmuth Reuter
- Division of Clinical Pharmacology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
| | - Sanet Henriët Kotzé
- Division of Clinical Anatomy, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
- Division of Anatomy, Department of Biomedical Sciences, School of Veterinary Medicine, Ross University, Basseterre P.O. Box 334, Saint Kitts and Nevis
| | - Christo John Fredrick Muller
- Biomedical Research and Innovation Platform (BRIP), South African Medical Research Council (SAMRC), Cape Town 7505, South Africa;
- Centre for Cardio-Metabolic Research in Africa, Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch 7600, South Africa
- Department of Biochemistry and Microbiology, University of Zululand, KwaDlangezwa 3886, South Africa
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Ullah I, Hassan M, Khan KM, Sajid M, Umar M, Hassan S, Ullah A, El-Serehy HA, Charifi W, Yasmin H. Thiourea derivatives inhibit key diabetes-associated enzymes and advanced glycation end-product formation as a treatment for diabetes mellitus. IUBMB Life 2023; 75:161-180. [PMID: 36565478 DOI: 10.1002/iub.2699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 11/14/2022] [Indexed: 12/25/2022]
Abstract
This study was designed to screen novel thiourea derivatives against different enzymes, such as α-amylase, α-glucosidase, protein tyrosine phosphatase 1 B, and advanced glycated end product (AGEs). A cytotoxicity analysis was performed using rat L6 myotubes and molecular docking analysis was performed to map the binding interactions between the active compounds and α-amylase and α-glucosidase. The data revealed the potency of five compounds, including E (1-(2,4-difluorophenyl)-3-(3,4-dimethyl phenyl) thiourea), AG (1-(2-methoxy-5-(trifluoromethyl) phenyl)-3-(3-methoxy phenyl) thiourea), AF (1-(2,4-dichlorophenyl)-3-(4-ethylphenyl) thiourea), AD (1-(2,4-dichlorophenyl)-3-(4-ethylphenyl) thiourea), and AH (1-(2,4-difluorophenyl)-3-(2-iodophenyl) thiourea), showed activity against α-amylase. The corresponding percentage inhibitions were found to be 85 ± 1.9, 82 ± 0.7, 75 ± 1.2, 72 ± 0.4, and 65 ± 1.1%, respectively. These compounds were then screened using in vitro assays. Among them, AH showed the highest activity against α-glucosidase, AGEs, and PTP1B, with percentage inhibitions of 86 ± 0.4% (IC50 = 47.9 μM), 85 ± 0.7% (IC50 = 49.51 μM), and 85 ± 0.5% (IC50 = 79.74 μM), respectively. Compound AH showed an increased glucose uptake at a concentration of 100 μM. Finally, an in vivo study was conducted using a streptozotocin-induced diabetic mouse model and PTP1B expression was assessed using real-time PCR. Additionally, we examined the hypoglycemic effect of compound AH in diabetic rats compared to the standard drug glibenclamide.
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Affiliation(s)
- Imran Ullah
- Department of Biochemistry, Hazara University Mansehra, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Mukhtiar Hassan
- Department of Biochemistry, Hazara University Mansehra, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Khalid M Khan
- H.E.J Research Institute of Chemistry, University of Karachi, Karachi, Pakistan
| | - Muhammad Sajid
- Department of Biochemistry, Hazara University Mansehra, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Umar
- Department of Orthopaedics, Shenzhen University General Hospital, Shenzhen, Guangdong, People's Republic of China
| | - Said Hassan
- Institute of Biotechnology and Microbiology, Bacha Khan University Charsadda, Charsadda, Khyber Pakhtunkhwa, Pakistan
| | - Amin Ullah
- Department of Health and Biological Sciecnes, Abasyn University Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan
| | - Hamed A El-Serehy
- Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Wafa Charifi
- Cochin Institute, University of Paris, INSERM, U1016, Paris, France
| | - Humaira Yasmin
- Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan
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12
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Translatability of in vitro Inhibition Potency to in vivo P-Glycoprotein Mediated Drug Interaction Risk. J Pharm Sci 2023; 112:1715-1723. [PMID: 36682487 DOI: 10.1016/j.xphs.2023.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/13/2023] [Accepted: 01/13/2023] [Indexed: 01/22/2023]
Abstract
P-glycoprotein (P-gp) may limit oral drug absorption of substrate drugs due to intestinal efflux. Therefore, regulatory agencies require investigation of new chemical entities as possible inhibitors of P-gp in vitro. Unfortunately, inter-laboratory and inter-assay variability have hindered the translatability of in vitro P-gp inhibition data to predict clinical drug interaction risk. The current study was designed to evaluate the impact of potential IC50 discrepancies between two commonly utilized assays, i.e., bi-directional Madin-Darby Canine Kidney-MDR1 cell-based and MDR1 membrane vesicle-based assays. When comparing vesicle- to cell-based IC50 values (n = 28 inhibitors), non-P-gp substrates presented good correlation between assay formats, whereas IC50s of P-gp substrates were similar or lower in the vesicle assays. The IC50s obtained with a cell line expressing relatively low P-gp aligned more closely to those obtained from the vesicle assay, but passive permeability of the inhibitors did not appear to influence the correlation of IC50s, suggesting that efflux activity reduces intracellular inhibitor concentrations. IC50s obtained between two independent laboratories using the same assay type showed good correlation. Using the G-value (i.e., ratio of estimated gut concentration-to-inhibition potency) >10 cutoff recommended by regulatory agencies resulted in minimal differences in predictive performance, suggesting this cutoff is appropriate for either assay format.
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13
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Zhang T, Applebee Z, Zou P, Wang Z, Diaz ES, Li Y. An in vitro human mammary epithelial cell permeability assay to assess drug secretion into breast milk. Int J Pharm X 2022; 4:100122. [PMID: 35789754 PMCID: PMC9249612 DOI: 10.1016/j.ijpx.2022.100122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 06/10/2022] [Accepted: 06/19/2022] [Indexed: 11/30/2022] Open
Affiliation(s)
- Tao Zhang
- Department of Pharmaceutical Sciences, School of Pharmacy, Husson University, Bangor, ME 04401, United States of America
- Corresponding author.
| | - Zachary Applebee
- Department of Pharmaceutical Sciences, School of Pharmacy, Husson University, Bangor, ME 04401, United States of America
| | - Peng Zou
- Daiichi Sankyo, Inc., 211 Mount Airy Road, Basking Ridge, NJ 07920, United States of America
| | - Zhen Wang
- Department of Pharmaceutical Sciences, School of Pharmacy, Husson University, Bangor, ME 04401, United States of America
| | - Erika Solano Diaz
- Department of Biomedical Engineering, SUNY-Binghamton University, PO Box 6000, Binghamton, NY 13902-6000, United States of America
| | - Yanyan Li
- College of Science and Humanities, Husson University, Bangor, ME 04401, USA. Current affiliation: School of Food and Agriculture, College of Natural Sciences, Forestry, and Agriculture, University of Maine, Orono, ME 04469, USA
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14
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Inchinkoto, the Traditional Japanese Kampo Medicine, Enhances Intestinal Epithelial Barrier Function In Vitro. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:4139812. [PMID: 36212959 PMCID: PMC9536930 DOI: 10.1155/2022/4139812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 08/11/2022] [Accepted: 09/10/2022] [Indexed: 11/18/2022]
Abstract
Inchinkoto (ICKT), a traditional herbal medicine that is often used as a hepatoprotective drug in Japan, has pharmacological properties that include antioxidant, anti-inflammatory, and choleretic actions. Genipin is a metabolite of geniposide and the most abundant ingredient of ICKT; furthermore, it is considered to be the active substance responsible for its pharmacological properties in the liver. Drugs with such pharmacological characteristics are expected to prevent intestinal barrier dysfunction, which causes inflammatory bowel diseases (IBDs). However, no studies have investigated the effects of ICKT on the intestinal epithelial barrier. Therefore, we investigated the activity of ICKT in intestinal tight junctions by using cultured Caco-2 cell monolayers. The action of the compound on tight junctions was examined by measuring transepithelial electrical resistance (TEER) and sodium fluorescein (Na-F) permeability in the presence or absence of lipopolysaccharide (LPS). Moreover, the expression of the tight junction protein claudin-1 was assessed by using immunofluorescent staining. ICKT and genipin increased TEER and decreased Na-F permeability, which was suggestive of enhanced intestinal epithelial barrier function. Moreover, they prevented the LPS-induced destruction of the barrier, i.e., a decrease in TEER and an increase in Na-F permeability. Immunofluorescence staining revealed a high claudin-1 expression level on the cell surface, whereas exposure to LPS downregulated claudin-1. In turn, ICKT and genipin prevented the LPS-mediated reduction of claudin-1. These results suggest that ICKT enhances intestinal epithelial barrier function by upregulating claudin-1. Furthermore, genipin contributed to these effects. ICKT may be a promising medicine for the prevention and treatment of diseases associated with intestinal barrier disruption, such as IBD, obesity, and metabolic disorders.
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15
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Wright SH, Secomb TW. Novel method for kinetic analysis applied to transport by the uniporter OCT2. Am J Physiol Renal Physiol 2022; 323:F370-F387. [PMID: 35862650 PMCID: PMC9423780 DOI: 10.1152/ajprenal.00106.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 11/22/2022] Open
Abstract
The kinetics of solute transport shed light on the roles these processes play in cellular physiology, and the absolute values of the kinetic parameters that quantitatively describe transport are increasingly used to model its impact on drug clearance. However, accurate assessment of transport kinetics is challenging. Although most carrier-mediated transport is adequately described by the Michaelis-Menten equation, its use presupposes that the rates of uptake used in the analysis of maximal rates of transport (Jmax) and half-saturation constants (Kt) reflect true unidirectional rates of influx from known concentrations of substrate. Most experimental protocols estimate the initial rate of transport from net substrate accumulation determined at a single time point (typically between 0.5 and 5 min) and assume it reflects unidirectional influx. However, this approach generally results in systematic underestimates of Jmax and overestimates of Kt; the former primarily due to the unaccounted impact of efflux of accumulated substrate, and the latter due to the influence of unstirred water layers. Here, we describe the bases of these time-dependent effects and introduce a computational model that analyzes the time course of net substrate uptake at several concentrations to calculate Jmax and Kt for unidirectional influx, taking into account the influence of unstirred water layers and mediated efflux. This method was then applied to calculate the kinetics of transport of 1-methyl-4-phenylpryridinium and metformin by renal organic cation transporter 2 as expressed in cultured Chinese hamster ovary cells.NEW & NOTEWORTHY Here, we describe a mathematical model that uses the time course of net substrate uptake into cells from several increasing concentrations to calculate unique kinetic parameters [maximal rates of transport (Jmax) and half-saturation constants (Kt)] of the process. The method is the first to take into consideration the common complicating factors of unstirred layers and carrier-mediated efflux in the experimental determination of transport kinetics.
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Affiliation(s)
- Stephen H Wright
- Department of Physiology, College of Medicine, University of Arizona, Tucson, Arizona
| | - Timothy W Secomb
- Department of Physiology, College of Medicine, University of Arizona, Tucson, Arizona
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16
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Taskar KS, Yang X, Neuhoff S, Patel M, Yoshida K, Paine MF, Brouwer KL, Chu X, Sugiyama Y, Cook J, Polli JW, Hanna I, Lai Y, Zamek-Gliszczynski M. Clinical Relevance of Hepatic and Renal P-gp/BCRP Inhibition of Drugs: An International Transporter Consortium Perspective. Clin Pharmacol Ther 2022; 112:573-592. [PMID: 35612761 PMCID: PMC9436425 DOI: 10.1002/cpt.2670] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 05/16/2022] [Indexed: 12/11/2022]
Abstract
The role of P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) in drug-drug interactions (DDIs) and limiting drug absorption as well as restricting the brain penetration of drugs with certain physicochemical properties is well known. P-gp/BCRP inhibition by drugs in the gut has been reported to increase the systemic exposure to substrate drugs. A previous International Transporter Consortium (ITC) perspective discussed the feasibility of P-gp/BCRP inhibition at the blood-brain barrier and its implications. This ITC perspective elaborates and discusses specifically the hepatic and renal P-gp/BCRP (referred as systemic) inhibition of drugs and whether there is any consequence for substrate drug disposition. This perspective summarizes the clinical evidence-based recommendations regarding systemic P-gp and BCRP inhibition of drugs with a focus on biliary and active renal excretion pathways. Approaches to assess the clinical relevance of systemic P-gp and BCRP inhibition in the liver and kidneys included (i) curation of DDIs involving intravenously administered substrates or inhibitors; (ii) in vitro-to-in vivo extrapolation of P-gp-mediated DDIs at the systemic level; and (iii) curation of drugs with information available about the contribution of biliary excretion and related DDIs. Based on the totality of evidence reported to date, this perspective supports limited clinical DDI risk upon P-gp or BCRP inhibition in the liver or kidneys.
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Affiliation(s)
- Kunal S. Taskar
- Drug Metabolism and Pharmacokinetics, IVIVT, GlaxoSmithKline, Stevenage, UK
| | - Xinning Yang
- Office of Clinical Pharmacology, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD
| | - Sibylle Neuhoff
- Certara UK Ltd, Simcyp Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, UK
| | - Mitesh Patel
- Novartis Institutes for BioMedical Research, Cambridge, MA, USA
| | - Kenta Yoshida
- Clinical Pharmacology, Genentech Early Research and Development, South San Francisco, CA 94080, USA
| | - Mary F. Paine
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA
| | - Kim L.R. Brouwer
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Xiaoyan Chu
- Department of ADME and Discovery Toxicology, Merck & Co., Inc., 2000 Galloping Hill Rd, Kenilworth, NJ 07033 USA
| | - Yuichi Sugiyama
- Laboratory of Quantitative System PK/Pharmacodynamics, School of Pharmacy, Kioicho campus, Josai International University, Tokyo 102-0093, Japan
| | - Jack Cook
- Clinical Pharmacology, Global Product Development, Pfizer Inc., Groton, Connecticut, USA
| | - Joseph W. Polli
- Global Medical Sciences, ViiV Healthcare, Research Triangle Park NC USA
| | - Imad Hanna
- Pharmacokinetic Sciences-Oncology, Novartis Institute for Biomedical Research, East Hanover, NJ
| | - Yurong Lai
- Drug Metabolism, Gilead Sciences Inc. Foster City, CA USA
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17
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Volpe DA, Joshi A, Arya V. Do differences in cell lines and methods used for calculation of IC 50 values influence categorisation of drugs as P-glycoprotein substrates and inhibitors? Xenobiotica 2022; 52:751-757. [PMID: 36218364 DOI: 10.1080/00498254.2022.2135040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In vitro bidirectional assays are employed to determine whether a drug is a substrate and/or inhibitor of P-glycoprotein (P-gp) transport. Differences between cell lines and calculation methods can lead to variations in the determination of efflux ratios (ER) and IC50 values used to classify a drug as a P-gp substrate and inhibitor, respectively.Information was collected from the literature on ER and IC50 values with digoxin as the probe substrate using different cell lines and inhibition calculation methods. Predictive performance was evaluated by comparing [Igut]/IC50 ratios versus reported in vivo results.For known P-gp substrates, 50% of the drugs had their highest ER value in MDCK-MDR1 cells while 81% had their lowest ER value in Caco-2 cells. For 30 drugs with inhibition data, lower mean IC50 values were often observed with the Caco-2 cells and calculations based on ER. Based on the cut-off criteria of [Igut]/IC50 ≥ 10, there were no significant differences in positive or negative predictive values based on either cell line or calculation method for the drugs.Within this limited dataset, differences between cell lines or IC50 calculation methods do not seem to impact the prediction of in vivo P-gp inhibitor classification.
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Affiliation(s)
- Donna A Volpe
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - Abhay Joshi
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
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18
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Wang X, Wang A, Feng W, Wang D, Guo X, Wang X, Miao Q, Liu M, Xia G. Novel 5-Fluorouracil Carbonate-Loaded Liposome: Preparation, In Vitro, and In Vivo Evaluation as an Antitumor Agent. Mol Pharm 2022; 19:2061-2076. [PMID: 35731595 DOI: 10.1021/acs.molpharmaceut.1c00820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
5-Fluorouracil (5-FU) is a chemotherapeutic drug against many types of cancers, especially colorectal cancer. However, its short plasma half-life and serious adverse reactions limit its wide clinical applications. To overcome these shortcomings, a novel lipophilic 5-FU carbonate [XL-01, (5-fluoro-2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl) methyl tetradecyl carbonate] was designed, synthesized, and encapsulated into liposome (LipoXL-01) by a thin-film dispersion method through formulation screening and optimization. LipoXL-01 was characterized by a particle size of around 100 nm, polydispersity index of 0.200, ζ-potential value of -41 mV, encapsulation efficiency of 93.9%, and drug-loading efficiency of 11.6%. The cellular uptake of LipoXL-01 was increased in a concentration-dependent manner on HCT15 cells. LipoXL-01 could enhance the induction of cell apoptosis and the inhibition of cell migration and arrest the ability of the cell cycle at the S-phase on HCT15 cells better than 5-FU. Additionally, LipoXL-01 exhibited a slow drug release profile with a cumulative release rate of 12% in 8 h. The results of pharmacokinetic and biodistribution studies revealed that LipoXL-01 had a long plasma half-life (7.21 h) and a high tumor accumulation (733 nmol/g at 8 h). The in vivo antitumor effect study also showed that LipoXL-01 had more potent efficacy than 5-FU (65 vs 48% of the tumor-inhibition rate). Simultaneously, negligible systemic toxicity was observed via analyzing the body weight as well as hematological and pathological parameters in the tested mice. The current study suggested that LipoXL-01 might be a promising nanocandidate for chemotherapy of colorectal cancer.
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Affiliation(s)
- Xuelei Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Apeng Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Wenkai Feng
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Dan Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Xiaoru Guo
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Xiaowei Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Qingfang Miao
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Mingliang Liu
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
| | - Guimin Xia
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China
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19
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Denecke S, Bảo Lương HN, Koidou V, Kalogeridi M, Socratous R, Howe S, Vogelsang K, Nauen R, Batterham P, Geibel S, Vontas J. Characterization of a novel pesticide transporter and P-glycoprotein orthologues in Drosophila melanogaster. Proc Biol Sci 2022; 289:20220625. [PMID: 35582794 PMCID: PMC9114944 DOI: 10.1098/rspb.2022.0625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Pesticides remain one of the most effective ways of controlling agricultural and public health insects, but much is still unknown regarding how these compounds reach their targets. Specifically, the role of ABC transporters in pesticide absorption and excretion is poorly understood, especially compared to the detailed knowledge about mammalian systems. Here, we present a comprehensive characterization of pesticide transporters in the model insect Drosophila melanogaster. An RNAi screen was performed, which knocked down individual ABCs in specific epithelial tissues and examined the subsequent changes in sensitivity to the pesticides spinosad and fipronil. This implicated a novel ABC drug transporter, CG4562, in spinosad transport, but also highlighted the P-glycoprotein orthologue Mdr65 as the most impactful ABC in terms of chemoprotection. Further characterization of the P-glycoprotein family was performed via transgenic overexpression and immunolocalization, finding that Mdr49 and Mdr50 play enigmatic roles in pesticide toxicology perhaps determined by their different subcellular localizations within the midgut. Lastly, transgenic Drosophila lines expressing P-glycoprotein from the major malaria vector Anopheles gambiae were used to establish a system for in vivo characterization of this transporter in non-model insects. This study provides the basis for establishing Drosophila as a model for toxicology research on drug transporters.
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Affiliation(s)
- Shane Denecke
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 100N. Plastira Street, 700 13 Heraklion Crete, Greece
| | - Hằng Ngọc Bảo Lương
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 100N. Plastira Street, 700 13 Heraklion Crete, Greece
| | - Venetia Koidou
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 100N. Plastira Street, 700 13 Heraklion Crete, Greece,Department of Biology, University of Crete, Vassilika Vouton, 71409 Heraklion, Greece
| | - Maria Kalogeridi
- Department of Biology, University of Crete, Vassilika Vouton, 71409 Heraklion, Greece
| | - Rafaella Socratous
- Department of Biology, University of Crete, Vassilika Vouton, 71409 Heraklion, Greece
| | - Steven Howe
- School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Kathrin Vogelsang
- Bayer AG, CropScience Division, R&D Pest Control, D-40789 Monheim, Germany
| | - Ralf Nauen
- Bayer AG, CropScience Division, R&D Pest Control, D-40789 Monheim, Germany
| | - Philip Batterham
- School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Sven Geibel
- Bayer AG, CropScience Division, R&D Pest Control, D-40789 Monheim, Germany
| | - John Vontas
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 100N. Plastira Street, 700 13 Heraklion Crete, Greece,Laboratory of Pesticide Science, Department of Crop Science, Agricultural University of Athens, Greece
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20
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Krishnan S, Ramsden D, Ferguson D, Stahl SH, Wang J, McGinnity DF, Hariparsad N. Challenges and Opportunities for Improved Drug-Drug Interaction Predictions for Renal OCT2 and MATE1/2-K Transporters. Clin Pharmacol Ther 2022; 112:562-572. [PMID: 35598119 DOI: 10.1002/cpt.2666] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 05/13/2022] [Indexed: 11/08/2022]
Abstract
Transporters contribute to renal elimination of drugs; therefore drug disposition can be impacted if transporters are inhibited by comedicant drugs. Regulatory agencies have provided guidelines to assess potential drug-drug interaction (DDI) risk for renal organic cation transporter 2 (OCT2) and multidrug and toxin extrusion 1 and 2-K (MATE1/2-K) transporters. Despite this, there are challenges with translating in vitro data using currently available tools to obtain a quantitative assessment of DDI risk in the clinic. Given the high number of drugs and new molecular entities showing in vitro inhibition toward OCT2 and/or MATE1/2-K and the lack of translation to clinically significant effects, it is reasonable to question whether the current in vitro assay design and modeling practice has led to unnecessary clinical evaluation. The aim of this review is to assess and discuss available in vitro and clinical data along with prediction models intended to provide clinical context of risk, including static models proposed by regulatory agencies and physiologically-based pharmacokinetic models, in order to identify best practices and areas of future opportunity. This analysis highlights that different in vitro assay designs, including substrate and cell systems used, strongly influence the derived concentration of drug producing 50% inhibition values and contribute to high variability observed across laboratories. Furthermore, the lack of sensitive index substrates coupled with specific inhibitors for individual transporters necessitates the use of complex models to evaluate clinical DDI risk.
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Affiliation(s)
- Srinivasan Krishnan
- Drug Metabolism and Pharmacokinetics, Oncology Research & Development, AstraZeneca, Boston, Massachusetts, USA
| | - Diane Ramsden
- Drug Metabolism and Pharmacokinetics, Oncology Research & Development, AstraZeneca, Boston, Massachusetts, USA
| | - Douglas Ferguson
- Drug Metabolism and Pharmacokinetics, Oncology Research & Development, AstraZeneca, Boston, Massachusetts, USA
| | - Simone H Stahl
- Cardiovascular, Renal, and Metabolism Safety, Clinical Pharmacology and Safety Sciences, Research & Development, AstraZeneca, Cambridge, UK
| | - Joanne Wang
- Department of Pharmaceutics, University of Washington, Seattle, Washington, USA
| | - Dermot F McGinnity
- Drug Metabolism and Pharmacokinetics, Oncology Research & Development, AstraZeneca, Cambridge, UK
| | - Niresh Hariparsad
- Drug Metabolism and Pharmacokinetics, Oncology Research & Development, AstraZeneca, Boston, Massachusetts, USA
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21
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Yabut J, Houle R, Wang S, Liaw A, Katwaru R, Collier H, Hittle L, Chu X. Selection of an optimal in vitro model to assess P-gp inhibition: comparison of vesicular and bi-directional transcellular transport inhibition assays. Drug Metab Dispos 2022; 50:909-922. [PMID: 35489778 DOI: 10.1124/dmd.121.000807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/04/2022] [Indexed: 11/22/2022] Open
Abstract
The multidrug resistance protein 1 (MDR1) P-glycoprotein (P-gp) is a clinically important transporter. In vitro P-gp inhibition assays have been routinely conducted to predict the potential for clinical drug-drug interactions (DDIs) mediated by P-gp. However, high inter- laboratory and inter-system variability of P-gp IC50 data limits accurate prediction of DDIs using static models and decision criteria recommended by regulatory agencies. In this study, we calibrated two in vitro P-gp inhibition models: vesicular uptake of N-methyl-quinidine (NMQ) in MDR1 vesicles and bidirectional transport (BDT) of digoxin in Lilly Laboratories Cell Porcine Kidney 1 cells overexpressing MDR1 (LLC-MDR1) using a total of 48 P-gp inhibitor and non-inhibitor drugs, and digoxin DDI data from 70 clinical studies. Refined thresholds were derived using receiver operating characteristic (ROC) analysis and their predictive performance was compared with the decision frameworks proposed by regulatory agencies and selected reference. Furthermore, the impact of various IC50 calculation methods and non-specific binding of drugs on DDI prediction was evaluated. Our studies suggest that the concentration of inhibitor based on highest approved dose dissolved in 250 ml divided by IC50(I2/IC50) is sufficient to predict P-gp related intestinal DDIs. IC50 obtained from vesicular inhibition assay with a refined threshold of I2/IC50 {greater than or equal to} 25.9 provides comparable predictive power than those measured by net secretory flux and efflux ratio in LLC-MDR1 cells. We therefore recommend vesicular P-gp inhibition as our preferred method given its simplicity, lower variability, higher assay throughput, and more direct estimation of in vitro kinetic parameters than BDT assay. Significance Statement We have conducted comprehensive calibration of two in vitro P-gp inhibition models: uptake in MDR1 vesicles and bidirectional transport in LLC-MDR1 cell monolayers to predict DDIs. Our studies suggest that IC50s obtained from vesicular inhibition with a refined threshold of I2/IC50 ≥ 25.9 provide comparable predictive power than those in LLC-MDR1 cells. We therefore recommend vesicular P-gp inhibition as preferred method given its simplicity, lower variability, higher assay throughput, and more direct estimation of in vitro kinetic parameters.
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Affiliation(s)
| | | | | | | | | | | | | | - Xiaoyan Chu
- Pharmacokinetics, Pharmacodynamics and Drug Metabolism, Merck & Co., Inc., United States
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22
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Millones Gómez PA, Tay Chu Jon LY, Maurtua Torres DJ, Bacilio Amaranto RE, Collantes Díaz IE, Minchón Medina CA, Calla Choque JS. Antibacterial, antibiofilm, and cytotoxic activities and chemical compositions of Peruvian propolis in an in vitro oral biofilm. F1000Res 2022; 10:1093. [PMID: 34853678 PMCID: PMC8613507 DOI: 10.12688/f1000research.73602.2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/13/2021] [Indexed: 12/27/2022] Open
Abstract
Background: Natural products with antibacterial potential have begun to be tested on biofilm models, bringing us closer to understanding the response generated by the complex microbial ecosystems of the oral cavity. The objective of this study was to evaluate the antibacterial, antibiofilm, and cytotoxic activities and chemical compositions of Peruvian propolis in an
in vitro biofilm of
Streptococcus gordonii and
Fusobacterium nucleatum. Methods: The experimental work involved a consecutive,
in vitro, longitudinal, and double-blinded study design. Propolis samples were collected from 13 different regions of the Peruvian Andes. The disk diffusion method was used for the antimicrobial susceptibility test. The cytotoxic effect of propolis on human gingival fibroblasts was determined by cell viability method using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay, and the effect of propolis on the biofilm was evaluated by confocal microscopy and polymerase chain reaction (PCR). Results: The 0.78 mg/mL and 1.563 mg/mL concentrations of the methanolic fraction of the chloroform residue of Oxapampa propolis showed effects on biofilm thickness and the copy numbers of the
srtA gene of
S. gordonii and the
radD gene of
F. nucleatum at 48 and 120 hours, and chromatography (UV, λ 280 nm) identified rhamnocitrin, isorhamnetin, apigenin, kaempferol, diosmetin, acacetin, glycerol, and chrysoeriol. Conclusions: Of the 13 propolis evaluated, it was found that only the methanolic fraction of Oxapampa propolis showed antibacterial and antibiofilm effects without causing damage to human gingival fibroblasts. Likewise, when evaluating the chemical composition of this fraction, eight flavonoids were identified.
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Affiliation(s)
- Pablo Alejandro Millones Gómez
- Facultad de Medicina, Universidad Señor de Sipán, Chiclayo, 14000, Peru.,Faculty of Dentistry, Universidad Peruana Cayetano Heredia, Lima, 07001, Peru
| | | | | | | | | | - Carlos Alberto Minchón Medina
- Department of Statistics, Faculty of Physical Sciences and Mathematics, Universidad Nacional de Trujillo, Trujillo, 13001, Peru
| | - Jaeson Santos Calla Choque
- Department of Pediatrics, School of Medicine, University of California San Diego (UCSD), La Jolla, CA, 92093, USA
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23
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Ozgür B, Saaby L, Janfelt C, Langthaler K, Eneberg E, Jacobsen AM, Badolo L, Montanari D, Brodin B. Screening novel CNS drug candidates for P-glycoprotein interactions using the cell line iP-gp: In vitro efflux ratios from iP-gp and MDCK-MDR1 monolayers compared to brain distribution data from mice. Eur J Pharm Biopharm 2021; 169:211-219. [PMID: 34756975 DOI: 10.1016/j.ejpb.2021.10.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 09/17/2021] [Accepted: 10/14/2021] [Indexed: 01/16/2023]
Abstract
Drug efflux by P-glycoprotein (P-gp, ABCB1) is considered as a major obstacle for brain drug delivery for small molecules. P-gp-expressing cell monolayers are used for screening of new drug candidates during early states of drug development. It is, however, uncertain how well the in vitro studies can predict the in vivo P-gp mediated efflux at the blood-brain barrier (BBB). We previously developed a novel cell line of porcine origin, the iP-gp cell line, with high transepithelial resistance and functional expression of human P-gp. The aim of the present study was to evaluate the applicability of the cell line for screening of P-gp interactions of novel drug candidates. For this purpose, bidirectional fluxes of 14 drug candidates were measured in iP-gp cells and in MDCK-MDR1 cells, and compared with pharmacokinetic data obtained in male C57BL/6 mice. The iP-gp cells formed extremely tight monolayers (>15 000 Ω∙cm2) as compared to the MDCK- MDR1 cells (>250 Ω∙cm2) and displayed lower Papp,a-b values. The efflux ratios obtained with iP-gp and MDCK-MDR1 monolayers correlated with Kp,uu,brain values from the in vivo studies, where compounds with the lowest Kp,uu,brain generally displayed the highest efflux ratios. 12 of the tested compounds displayed a poor BBB penetration in mice as judged by Kp,uu less than 1. Of these compounds, nine compounds were categorized as P-gp substrates in the iP-gp screening, whereas analysis of data estimated in MDCK-MDR1 cells indicated four compounds as potential substrates. The results suggest that the iP-gp cell model may be a sensitive and useful screening tool for drug screening purposes to identify possible substrates of human P-glycoprotein.
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Affiliation(s)
- Burak Ozgür
- Department of Pharmacy, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark
| | - Lasse Saaby
- Department of Pharmacy, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark; Bioneer-FARMA, Department of Pharmacy, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark
| | - Christian Janfelt
- Department of Pharmacy, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark
| | | | - Elin Eneberg
- H. Lundbeck A/S, Ottiliavej 9, 2500 Valby, Denmark
| | | | | | | | - Birger Brodin
- Department of Pharmacy, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark.
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24
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Türk D, Fuhr LM, Marok FZ, Rüdesheim S, Kühn A, Selzer D, Schwab M, Lehr T. Novel models for the prediction of drug-gene interactions. Expert Opin Drug Metab Toxicol 2021; 17:1293-1310. [PMID: 34727800 DOI: 10.1080/17425255.2021.1998455] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
INTRODUCTION Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs. AREAS COVERED Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations. EXPERT OPINION Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.
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Affiliation(s)
- Denise Türk
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
| | | | | | - Simeon Rüdesheim
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany.,Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
| | - Anna Kühn
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
| | - Dominik Selzer
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany.,Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University of Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC2180) "Image-guided and Functionally Instructed Tumor Therapies," University of Tübingen, Tübingen, Germany
| | - Thorsten Lehr
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
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25
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Yamazaki S, Evers R, De Zwart L. Physiologically-based pharmacokinetic modeling to evaluate in vitro-to-in vivo extrapolation for intestinal P-glycoprotein inhibition. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 11:55-67. [PMID: 34668334 PMCID: PMC8752109 DOI: 10.1002/psp4.12733] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/12/2021] [Accepted: 10/12/2021] [Indexed: 11/08/2022]
Abstract
As one of the key components in model‐informed drug discovery and development, physiologically‐based pharmacokinetic (PBPK) modeling linked with in vitro‐to‐in vivo extrapolation (IVIVE) is widely applied to quantitatively predict drug–drug interactions (DDIs) on drug‐metabolizing enzymes and transporters. This study aimed to investigate an IVIVE for intestinal P‐glycoprotein (Pgp, ABCB1)‐mediated DDIs among three Pgp substrates, digoxin, dabigatran etexilate, and quinidine, and two Pgp inhibitors, itraconazole and verapamil, via PBPK modeling. For Pgp substrates, assuming unbound Michaelis‐Menten constant (Km) to be intrinsic, in vitro‐to‐in vivo scaling factors for maximal Pgp‐mediated efflux rate (Jmax) were optimized based on the clinically observed results without co‐administration of Pgp inhibitors. For Pgp inhibitors, PBPK models utilized the reported in vitro values of Pgp inhibition constants (Ki), 1.0 μM for itraconazole and 2.0 μM for verapamil. Overall, the PBPK modeling sufficiently described Pgp‐mediated DDIs between these substrates and inhibitors with the prediction errors of less than or equal to ±25% in most cases, suggesting a reasonable IVIVE for Pgp kinetics in the clinical DDI results. The modeling results also suggest that Pgp kinetic parameters of both the substrates (Km and Jmax) and the inhibitors (Ki) are sensitive to Pgp‐mediated DDIs, thus being key for successful DDI prediction. It would also be critical to incorporate appropriate unbound inhibitor concentrations at the site of action into PBPK models. The present results support a quantitative prediction of Pgp‐mediated DDIs using in vitro parameters, which will significantly increase the value of in vitro studies to design and run clinical DDI studies safely and effectively.
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Affiliation(s)
- Shinji Yamazaki
- Drug Metabolism & Pharmacokinetics, Janssen Research & Development, LLC, San Diego, California, USA
| | - Raymond Evers
- Drug Metabolism & Pharmacokinetics, Janssen Research & Development, LLC, Spring House, Pennsylvania, USA
| | - Loeckie De Zwart
- Drug Metabolism & Pharmacokinetics, Janssen Research & Development, Beerse, Belgium
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26
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Ning C, Su S, Li J, Kong D, Cai H, Qin Z, Xing H, Chen X, He J. Evaluation of a Clinically Relevant Drug-Drug Interaction Between Rosuvastatin and Clopidogrel and the Risk of Hepatotoxicity. Front Pharmacol 2021; 12:715577. [PMID: 34646133 PMCID: PMC8504577 DOI: 10.3389/fphar.2021.715577] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 08/06/2021] [Indexed: 11/25/2022] Open
Abstract
Purpose: The combination therapy of rosuvastatin (RSV) and the platelet inhibitor clopidogrel (CP) is widely accepted in the management of cardiovascular diseases. The objective of the present study was to identify the mechanism of RSV–CP DDI and evaluate the risk of hepatotoxicity associated with the concomitant use of CP. Methods: We first studied the effect of CP and its major circulating metabolite, carboxylic acid metabolite (CPC), on RSV transport by overexpressing cells and membrane vesicles. Second, we investigated whether a rat model could replicate this DDI and then be used to conduct mechanistic studies and assess the risk of hepatotoxicity. Then, cytotoxicity assay in hepatocytes, biochemical examination, and histopathology were performed to measure the magnitude of liver injury in the presence and absence of DDI. Results: CP inhibited OATP1B1-mediated transport of RSV with an IC50 value of 27.39 μM. CP and CPC inhibited BCRP-mediated RSV transport with IC50 values of <0.001 and 5.96 μM, respectively. The CP cocktail (0.001 μM CP plus 2 μM CPC) significantly inhibited BCRP-mediated transport of RSV by 26.28%. Multiple p.o. doses of CP significantly increased intravenous RSV plasma AUC0-infinity by 76.29% and decreased intravenous RSV CL by 42.62%. Similarly, multiple p.o. doses of CP significantly increased p.o. RSV plasma AUC0-infinity by 87.48% and decreased p.o. RSV CL by 43.27%. CP had no effect on cell viability, while RSV exhibited dose-dependent cytotoxicity after 96 h incubation. Co-incubation of 100 μM CP and RSV for 96 h significantly increased intracellular concentrations and cell-to-medium concentration ratios of RSV and reduced hepatocyte viability. Histological evaluation of liver specimens showed patterns of drug-induced liver injury. Cholestasis was found in rats in the presence of DDI. Conclusion: CP is not a clinically relevant inhibitor for OATP1B1 and OATP1B3. The primary mechanism of RSV–CP DDI can be attributed to the inhibition of intestinal BCRP by CP combined with the inhibition of hepatic BCRP by CPC. The latter is likely to be more clinically relevant and be a contributing factor for increased hepatotoxicity in the presence of DDI.
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Affiliation(s)
- Chen Ning
- Department of Pharmacy, The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Shengdi Su
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Jiaming Li
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Dexuan Kong
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Hui Cai
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Zhiying Qin
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Han Xing
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Xijing Chen
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Jiake He
- Department of Pharmacy, The Second Affiliated Hospital of Nanchang University, Nanchang, China.,Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.,Department of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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27
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Trivedi A, Sohn W, Kulkarni P, Jafarinasabian P, Zhang H, Spring M, Flach S, Abbasi S, Wahlstrom J, Lee E, Dutta S. Evaluation of drug-drug interaction potential between omecamtiv mecarbil and rosuvastatin, a BCRP substrate, with a clinical study in healthy subjects and using a physiologically-based pharmacokinetic model. Clin Transl Sci 2021; 14:2510-2520. [PMID: 34415673 PMCID: PMC8604240 DOI: 10.1111/cts.13118] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 07/14/2021] [Accepted: 07/23/2021] [Indexed: 11/30/2022] Open
Abstract
Omecamtiv mecarbil (OM) is a novel cardiac myosin activator in development for the treatment of heart failure. In vitro, OM is an inhibitor of BCRP. Rosuvastatin, a BCRP substrate, is one of the most commonly prescribed medications in patients with heart failure. The potential for a pharmacokinetic (PK) drug‐drug interaction (DDI) was investigated, specifically to determine whether a single 50 mg dose of OM would impact the PKs of a single 10 mg dose of rosuvastatin in an open‐label study in 14 healthy subjects. The ratios of the geometric least‐square means (90% confidence intervals [CIs]) of rosuvastatin co‐administered with OM compared to rosuvastatin alone were 127.1% (90% CI 113.8–141.9), 132.8% (90% CI 120.7–146.1), and 154.2% (90% CI 132.8–179.1) for area under the plasma‐concentration time curve from time zero to infinity (AUCinf), area under the plasma‐concentration time curve from time zero to time of last quantifiable concentration (AUClast), and maximum observed plasma concentration (Cmax), respectively. Whereas the DDI study with rosuvastatin was conducted with the co‐administration of a single dose of OM, in the clinical setting, patients receive OM at doses of 25, 37.5, or 50 mg twice daily (b.i.d.). Hence, to extrapolate the results of the DDI study to a clinically relevant scenario of continuous b.i.d. dosing with OM, physiologically‐based pharmacokinetic (PBPK) modeling was performed to explore the potential of BCRP inhibition following continuous b.i.d. dosing of OM at the highest 50 mg dose. Modeling results indicated that following 50 mg b.i.d. dosing of OM, the predicted ratios of the geometric means (90% CIs) for rosuvastatin AUCinf and Cmax were 1.18 (90% CI 1.16–1.20) and 2.04 (90% CI 1.99–2.10), respectively. Therefore, these results suggest that OM, following multiple dose administration, is a weak inhibitor of BCRP substrates and is in accordance with that observed in the single dose OM DDI clinical study.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Edward Lee
- Amgen, Inc, Thousand Oaks, California, USA
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Reus P, Schneider AK, Ulshöfer T, Henke M, Bojkova D, Cinatl J, Ciesek S, Geisslinger G, Laux V, Grättinger M, Gribbon P, Schiffmann S. Characterization of ACE Inhibitors and AT 1R Antagonists with Regard to Their Effect on ACE2 Expression and Infection with SARS-CoV-2 Using a Caco-2 Cell Model. Life (Basel) 2021; 11:life11080810. [PMID: 34440554 PMCID: PMC8399150 DOI: 10.3390/life11080810] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 07/29/2021] [Accepted: 08/06/2021] [Indexed: 12/18/2022] Open
Abstract
Blood-pressure-lowering drugs are proposed to foster SARS-CoV-2 infection by pharmacological upregulation of angiotensin-converting enzyme 2 (ACE2), the binding partner of the virus spike (S) protein, located on the surface of the host cells. Conversely, it is postulated that angiotensin–renin system antagonists may prevent lung damage caused by SARS-CoV-2 infection, by reducing angiotensin II levels, which can induce permeability of lung endothelial barrier via its interaction with the AT1 receptor (AT1R). Methods: We have investigated the influence of the ACE inhibitors (lisinopril, captopril) and the AT1 antagonists (telmisartan, olmesartan) on the level of ACE2 mRNA and protein expression as well as their influence on the cytopathic effect of SARS-CoV-2 and on the cell barrier integrity in a Caco-2 cell model. Results: The drugs revealed no effect on ACE2 mRNA and protein expression. ACE inhibitors and AT1R antagonist olmesartan did not influence the infection rate of SARS-CoV-2 and were unable to prevent the SARS-CoV-2-induced cell barrier disturbance. A concentration of 25 µg/mL telmisartan significantly reduced the virus replication rate. Conclusion: ACE inhibitors and AT1R antagonist showed neither beneficial nor detrimental effects on SARS-CoV-2-infection and cell barrier integrity in vitro at pharmacologically relevant concentrations.
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Affiliation(s)
- Philipp Reus
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Paul-Ehrlich-Str. 40, 60596 Frankfurt am Main, Germany; (D.B.); (J.C.)
| | - Ann-Kathrin Schneider
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Thomas Ulshöfer
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Marina Henke
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Denisa Bojkova
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Paul-Ehrlich-Str. 40, 60596 Frankfurt am Main, Germany; (D.B.); (J.C.)
| | - Jindrich Cinatl
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Paul-Ehrlich-Str. 40, 60596 Frankfurt am Main, Germany; (D.B.); (J.C.)
| | - Sandra Ciesek
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Paul-Ehrlich-Str. 40, 60596 Frankfurt am Main, Germany; (D.B.); (J.C.)
| | - Gerd Geisslinger
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
- Pharmazentrum Frankfurt/ZAFES, Department of Clinical Pharmacology, Goethe-University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
- Fraunhofer Cluster of Excellence Immune Mediated Diseases, CIMD, 60596 Frankfurt am Main, Germany
| | - Volker Laux
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Mira Grättinger
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Philip Gribbon
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
| | - Susanne Schiffmann
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Theodor-Stern-Kai 7, 60596 Frankfurt am Main, Germany; (P.R.); (A.-K.S.); (T.U.); (M.H.); (S.C.); (G.G.); (V.L.); (M.G.); (P.G.)
- Fraunhofer Cluster of Excellence Immune Mediated Diseases, CIMD, 60596 Frankfurt am Main, Germany
- Correspondence: ; Tel.: +49-69-870025060; Fax: +49-69-870010000
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Asano S, Yoshitomo A, Hozuki S, Sato H, Kazuki Y, Hisaka A. A New Intestinal Model for Analysis of Drug Absorption and Interactions Considering Physiological Translocation of Contents. Drug Metab Dispos 2021; 49:581-591. [PMID: 33962977 DOI: 10.1124/dmd.121.000361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/09/2021] [Indexed: 11/22/2022] Open
Abstract
Precise prediction of drug absorption is key to the success of new drug development and efficacious pharmacotherapy. In this study, we developed a new absorption model, the advanced translocation model (ATOM), by extending our previous model, the translocation model. ATOM reproduces the translocation of a substance in the intestinal lumen using a partial differential equation with variable dispersion and convection terms to describe natural flow and micromixing within the intestine under not only fasted but also fed conditions. In comparison with ATOM, it was suggested that a conventional absorption model, advanced compartmental absorption and transit model, tends to underestimate micromixing in the upper intestine, and it is difficult to adequately describe movements under the fasted and fed conditions. ATOM explains the observed nonlinear absorption of midazolam successfully, with a minimal number of scaling factors. Furthermore, ATOM considers the apical and basolateral membrane permeabilities of enterocytes separately and assumes compartmentation of the lamina propria, including blood vessels, to consider intestinal blood flow appropriately. ATOM estimates changes in the intestinal availability caused by drug interaction associated with inhibition of CYP3A and P-glycoprotein in the intestine. Additionally, ATOM can estimate the drug absorption in the fed state considering delayed intestinal drug flow. Therefore, ATOM is a useful tool for the analysis of local pharmacokinetics in the gastrointestinal tract, especially for the estimation of nonlinear drug absorption, which may involve various interactions with intestinal contents or other drugs. SIGNIFICANCE STATEMENT: The newly developed advanced translocation model precisely explains various movements of intestinal contents under fasted and fed conditions, which cannot be adequately described by the current physiological pharmacokinetic models.
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Affiliation(s)
- Satoshi Asano
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
| | - Aoi Yoshitomo
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
| | - Shizuka Hozuki
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
| | - Hiromi Sato
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
| | - Yasuhiro Kazuki
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
| | - Akihiro Hisaka
- Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan (S.A., A.Y., S.H., H.S., A.H.); DMPK Research Department, Teijin Pharma Limited, Tokyo, Japan (S.A.); Chromosome Engineering Research Center (Y.K.) and Division of Genome and Cellular Functions, Department of Molecular and Cellular Biology, School of Life Science, Faculty of Medicine (Y.K.), Tottori University, Tottori, Japan
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Reinoso RF, Yeste S, Ayet E, Pretel MJ, Balada A, Serafini MT. Preliminary in vitro assessment of pharmacokinetic drug-drug interactions of EST64401 and EST64514, two sigma-1 receptor antagonists. Xenobiotica 2021; 51:373-386. [PMID: 33350877 DOI: 10.1080/00498254.2020.1867332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/17/2020] [Accepted: 12/17/2020] [Indexed: 01/22/2023]
Abstract
EST64401 and EST64514 are two selective sigma-1 receptor ligands that showed a good profile in a lead optimization process for oral pain treatment. Their potential for pharmacokinetic-based drug-drug interactions was assessed to anticipate clinical interactions.Both compounds showed a low potential for CYP inhibition with percentages of inhibition <50% at 1 µM in recombinant human CYPs (CYP1A2, 2C9, 2C19, 2D6 and 3A4) and IC50 ≥75 µM for CYP3A4 and 2D6 in human liver microsomes.No CYP induction was observed for CYP1A2, 2B6 and 3A4 at concentrations ≤25 µM (EST64401) or ≤50 µM (EST64514) in human hepatocytes using as endpoints CYP activities and mRNA levels.More than one enzyme participated in compound metabolism. The main enzymes involved were CYP3A4 for EST64401 and CYP2D6 besides CYP3A4 for EST64514.Neither EST64401 nor EST64514 seemed to be substrates of P-gp or BCRP in Caco-2 cells (efflux ratio ≤2). Transporter inhibition was observed at concentrations ≥20 µM; EST64401 only inhibiting P-gp at higher concentrations (≥125 µM).Preliminary in vitro interaction studies suggest a similar profile for EST64401 and EST64514. Therefore, other properties will have to be considered for compound differentiation and selection for further development.
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Affiliation(s)
- Raquel F Reinoso
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
| | - Sandra Yeste
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
| | - Eva Ayet
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
| | - María José Pretel
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
| | - Ariadna Balada
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
| | - Maria Teresa Serafini
- Early ADME, Drug Discovery and Preclinical Development, ESTEVE Pharmaceuticals, Barcelona, Spain
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Rowbottom C, Pietrasiewicz A, Tuczewycz T, Grater R, Qiu D, Kapadnis S, Trapa P. Optimization of dose and route of administration of the P-glycoprotein inhibitor, valspodar (PSC-833) and the P-glycoprotein and breast cancer resistance protein dual-inhibitor, elacridar (GF120918) as dual infusion in rats. Pharmacol Res Perspect 2021; 9:e00740. [PMID: 33660938 PMCID: PMC7931226 DOI: 10.1002/prp2.740] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 02/01/2021] [Indexed: 01/16/2023] Open
Abstract
Transporters can play a key role in the absorption, distribution, metabolism, and excretion of drugs. Understanding these contributions early in drug discovery allows for more accurate projection of the clinical pharmacokinetics. One method to assess the impact of transporters in vivo involves co‐dosing specific inhibitors. The objective of the present study was to optimize the dose and route of administration of a P‐glycoprotein (P‐gp) inhibitor, valspodar (PSC833), and a dual P‐gp/breast cancer resistance protein (BCRP) inhibitor, elacridar (GF120918), by assessing the transporters’ impact on brain penetration and absorption. A dual‐infusion strategy was implemented to allow for flexibility with dose formulation. The chemical inhibitor was dosed intravenously via the femoral artery, and a cassette of known substrates was infused via the jugular vein. Valspodar or elacridar was administered as 4.5‐hour constant infusions over a range of doses. To assess the degree of inhibition, the resulting ratios of brain and plasma concentrations, Kp's, of the known substrates were compared to the vehicle control. These data demonstrated that doses greater than 0.9 mg/hr/kg valspodar and 8.9 mg/hr/kg elacridar were sufficient to inhibit P‐gp‐ and BCRP‐mediated efflux at the blood‐brain barrier in rats without any tolerability issues. Confirmation of BBB restriction by efflux transporters in preclinical species allows for subsequent prediction in humans based upon the proteomic expression at rodent and human BBB. Overall, the approach can also be applied to inhibition of efflux at other tissues (gut absorption, liver clearance) or can be extended to other transporters of interest using alternate inhibitors.
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Bruyère A, Le Vée M, Jouan E, Molez S, Nies AT, Fardel O. Differential in vitro interactions of the Janus kinase inhibitor ruxolitinib with human SLC drug transporters. Xenobiotica 2021; 51:467-478. [PMID: 33455503 DOI: 10.1080/00498254.2021.1875516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Interactions of the Janus kinase (JAK) inhibitor ruxolitinib with solute carriers (SLCs) remain incompletely characterised. The present study was therefore designed to investigate this issue.The interactions of ruxolitinib with SLCs were analysed using transporter-overexpressing human embryonic kidney HEK293 cells. Substrate accumulation was detected by spectrofluorimetry, liquid chromatography coupled to tandem mass spectrometry or scintillation counting.Ruxolitinib was found to potently inhibit the activities of organic anion transporter 3 (OAT3), organic cation transporter 2 (OCT2), multidrug and toxin extrusion 1 (MATE1) and MATE2-K (half maximal inhibitory concentration (IC50) < 10 µM). It blocked OAT1, OAT4, OATP1B1, OATP1B3, OATP2B1 and OCT3, but in a weaker manner (IC50 > 10 µM), whereas OCT1 was not impacted. No time-dependent inhibition was highlighted. When applying the US Food and Drug Administration (FDA) criteria for transporters-related drug-drug interaction risk, OCT2 and MATE2-K, unlike MATE1 and OAT3, were predicted to be in vivo inhibited by ruxolitinib. Cellular uptake studies additionally indicated that ruxolitinib is a substrate for MATE1 and MATE2-K, but not for OAT3 and OCT2.Ruxolitinib in vitro blocked activities of most of SLC transporters. Only OCT2 and MATE-2K may be however clinically inhibited by the JAK inhibitor, with the caution for OCT2 that in vitro inhibition data were generated with an FDA-non recommended fluorescent substrate. Ruxolitinib MATEs-mediated transport may additionally deserve attention for its possible pharmacological consequences in MATE-positive cells.
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Affiliation(s)
- Arnaud Bruyère
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France
| | - Marc Le Vée
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France
| | - Elodie Jouan
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France
| | - Stephanie Molez
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France
| | - Anne T Nies
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart and University of Tübingen, Stuttgart, Germany.,iFIT Cluster of Excellence (EXC2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Olivier Fardel
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes, France
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Bentz J, Ellens H. Case Study 8: Status of the Structural Mass Action Kinetic Model of P-gp-Mediated Transport Through Confluent Cell Monolayers. Methods Mol Biol 2021; 2342:737-763. [PMID: 34272715 DOI: 10.1007/978-1-0716-1554-6_27] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In the first edition of this book, we presented the basics of explicitly incorporating the lipid biochemistry into a confluent cell monolayer transport model and the novel findings of this model up to 2013, including the use of global optimization to fit the elementary rate constants and the efflux active P-glycoprotein (P-gp) membrane concentrations for the transport of four P-gp substrates across MDCKII-hMDR1-NKI confluent cell monolayers. This chapter is an update on that model, which has been focused primarily on discovering how microvilli morphology regulates the efflux active P-gp and the existence of, as yet, unidentified uptake transporters of P-gp substrates in all of the commonly used P-gp expressing cell lines used in the pharmaceutical industry, thereby adding new players to DDI predictions and IVIVE. The structural mass action kinetic model uses the general mass action reactions for P-gp binding and efflux, with the membrane structural parameters for the confluent cell monolayer to predict drug transport over time. Binding of drug to P-gp occurs within the cytosolic monolayer of the apical membrane, according to (a) the molar partition coefficient of the drug to the cytosolic monolayer and (b) the association rate constant, k1 (M-1 s-1), of the drug from the basolateral or apical outer monolayers into the P-gp binding site. Release of substrate from P-gp back into the cytosolic monolayer occurs with a dissociation rate constant kr (s-1) or, much less frequently, into the apical aqueous chamber with an efflux rate constant k2 (s-1). The model fits the efflux active P-gp concentration, T(0), i.e., the P-gp whose effluxed drug actually reaches the apical aqueous chamber, as opposed to the majority of P-gp whose effluxed drug is reabsorbed back into the same or neighboring microvilli prior to reaching the apical aqueous chamber. Efflux active P-gp largely resides near the tips of the microvilli. We have shown using kinetics and structured illumination microscopy that: (a) efflux active P-gp is controlled by microvilli morphology; (b) there are apical (AT) and basolateral (BT) uptake transporters for P-gp substrates in most, if not all, P-gp expressing cell lines used in the pharmaceutical industry, which exist, but which remain unidentified; (c) the lab-to-lab variability in P-gp IC50 values observed in the P-gp IC50 initiative was due to the conflated inhibition of P-gp and the basolateral digoxin uptake transporters by all 15 P-gp substrates tested in that study; (d) even the IC50 values for P-gp inhibition alone do not obey the Cheng-Prusoff relationship; (e) the fitted elementary rate constants and the molecular dissociation constant Ki for this kinetic model are system independent; and (f) the time dependence of product formation for these confluent cell monolayers is correlated with the P-gp Vmax/Km, when defined by its fitted elementary rate constants and uptake transporter clearances, without any steady-state assumptions.
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Affiliation(s)
- Joe Bentz
- Department of Biology, Drexel University, Philadelphia, PA, USA.
| | - Harma Ellens
- GlaxoSmithKline Pharmaceuticals, Drug Metabolism and Pharmacokinetics, King of Prussia, PA, USA
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Yu D, Kan Z, Shan F, Zang J, Zhou J. Triple Strategies to Improve Oral Bioavailability by Fabricating Coamorphous Forms of Ursolic Acid with Piperine: Enhancing Water-Solubility, Permeability, and Inhibiting Cytochrome P450 Isozymes. Mol Pharm 2020; 17:4443-4462. [PMID: 32926628 DOI: 10.1021/acs.molpharmaceut.0c00443] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
As a BCS IV drug, ursolic acid (UA) has low oral bioavailability mainly because of its poor aqueous solubility/dissolution, poor permeability, and metabolism by cytochrome P450 (CYP) isozymes, such as CYP3A4. Most UA preparations demonstrated a much higher dissolution than that of its crystalline form yet a low drug concentration in plasma due to their lower consideration or evaluation for the permeability and metabolism issues. In the current study, a supramolecular coamorphous system of UA with piperine (PIP) was prepared and characterized by powder X-ray diffraction, differential scanning calorimetry, and scanning electron microscopy. In comparison to crystalline UA and UA in physical mixture, such coamorphous system enhanced solubility (5.3-7-fold in the physiological solution) and dissolution (7-8-fold in the physiological solution within 2 h) of UA and exhibited excellent physical stability under 90-day storage conditions. More importantly, the pharmacokinetic study of coamorphous UA in rats exhibited 5.8-fold and 2.47-fold improvement in AUC0-∞ value, respectively, compared with its free and mixed crystalline counterparts. In order to further explore the mechanism of such improvement, the molecular interactions of a coamorphous system in the solid state were investigated. Fourier transform infrared spectroscopy, solid-state 13C nuclear magnetic resonance spectroscopy, and density functional theory modeling suggested that intermolecular hydrogen bonds with strong interactions newly formed between UA and PIP after coamorphization. The in vitro permeability studies across Caco-2 cell monolayer and metabolism studies by rat hepatic microsomes indicated that free PIP significantly increased the permeability of UA and inhibited the enzymatic metabolism of UA by CYP3A4. However, PIP in the coamorphous combination exhibited a much lower level in the bioenhancing than its free form arising from the synchronized dissolution characteristic of the preparation (only 60% of PIP released in comparison to its free counterpart in 2 h). The in situ loop study in rats proposed that the acid-sensitive dissolution in the stomach of the coamorphous preparation helped to improve the effective free drug concentration, thereby facilitating PIP to play its role in bioenhancing. The current study offers an exploratory strategy to overcome poor solubility/dissolution, poor permeability, and metabolism by cytochrome P450 isozymes of the BCS IV drug to improve its oral bioavailability.
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Affiliation(s)
- Danni Yu
- Key Laboratory of Biomedical Functional Materials, China Pharmaceutical University, Nanjing 211198, PR China
| | - Zigui Kan
- Key Laboratory of Biomedical Functional Materials, China Pharmaceutical University, Nanjing 211198, PR China
- School of Chemistry and Chemical Engineering, Key Laboratory of Mesoscopic Chemistry of MOE, Nanjing University, Nanjing 210093, PR China
| | - Fei Shan
- School of Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Jing Zang
- School of Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
| | - Jianping Zhou
- School of Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China
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Nicklisch SC, Hamdoun A. Disruption of small molecule transporter systems by Transporter-Interfering Chemicals (TICs). FEBS Lett 2020; 594:4158-4185. [PMID: 33222203 PMCID: PMC8112642 DOI: 10.1002/1873-3468.14005] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 11/17/2020] [Accepted: 11/17/2020] [Indexed: 12/25/2022]
Abstract
Small molecule transporters (SMTs) in the ABC and SLC families are important players in disposition of diverse endo- and xenobiotics. Interactions of environmental chemicals with these transporters were first postulated in the 1990s, and since validated in numerous in vitro and in vivo scenarios. Recent results on the co-crystal structure of ABCB1 with the flame-retardant BDE-100 demonstrate that a diverse range of man-made and natural toxic molecules, hereafter termed transporter-interfering chemicals (TICs), can directly bind to SMTs and interfere with their function. TIC-binding modes mimic those of substrates, inhibitors, modulators, inducers, and possibly stimulants through direct and allosteric mechanisms. Similarly, the effects could directly or indirectly agonize, antagonize or perhaps even prime the SMT system to alter transport function. Importantly, TICs are distinguished from drugs and pharmaceuticals that interact with transporters in that exposure is unintended and inherently variant. Here, we review the molecular mechanisms of environmental chemical interaction with SMTs, the methodological considerations for their evaluation, and the future directions for TIC discovery.
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Affiliation(s)
- Sascha C.T. Nicklisch
- Department of Environmental Toxicology, University of California, Davis, Davis, CA 95616
| | - Amro Hamdoun
- Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093-0202
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Hu Y, Gruber KA, Smith DE. Characterization of the cellular transport mechanisms for the anti-cachexia candidate compound TCMCB07. J Cachexia Sarcopenia Muscle 2020; 11:1677-1687. [PMID: 32725770 PMCID: PMC7749613 DOI: 10.1002/jcsm.12602] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 05/27/2020] [Accepted: 06/01/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Cachexia is a debilitating, life-threatening condition whose pathology includes reduced food intake accompanied by hypermetabolism, leading to a catabolic state. The hypothalamic melanocortin system is a critical regulator of metabolic rate with effects being mediated through the melanocortin-4 receptor (MC4R). MC4R activation is also critical to the initiation and maintenance of cachexia. A major problem in the design of anti-cachexia drugs has been the need to cross the blood-brain barrier to access the metabolic rate-controlling centres in the hypothalamus. The overwhelming majority of anti-cachexia drugs are only effective when administered intracerebroventricularly. TCMCB07 is a cyclic nonapeptide peptide MC4R antagonist with parenteral anti-cachexia activity in both small and large animal models. This suggests it can cross the blood-brain barrier. The aim of this study was to examine potential transport mechanisms of TCMCB07 furthering its preclinical development for subsequent studies in humans. METHODS In vitro studies were performed in transporter-transfected cells to study whether or not TCMCB07 was an inhibitor as well as substrate for OATP1A2, OATP1B1, OATP1B3, OATP2B1, OCT2, OAT1, OAT3, MATE1, MATE2-K, P-gp (MDR1), and BCRP. In vivo mass balance studies were also performed in mice to evaluate the absorption and disposition of TCMCB07 after oral and intravenous bolus administrations. RESULTS TCMCB07 inhibited the uptake of prototypical substrates in cells transfected with OATP1A2 (IC50 24.0 μM), OATP1B1 (IC50 6.8 μM), OATP1B3 (IC50 307 μM), OATP2B1 (IC50 524 μM), OCT2 (IC50 1,169 μM), MATE1 (IC50 8.7 μM), and MATE2-K (IC50 20.7 μM) but not in cells transfected with OAT1 and OAT3. TCMCB07 did not affect the P-gp (MDR1)-mediated and BCRP-mediated permeability of prototypical substrates in transfected cells. Importantly, direct evidence was shown for the uptake of TCMCB07 in OATP1A2-transfected cells (i.e. Vmax 236 pmol/mg, Km 58.4 μM, and Kd 0.39 μL/mg), demonstrating that the nonapeptide was a substrate for this transporter. Mass balance studies demonstrated that 24.2% of TCMCB07 was absorbed orally in vivo (P = 0.0033) and excreted primarily in the bile after both oral and intravenous administrations. CONCLUSIONS OATP1A2 is the transporter responsible for the oral absorption of TCMCB07 in the intestine and for its pharmacologic response in the brain.
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Affiliation(s)
- Yongjun Hu
- Department of Pharmaceutical Sciences, College of PharmacyUniversity of MichiganAnn ArborMIUSA
| | | | - David E. Smith
- Department of Pharmaceutical Sciences, College of PharmacyUniversity of MichiganAnn ArborMIUSA
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Sáfár Z, Kecskeméti G, Molnár J, Kurunczi A, Szabó Z, Janáky T, Kis E, Krajcsi P. Inhibition of ABCG2/BCRP-mediated transport-correlation analysis of various expression systems and probe substrates. Eur J Pharm Sci 2020; 156:105593. [PMID: 33059043 DOI: 10.1016/j.ejps.2020.105593] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 09/23/2020] [Accepted: 10/09/2020] [Indexed: 12/14/2022]
Abstract
BCRP / ABCG2 is a key determinant of pharmacokinetics of substrate drugs. Several BCRP substrates and inhibitors are of low passive permeability, and the vesicular transport assay works well in this permeability space. Membranes were prepared from BCRP-HEK293, MCF-7/MX, and baculovirus-infected Sf9 cells with (BCRP-Sf9-HAM), and without (BCRP-Sf9) cholesterol loading. Km values for three substrates - estrone-3-sulfate, sulfasalazine, topotecan - correlated well between the four expression systems. In contrast, a 10-20-fold range in Vmax values was observed, with BCRP-HEK293 membranes possessing the largest dynamic range. IC50 values of the different test systems were similar to each other, with 94.4% of pairwise comparisons being within 3-fold. Substrate dependent inhibition showed somewhat greater variation, as 81.4% of IC50 values in the BCRP-HEK293 membranes were within 3-fold in pairwise comparisons. Overall, BCRP-HEK293 membranes demonstrated the highest activity. The IC50 values showed good concordance but substrate dependent inhibition was observed for some drugs.
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Affiliation(s)
- Zsolt Sáfár
- Solvo Biotechnology, a Charles River Company, 52 Közép fasor, Szeged H-6726, Hungary.
| | - Gábor Kecskeméti
- Department of Medical Chemistry, Faculty of Medicine, University of Szeged, Dóm tér 8, Szeged H-6720, Hungary.
| | - Judit Molnár
- Solvo Biotechnology, a Charles River Company, 52 Közép fasor, Szeged H-6726, Hungary.
| | - Anita Kurunczi
- Solvo Biotechnology, a Charles River Company, 52 Közép fasor, Szeged H-6726, Hungary.
| | - Zoltán Szabó
- Department of Medical Chemistry, Faculty of Medicine, University of Szeged, Dóm tér 8, Szeged H-6720, Hungary.
| | - Tamás Janáky
- Department of Medical Chemistry, Faculty of Medicine, University of Szeged, Dóm tér 8, Szeged H-6720, Hungary.
| | - Emese Kis
- Solvo Biotechnology, a Charles River Company, 52 Közép fasor, Szeged H-6726, Hungary.
| | - Péter Krajcsi
- Solvo Biotechnology, a Charles River Company, 52 Közép fasor, Szeged H-6726, Hungary; Solvo Biotechnology, a Charles River Company, 4-20 Irinyi J str, Budapest H-1117, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter str 50/a, Budapest H-1083, Hungary; Semmelweis University, Faculty of Health Sciences, Vas str 17, Budapest H-1088, Hungary.
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Li N, Kulkarni P, Badrinarayanan A, Kefelegn A, Manoukian R, Li X, Prasad B, Karasu M, McCarty WJ, Knutson CG, Gupta A. P-glycoprotein Substrate Assessment in Drug Discovery: Application of Modeling to Bridge Differential Protein Expression Across In Vitro Tools. J Pharm Sci 2020; 110:325-337. [PMID: 32946896 DOI: 10.1016/j.xphs.2020.09.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 09/07/2020] [Accepted: 09/09/2020] [Indexed: 01/16/2023]
Abstract
P-glycoprotein (P-gp) efflux assay is an integral part of discovery screening, especially for drugs requiring brain penetration as P-gp efflux ratio (ER) inversely correlates with brain exposure. However, significant variability in P-gp ER generated across cell lines can lead to misclassification of a P-gp substrate and subsequently disconnect with brain exposure data. We hypothesized that the ER depends on P-gp protein expression level in the in vitro assay. Quantitative proteomics and immunofluorescence staining were utilized to characterize P-gp protein expression and localization in four recombinant cell lines, over-expressing human or mouse P-gp isoforms, followed by functional evaluation. Efflux data generated in each cell line was compared against available rodent brain distribution data. The results suggested that the cell line with highest P-gp expression (hMDCK-MDR1 sourced from NIH) led to greatest dynamic range for efflux; thus, proving to be the most sensitive model to predict brain penetration. Cell lines with lower P-gp expression exhibited the greatest tendency for compound-dependent in vitro efflux saturation leading to false negative results. Ultimately, P-gp kinetics were characterized using a compartmental model to generate system-independent parameters to resolve such discrepancy. This study highlights the need for careful choice of well characterized P-gp in vitro tools and utility of modeling techniques to enable appropriate interpretation of the data.
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Affiliation(s)
- Na Li
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Priyanka Kulkarni
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Akshay Badrinarayanan
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Adey Kefelegn
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Raffi Manoukian
- Department of Cytometry Sciences, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Xingwen Li
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Bhagwat Prasad
- Department of Pharmaceutical Sciences, Washington State University, Spokane, WA 99202, USA
| | - Matthew Karasu
- Department of Pharmaceutical Sciences, Washington State University, Spokane, WA 99202, USA
| | - William J McCarty
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Charles G Knutson
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA
| | - Anshul Gupta
- Department of Pharmacokinetics and Drug Metabolism, Amgen Research, Amgen Inc, Cambridge, MA 02142, USA.
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Garrison DA, Talebi Z, Eisenmann ED, Sparreboom A, Baker SD. Role of OATP1B1 and OATP1B3 in Drug-Drug Interactions Mediated by Tyrosine Kinase Inhibitors. Pharmaceutics 2020; 12:E856. [PMID: 32916864 PMCID: PMC7559291 DOI: 10.3390/pharmaceutics12090856] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 09/02/2020] [Accepted: 09/02/2020] [Indexed: 12/20/2022] Open
Abstract
Failure to recognize important features of a drug's pharmacokinetic characteristics is a key cause of inappropriate dose and schedule selection, and can lead to reduced efficacy and increased rate of adverse drug reactions requiring medical intervention. As oral chemotherapeutic agents, tyrosine kinase inhibitors (TKIs) are particularly prone to cause drug-drug interactions as many drugs in this class are known or suspected to potently inhibit the hepatic uptake transporters OATP1B1 and OATP1B3. In this article, we provide a comprehensive overview of the published literature and publicly-available regulatory documents in this rapidly emerging field. Our findings indicate that, while many TKIs can potentially inhibit the function of OATP1B1 and/or OATP1B3 and cause clinically-relevant drug-drug interactions, there are many inconsistencies between regulatory documents and the published literature. Potential explanations for these discrepant observations are provided in order to assist prescribing clinicians in designing safe and effective polypharmacy regimens, and to provide researchers with insights into refining experimental strategies to further predict and define the translational significance of TKI-mediated drug-drug interactions.
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Affiliation(s)
| | | | | | - Alex Sparreboom
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA; (D.A.G.); (Z.T.); (E.D.E.)
| | - Sharyn D. Baker
- Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA; (D.A.G.); (Z.T.); (E.D.E.)
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Unger MS, Schumacher L, Enzlein T, Weigt D, Zamek-Gliszczynski MJ, Schwab M, Nies AT, Drewes G, Schulz S, Reinhard FBM, Hopf C. Direct Automated MALDI Mass Spectrometry Analysis of Cellular Transporter Function: Inhibition of OATP2B1 Uptake by 294 Drugs. Anal Chem 2020; 92:11851-11859. [DOI: 10.1021/acs.analchem.0c02186] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Melissa S. Unger
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
- Cellzome - a GlaxoSmithKline company, Meyerhofstr. 1, 69177 Heidelberg, Germany
| | - Lena Schumacher
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
| | - Thomas Enzlein
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
| | - David Weigt
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
| | - Maciej J. Zamek-Gliszczynski
- Drug Metabolism and Pharmacokinetics, GlaxoSmithKline, 1250 S Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute for Clinical Pharmacology, Auerbachstr. 112, 70376 Stuttgart, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tuebingen, 72076 Tuebingen, Germany
- Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University of Tuebingen, Auf der Morgenstelle 8, 72076 Tübingen, Germany
| | - Anne T. Nies
- Dr. Margarete Fischer-Bosch-Institute for Clinical Pharmacology, Auerbachstr. 112, 70376 Stuttgart, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tuebingen, 72076 Tuebingen, Germany
| | - Gerard Drewes
- Cellzome - a GlaxoSmithKline company, Meyerhofstr. 1, 69177 Heidelberg, Germany
| | - Sandra Schulz
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
| | | | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Paul-Wittsack Str. 10, 68163 Mannheim, Germany
- Institute of Medical Technology, Heidelberg University and Mannheim University of Applied Sciences, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
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do Nascimento SB, de Lima Nascimento M, de Araújo LL, de Oliveira FM, do Carmo Vieira M, Duarte-Almeida JM, Siqueira JM, da Costa César I, Derendorf H, de Castro WV. Evaluation of the Effects of Maytenus ilicifolia on the Activities of Cytochrome P450 3A and P-glycoprotein. Curr Drug Metab 2020; 21:281-290. [DOI: 10.2174/1389200221666200512112718] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 02/16/2020] [Accepted: 03/16/2020] [Indexed: 11/22/2022]
Abstract
Background:
Maytenus ilicifolia is a Brazilian popular medicine commonly used to treat ulcer and
gastritis. Despite the absence of toxicity regarding its consumption, possible interactions when co-administrated with
conventional drugs, are unknown.
Objective:
This study aimed to evaluate the effects of M. ilicifolia extracts on Cytochrome P450 3A (CYP3A) and
P-glycoprotein (P-gp) activities.
Method:
The extracts were obtained by infusion (MI) or turbo-extraction using hydro-acetonic solvent (MT70). The
content of polyphenols in each extract was determined. To assess the modulation of M. ilicifolia on P-gp activity, the
uptake of fexofenadine (FEX) by Caco-2 cells was investigated in the absence or presence of MI or MT70. The effect
on CYP3A activity was evaluated by the co-administration of midazolam (MDZ) with each extract in male Wistar
rats. The pharmacokinetic parameters of the drug were determined and compared with those from the control group.
The content of total phenolic compounds, tannins, and flavonoids on MT70 extract was about double of that found in
MI.
Results:
In the presence of the extracts, the uptake of the P-gp marker (FEX) by Caco-2 cells increased from
1.7 ± 0.4 ng.mg-1 protein (control) to 3.5 ± 0.2 ng.mg-1 protein (MI) and 4.4 ± 0.5 ng.mg-1 protein (MT70),
respectively. When orally co-administrated with MDZ (substrate of CYP3A), the extracts augmented the AUC(0-∞)
(Control: 911.7 ± 215.7 ng.h.mL-1; MI: 1947 ± 554.3 ng.h.mL-1; MT70: 2219.0 ± 506.3 ng.h.mL-1) and the
Cmax (Control: 407.7 ± 90.4 ng.mL-1; MI: 1770.5 ± 764.5 ng.mL-1; MT70: 1987.2 ± 544.9 ng.mL-1) of the drug in rats
indicating a 50% reduction of the oral Cl. No effect was observed when midazolam was given intravenously.
Conclusion:
The results suggest that M. ilicifolia can inhibit the intestinal metabolism and transport of drugs
mediated by CYP3A and P-gp, respectively, however, the involvement of other transporters and the clinical
relevance of such interaction still need to be clarified.
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Affiliation(s)
- Sara Batista do Nascimento
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - Mariana de Lima Nascimento
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - Laís Lobato de Araújo
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - Flávio Martins de Oliveira
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - Maria do Carmo Vieira
- Federal University of Grande Dourados R. Joao Rosa Goes, 1761-Vila Progresso, Dourados-MS, CEP: 79825-070, Brazil
| | - Joaquim Maurício Duarte-Almeida
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - João Máximo Siqueira
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
| | - Isabela da Costa César
- Federal University of Minas Gerais, Av. Presidente Antonio Carlos, 667, Campus Pampulha, Belo Horizonte-MG, CEP: 31270-901, Brazil
| | - Hartmut Derendorf
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL 32611, United States
| | - Whocely Victor de Castro
- Federal University of Sao Joao del-Rei, Av. Sebastiao Goncalves Coelho, 400, Campus Centro-Oeste, Chanadour, Divinopolis-MG, CEP: 35501-296, Brazil
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Huang L, Wells MC, Zhao Z. A Practical Perspective on the Evaluation of Small Molecule CNS Penetration in Drug Discovery. Drug Metab Lett 2020; 13:78-94. [PMID: 30854983 DOI: 10.2174/1872312813666190311125652] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 02/20/2019] [Accepted: 03/01/2019] [Indexed: 01/16/2023]
Abstract
The separation of the brain from blood by the blood-brain barrier and the bloodcerebrospinal fluid (CSF) barrier poses unique challenges for the discovery and development of drugs targeting the central nervous system (CNS). This review will describe the role of transporters in CNS penetration and examine the relationship between unbound brain (Cu-brain) and unbound plasma (Cu-plasma) or CSF (CCSF) concentration. Published data demonstrate that the relationship between Cu-brain and Cu-plasma or CCSF can be affected by transporter status and passive permeability of a drug and CCSF may not be a reliable surrogate for CNS penetration. Indeed, CCSF usually over-estimates Cu-brain for efflux substrates and it provides no additional value over Cu-plasma as the surrogate of Cu-brain for highly permeable non-efflux substrates. A strategy described here for the evaluation of CNS penetration is to use in vitro permeability, P-glycoprotein (Pgp) and breast cancer resistance protein efflux assays and Cu-brain/Cu-plasma in preclinical species. Cu-plasma should be used as the surrogate of Cu-brain for highly permeable non-efflux substrates with no evidence of impaired distribution into the brain. When drug penetration into the brain is impaired, we recommend using (total brain concentration * unbound fraction in the brain) as Cu-brain in preclinical species or Cu-plasma/in vitro Pgp efflux ratio if Pgp is the major limiting mechanism for brain penetration.
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Affiliation(s)
- Liyue Huang
- Epizyme Inc, 400 Technology Square, Cambridge, MA-02139, United States
| | - Mary C Wells
- Vertex Pharmaceuticals, 50 Northern Ave, Boston, MA-02210, United States
| | - Zhiyang Zhao
- Alliance Pharma, Inc. 17 Lee Blvd. Malvern, PA-19355, United States
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43
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Unger MS, Mudunuru J, Schwab M, Hopf C, Drewes G, Nies AT, Zamek-Gliszczynski MJ, Reinhard FBM. Clinically Relevant OATP2B1 Inhibitors in Marketed Drug Space. Mol Pharm 2020; 17:488-498. [PMID: 31834804 DOI: 10.1021/acs.molpharmaceut.9b00897] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OATP2B1 is an intestinal and hepatic drug uptake transporter. Intestinal OATP2B1 has been elucidated as the mechanism of unexpected clinical drug-drug interactions (DDIs), where drug exposure was unexpectedly decreased with unchanged half-life. Hepatic OATP2B1 may be an understudied clinical DDI mechanism. The aim of the present work was to understand the prevalence of clinically relevant intestinal and hepatic OATP2B1 inhibitors in marketed drug space. HEK293 cells stably overexpressing human OATP2B1 or vector control were generated and cultured for 72 h in a 96-well format. OATP2B1-mediated uptake of dibromofluorescein (DBF) was found to be optimal at 10 μM concentration and 30 min incubation time. A total of 294 drugs (top 300 marketed drugs, excluding biologics and restricted drugs, supplemented with ∼100 small-molecule drugs) were screened for OATP2B1 inhibition at 10 μM. Drugs demonstrating ≥50% inhibition in this screen were advanced for IC50 determination, which was extrapolated to clinical intestinal and hepatic OATP2B1 inhibition as per 2017 FDA DDI guidance. Of the 294 drugs screened, 67 elicited ≥50% inhibition of OATP2B1-mediated DBF uptake at 10 μM screening concentration. For the 67 drugs flagged in the single-concentration inhibition screen, upon evaluation of a full concentration range, IC50 values could be determined for 58 drugs. OATP2B1 IC50 values established for these 58 drugs were extrapolated as potentially clinically relevant at the intestinal level for 38 orally administered drugs (Igut/IC50 ≥ 10), and 17 were flagged as potential clinical inhibitors of hepatic OATP2B1 uptake (1 + Iin,max,u/IC50 ≥ 1.1). This analysis of 294 drugs demonstrated prevalence of clinically relevant intestinal and hepatic OATP2B1 inhibitors to be 13 and 6%, respectively. As OATP2B1-inhibitor drugs are not exceedingly rare, these results suggest that clinical OATP2B1 DDIs have been rarely observed because OATP2B1 is uncommonly the predominant determinant of drug disposition.
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Affiliation(s)
- Melissa S Unger
- Cellzome, a GlaxoSmithKline Company , 69117 Heidelberg , Germany.,Center for Mass Spectrometry and Optical Spectroscopy (CeMOS) and Institute of Medical Technology , Heidelberg University and Mannheim University of Applied Sciences , 68163 Mannheim , Germany
| | - Jennypher Mudunuru
- Drug Metabolism and Disposition , GlaxoSmithKline , Collegeville , Pennsylvania 19426 , United States
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology , University of Tübingen , 70376 Stuttgart , Germany.,Departments of Clinical Pharmacology, Pharmacy and Biochemistry , University of Tübingen , 72074 Tübingen , Germany
| | - Carsten Hopf
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS) and Institute of Medical Technology , Heidelberg University and Mannheim University of Applied Sciences , 68163 Mannheim , Germany
| | - Gerard Drewes
- Cellzome, a GlaxoSmithKline Company , 69117 Heidelberg , Germany
| | - Anne T Nies
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology , University of Tübingen , 70376 Stuttgart , Germany
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Taskar KS, Pilla Reddy V, Burt H, Posada MM, Varma M, Zheng M, Ullah M, Emami Riedmaier A, Umehara KI, Snoeys J, Nakakariya M, Chu X, Beneton M, Chen Y, Huth F, Narayanan R, Mukherjee D, Dixit V, Sugiyama Y, Neuhoff S. Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations. Clin Pharmacol Ther 2019; 107:1082-1115. [PMID: 31628859 PMCID: PMC7232864 DOI: 10.1002/cpt.1693] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 09/27/2019] [Indexed: 12/11/2022]
Abstract
Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.
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Affiliation(s)
- Kunal S Taskar
- GlaxoSmithKline, DMPK, In Vitro In Vivo Translation, GSK R&D, Ware, UK
| | - Venkatesh Pilla Reddy
- AstraZeneca, Modelling and Simulation, Early Oncology DMPK, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Howard Burt
- Simcyp-Division, Certara UK Ltd., Sheffield, UK
| | | | | | - Ming Zheng
- Bristol-Myers Squibb Company, Princeton, New Jersey, USA
| | | | | | | | - Jan Snoeys
- Janssen Research and Development, Beerse, Belgium
| | | | - Xiaoyan Chu
- Merck Sharp & Dohme Corp., Kenilworth, New Jersey, USA
| | | | - Yuan Chen
- Genentech, San Francisco, California, USA
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Nagayasu M, Ozeki K, Sakurai Y, Tsutsui H, Onoue S. Simplified Method to Determine the Efflux Ratio on P-Glycoprotein Substrates Using Three-Compartment Model Analysis for Caco-2 Cell Assay Data. Pharm Res 2019; 37:13. [PMID: 31873817 DOI: 10.1007/s11095-019-2729-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 10/30/2019] [Indexed: 12/31/2022]
Abstract
PURPOSE Multiple time-point sampling is required in transcellular transport studies to accurately calculate the appropriate efflux ratio (ER). Our study sought to develop a simplified method to determine the ER in Caco-2 cells. METHODS The equation for the ER was derived from a three-compartment model of apical to basal and basal to apical transport. Transcellular transport studies were conducted with 10 non-P-glycoprotein (P-gp) and 6 P-gp substrates in Caco-2 cells, and the ER was calculated using this equation. RESULTS The equation for the ER used the concentration ratio in the receiver compartment at the same time-point; therefore, the ER can theoretically be calculated using only a single point. The ER of all non-P-gp substrates tested was close to 1 at all sampling times. The ERs of cyclosporine A calculated from the concentration ratio at 30, 60, 90, and 120 min incubation were 2.93, 6.43, 7.12, and 9.57, respectively, and the ER at 120 min was almost identical to the theoretical value (9.62) calculated using three-compartment model analysis. The other 5 P-gp substrates showed a similar tendency. Single-point sampling can be used to accurately calculate ER at 120 min. CONCLUSIONS Single-point sampling is a promising approach for calculating appropriate ERs in the drug discovery stage.
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Affiliation(s)
- Miho Nagayasu
- Research division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan
- Laboratory of Biopharmacy, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka, 422-8256, Japan
| | - Kazuhisa Ozeki
- Research division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan.
| | - Yuuji Sakurai
- Research division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan
| | - Haruka Tsutsui
- Research division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan
| | - Satomi Onoue
- Laboratory of Biopharmacy, School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka, 422-8256, Japan
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Wright SH. Molecular and cellular physiology of organic cation transporter 2. Am J Physiol Renal Physiol 2019; 317:F1669-F1679. [PMID: 31682169 DOI: 10.1152/ajprenal.00422.2019] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Organic cation transporters play a critical role in mediating the distribution of cationic pharmaceuticals. Indeed, organic cation transporter (OCT)2 is the initial step in the renal secretion of organic cations and consequently plays a defining role in establishing the pharmacokinetics of many cationic drugs. Although a hallmark of OCTs is their broad selectivity, this characteristic also makes them targets for unwanted, adverse drug-drug interactions (DDIs), making them a focus for efforts to develop models of ligand interaction that could predict and preempt these adverse interactions. This review discusses the molecular characteristics of these transporters as well as the evidence that established the OCTs as key players in the distribution of organic cations. However, the primary focus is the present understanding of the complexity of ligand interaction with OCTs, particularly OCT2, including evidence for the presence of multiple ligand-binding sites and the influence of substrate structure on the affinity of the transporter for inhibitory ligands. This leads to a discussion of the complexities associated with the development of protocols for assessing the inhibitory potential of new molecular entities to perpetrate unwanted DDIs, the criteria that should be considered in the interpretation of the results of such protocols, and the challenges associated with development of models capable of predicting unwanted DDIs.
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Affiliation(s)
- Stephen H Wright
- Department of Physiology, University of Arizona, Tucson, Arizona
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47
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Yamazaki S, Costales C, Lazzaro S, Eatemadpour S, Kimoto E, Varma MV. Physiologically-Based Pharmacokinetic Modeling Approach to Predict Rifampin-Mediated Intestinal P-Glycoprotein Induction. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:634-642. [PMID: 31420942 PMCID: PMC6765699 DOI: 10.1002/psp4.12458] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/24/2019] [Indexed: 12/25/2022]
Abstract
Physiologically‐based pharmacokinetic (PBPK) modeling is a powerful tool to quantitatively describe drug disposition profiles in vivo, thereby providing an alternative to predict drug–drug interactions (DDIs) that have not been tested clinically. This study aimed to predict effects of rifampin‐mediated intestinal P‐glycoprotein (Pgp) induction on pharmacokinetics of Pgp substrates via PBPK modeling. First, we selected four Pgp substrates (digoxin, talinolol, quinidine, and dabigatran etexilate) to derive in vitro to in vivo scaling factors for intestinal Pgp kinetics. Assuming unbound Michaelis‐Menten constant (Km) to be intrinsic, we focused on the scaling factors for maximal efflux rate (Jmax) to adequately recover clinically observed results. Next, we predicted rifampin‐mediated fold increases in intestinal Pgp abundances to reasonably recover clinically observed DDI results. The modeling results suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin. Hence, the obtained fold increases can potentially be applicable to DDI prediction with other Pgp substrates.
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Affiliation(s)
- Shinji Yamazaki
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, San Diego, California, USA
| | - Chester Costales
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Groton, Connecticut, USA
| | - Sarah Lazzaro
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Groton, Connecticut, USA
| | - Soraya Eatemadpour
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Groton, Connecticut, USA
| | - Emi Kimoto
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Groton, Connecticut, USA
| | - Manthena V Varma
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Groton, Connecticut, USA
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McFeely SJ, Ritchie TK, Ragueneau-Majlessi I. Variability in In Vitro OATP1B1/1B3 Inhibition Data: Impact of Incubation Conditions on Variability and Subsequent Drug Interaction Predictions. Clin Transl Sci 2019; 13:47-52. [PMID: 31468718 PMCID: PMC6951852 DOI: 10.1111/cts.12691] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 08/08/2019] [Indexed: 12/24/2022] Open
Abstract
As the research into the organic anion transporting polypeptides (OATPs) continues to grow, it is important to ensure that the data generated are accurate and reproducible. In the in vitro evaluation of OATP1B1/1B3 inhibition, there are many variables that can contribute to variability in the resulting inhibition constants, which can then, in turn, contribute to variable results when clinical predictions (R-values) are performed. Currently, the only experimental condition recommended by the US Food and Drug Administration (FDA) is the inclusion of a pre-incubation period.1 To identify other potential sources of variability, a descriptive analysis of available in vitro inhibition data was completed. For each of the 21 substrate/inhibitor pairs evaluated, cell type and pre-incubation were found to have the greatest effect on half-maximal inhibitory concentration (IC50 ) variability. Indeed, when only HEK293 cells and co-incubation conditions were included, the observed variability for the entire data set (highest IC50 /lowest) was reduced from 12.4 to 5.2. The choice of probe substrate used in the study also had a significant effect on inhibitor constant variability. Interestingly, despite the broad range of inhibitory constants identified, these two factors showed little effect on the calculated R-values relative to the FDA evaluation cutoff of 1.1 triggering a clinical evaluation for the inhibitors evaluated. However, because of the small data set available, further research is needed to confirm these preliminary results and define best practice for the study of OATPs.
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Affiliation(s)
- Savannah J McFeely
- Department of Pharmaceutics, UW Drug Interaction Solutions, University of Washington, Seattle, Washington, USA
| | - Tasha K Ritchie
- Department of Pharmaceutics, UW Drug Interaction Solutions, University of Washington, Seattle, Washington, USA
| | - Isabelle Ragueneau-Majlessi
- Department of Pharmaceutics, UW Drug Interaction Solutions, University of Washington, Seattle, Washington, USA
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49
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Guimarães DSM, de Sousa Luz LS, do Nascimento SB, Silva LR, de Miranda Martins NR, de Almeida HG, de Souza Reis V, Maluf SEC, Budu A, Marinho JA, Abramo C, Carmona AK, da Silva MG, da Silva GR, Kemmer VM, Butera AP, Ribeiro-Viana RM, Gazarini ML, Júnior CSN, Guimarães L, Dos Santos FV, de Castro WV, Viana GHR, de Brito CFA, de Pilla Varotti F. Improvement of antimalarial activity of a 3-alkylpiridine alkaloid analog by replacing the pyridine ring to a thiazole-containing heterocycle: Mode of action, mutagenicity profile, and Caco-2 cell-based permeability. Eur J Pharm Sci 2019; 138:105015. [PMID: 31344442 DOI: 10.1016/j.ejps.2019.105015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 07/11/2019] [Accepted: 07/20/2019] [Indexed: 12/11/2022]
Abstract
The development of new antimalarial drugs is urgent to overcome the spread of resistance to the current treatment. Herein we synthesized the compound 3, a hit-to‑lead optimization of a thiazole based on the most promising 3-alkylpyridine marine alkaloid analog. Compound 3 was tested against Plasmodium falciparum and has shown to be more potent than its precursor (IC50 values of 1.55 and 14.7 μM, respectively), with higher selectivity index (74.7) for noncancerous human cell line. This compound was not mutagenic and showed genotoxicity only at concentrations four-fold higher than its IC50. Compound 3 was tested in vivo against Plasmodium berghei NK65 strain and inhibited the development of parasite at 50 mg/kg. In silico and UV-vis approaches determined that compound 3 acts impairing hemozoin crystallization and confocal microscopy experiments corroborate these findings as the compound was capable of diminishing food vacuole acidity. The assay of uptake using human intestinal Caco-2 cell line showed that compound 3 is absorbed similarly to chloroquine, a standard antimalarial agent. Therefore, we present here compound 3 as a potent new lead antimalarial compound.
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Affiliation(s)
| | - Letícia Silveira de Sousa Luz
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil
| | - Sara Batista do Nascimento
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil
| | - Lorena Rabelo Silva
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil
| | - Natália Rezende de Miranda Martins
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil
| | - Heloísa Gonçalves de Almeida
- Universidade Federal de São João del-Rei, Campus Dom Bosco, 74 Dom Helvécio Square, São João del Rei, MG 36301-160, Brazil
| | - Vitória de Souza Reis
- Universidade Federal de São João del-Rei, Campus Dom Bosco, 74 Dom Helvécio Square, São João del Rei, MG 36301-160, Brazil
| | - Sarah El Chamy Maluf
- Universidade Federal de São Paulo, Departamento de Biofísica, 669 Pedro de Toledo Street, São Paulo, SP 04039-032, Brazil
| | - Alexandre Budu
- Universidade Federal de São Paulo, Departamento de Biofísica, 669 Pedro de Toledo Street, São Paulo, SP 04039-032, Brazil.
| | - Juliane Aparecida Marinho
- Núcleo de Pesquisas em Parasitologia, Universidade Federal de Juiz de Fora, José Lourenço Kelmer Street, Juiz de Fora, MG 36036-900, Brazil
| | - Clarice Abramo
- Núcleo de Pesquisas em Parasitologia, Universidade Federal de Juiz de Fora, José Lourenço Kelmer Street, Juiz de Fora, MG 36036-900, Brazil.
| | - Adriana Karaoglanovic Carmona
- Universidade Federal de São Paulo, Departamento de Biofísica, 669 Pedro de Toledo Street, São Paulo, SP 04039-032, Brazil.
| | - Marina Goulart da Silva
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil.
| | - Gisele Rodrigues da Silva
- Universidade Federal de Ouro Preto, Departamento de Farmácia, Campus Morro do Cruzeiro, w/n, Bauxita, Ouro Preto, MG 35400-000, Brazil.
| | - Victor Matheus Kemmer
- Universidade Estadual de Londrina, Departamento de Química, Londrina, PR 86057-970, Brazil
| | - Anna Paola Butera
- Universidade Estadual de Londrina, Departamento de Química, Londrina, PR 86057-970, Brazil.
| | - Renato Márcio Ribeiro-Viana
- Universidade Tecnológica Federal do Paraná, Departamento Acadêmico de Química (DAQUI), Londrina, PR, 6036-370, Brazil.
| | - Marcos Leoni Gazarini
- Universidade Federal de São Paulo, Departamento de Biociências, 136 Silva Jardim Street, Santos, SP 11015-020, Brazil.
| | | | - Luciana Guimarães
- Universidade Federal de São João del-Rei, Campus Dom Bosco, 74 Dom Helvécio Square, São João del Rei, MG 36301-160, Brazil
| | - Fabio Vieira Dos Santos
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil.
| | - Whocely Victor de Castro
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil.
| | - Gustavo Henrique Ribeiro Viana
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil.
| | | | - Fernando de Pilla Varotti
- Núcleo de Pesquisa em Química Biológica, Universidade Federal de São João Del-Rei - Campus Centro Oeste, 400 Sebastião Gonçalves Coelho Street, Divinópolis, MG 35501-296, Brazil.
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Kashif SA, Park JK. Enzymatically Hydrolyzed Water-Soluble Chitosan as a Potent Anti-Microbial Agent. Macromol Res 2019. [DOI: 10.1007/s13233-019-7095-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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