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Pattanaik S, Monchaud C. Pharmacokinetic Boosting of Calcineurin Inhibitors in Transplantation: Pros, Cons, and Perspectives. Ther Drug Monit 2025; 47:118-140. [PMID: 39774591 DOI: 10.1097/ftd.0000000000001288] [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: 09/01/2024] [Accepted: 09/27/2024] [Indexed: 01/11/2025]
Abstract
ABSTRACT The concept of pharmacokinetic (PK) boosting of calcineurin inhibitors (CNI) emerged after the FDA approval of cyclosporine-A. Several studies followed, and the proof of concept was well established by the late 1990s. This also continued for the next blockbuster immunosuppressant, tacrolimus. The driver for such research was an endeavor to save costs, as both drugs were expensive due to patent protection. Two CYP inhibitors, ketoconazole and diltiazem, have been extensively studied in this context and continue to be prescribed off-label along with the CNI. It has been observed that using ketoconazole reduces the dose requirement of tacrolimus by about 50% and 30% with diltiazem, which is in conformity with their pharmacological actions. Off-label co-prescription of these drugs with CNI is often encountered in low and middle-income countries. The foremost reason cited is economic. This article collates the evidence from the clinical studies that evaluate the PK-boosting effects of CNI and also reviews the gaps in the current evidence base. The current knowledge prevents the transplant community from making meaningful inferences about the risks and benefits of such strategies. Although the PK-boosting strategy can lead to serious adverse events, emerging evidence suggests that it may be advantageous for individuals with high CNI dose requirements. Hence, PK boosting may be an unmet need in the therapeutics of CNI. Nevertheless, there are several unanswered questions surrounding such use, and therefore, this merits testing in well-designed clinical studies. Moreover, drugs with better safer profiles and a history of successful PK boosting may be considered for evaluation with CNI.
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Affiliation(s)
- Smita Pattanaik
- Clinical Pharmacology Unit, Department of Pharmacology, Post Graduate Institute of Medical Education and Research, Chandigarh, India
| | - Caroline Monchaud
- Service de Pharmacologie, Toxicologie et Pharmacovigilance, CHU Limoges, Limoges, France
- INSERM UMR-1248 Pharmacologie et Transplantation, Université Limoges, Limoges, France; and
- FHU SUPORT, Limoges, France
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2
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Reddy MB, Cabalu TD, de Zwart L, Ramsden D, Dowty ME, Taskar KS, Badée J, Bolleddula J, Boulu L, Fu Q, Kotsuma M, Leblanc AF, Lewis G, Liang G, Parrott N, Pilla Reddy V, Prakash C, Shah K, Umehara K, Mukherjee D, Rehmel J, Hariparsad N. Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective. Clin Pharmacol Ther 2025; 117:403-420. [PMID: 39422118 PMCID: PMC11739743 DOI: 10.1002/cpt.3477] [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: 06/25/2024] [Accepted: 10/01/2024] [Indexed: 10/19/2024]
Abstract
Physiologically-based pharmacokinetic (PBPK) modeling offers a viable approach to predict induction drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In the current work, the ability to predict the effect of rifampin, a well-characterized strong CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models (often developed using a workflow with optimization following a strong inhibitor DDI study to gain confidence in fraction metabolized by CYP3A4, fm,CYP3A4, and fraction available after intestinal metabolism, Fg), was assessed. Substrates with a range of fm,CYP3A4 (0.086-1.0), Fg (0.11-1.0) and hepatic availability (0.09-0.96) were included. Predictions were most often accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for three challenging DDI predictions (i.e., for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, for example, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact (e.g., induction of other enzymes or P-gp) should be considered for inclusion in the model. PBPK modeling was shown to be an effective tool to predict induction DDIs with rifampin for CYP3A substrates with limited mechanistic complications, increasing confidence in the rifampin model. While this analysis focused on rifampin, the learnings may apply to other inducers.
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Affiliation(s)
| | - Tamara D. Cabalu
- DMPK, Pharmacokinetics, Dynamics, Metabolism, and BioanalyticsMerck & Co., Inc.RahwayNew JerseyUSA
| | - Loeckie de Zwart
- DMPK, Janssen Pharmaceutica NVA Johnson & Johnson CompanyBeerseBelgium
| | - Diane Ramsden
- DMPK, Research and Early Development, Oncology R&DAstraZenecaBostonMassachusettsUSA
| | - Martin E. Dowty
- Pharmacokinetics Dynamics and MetabolismPfizer IncCambridgeMassachusettsUSA
| | - Kunal S. Taskar
- DMPK, Pre‐Clinical Sciences, Research TechnologiesGSKStevenageUK
| | - Justine Badée
- PK Sciences, Biomedical ResearchNovartisBaselSwitzerland
| | - Jayaprakasam Bolleddula
- Quantitative PharmacologyEMD Serono Research & Development Institute, Inc.BillericaMassachusettsUSA
| | - Laurent Boulu
- Modeling and Simulation, Translational Medicine and Early DevelopmentSanofiMontpellierFrance
| | - Qiang Fu
- Modeling and SimulationVertex PharmaceuticalsBostonMassachusettsUSA
| | - Masakatsu Kotsuma
- Quantitative Clinical PharmacologyDaiichi Sankyo Co., Ltd.TokyoJapan
| | - Alix F. Leblanc
- Quantitative, Translational & ADME Sciences, Development ScienceAbbVieNorth ChicagoIllinoisUSA
| | - Gareth Lewis
- DMPK, Pre‐Clinical Sciences, Research TechnologiesGSKStevenageUK
| | | | - Neil Parrott
- Pharmaceutical Sciences, Roche Pharma Research & Early DevelopmentRoche Innovation Center BaselBaselSwitzerland
| | - Venkatesh Pilla Reddy
- Global PKPD/PharmacometricsEli Lilly and CompanyBracknell, UK and Indianapolis, IndianaUSA
| | - Chandra Prakash
- DMPK and Clinical PharmacologyAgiosCambridgeMassachusettsUSA
| | - Kushal Shah
- Quantitative Clinical PharmacologyTakeda Pharmaceuticals International Inc.CambridgeMassachusettsUSA
| | - Kenichi Umehara
- Roche Pharmaceutical Research and Early Development, Roche Innovation CenterF. Hoffmann‐La Roche Ltd.BaselSwitzerland
| | - Dwaipayan Mukherjee
- Quantitative Clinical PharmacologyDaiichi‐Sankyo Inc.Basking RidgeNew JerseyUSA
| | - Jessica Rehmel
- Global PKPD/PharmacometricsEli Lilly and CompanyBracknell, UK and Indianapolis, IndianaUSA
| | - Niresh Hariparsad
- DMPK, Research and Early Development, Oncology R&DAstraZenecaBostonMassachusettsUSA
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Ohri S, Parekh P, Nichols L, Rajan SAP, Cirit M. Utilization of a human Liver Tissue Chip for drug-metabolizing enzyme induction studies of perpetrator and victim drugs. Drug Metab Dispos 2025; 53:100004. [PMID: 39884808 DOI: 10.1124/dmd.124.001497] [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: 07/17/2024] [Revised: 09/30/2024] [Accepted: 09/30/2024] [Indexed: 10/09/2024] Open
Abstract
Polypharmacy-related drug-drug interactions (DDIs) are a significant and growing healthcare concern. An increasing number of therapeutic drugs on the market underscores the necessity to accurately assess new drug combinations during preclinical evaluation for DDIs. In vitro primary human hepatocytes (PHH) models are only applicable for short-term induction studies because of their rapid loss of metabolic function. Though coculturing nonhuman stromal cells with PHH has been shown to stabilize metabolic activity long-term, there are concerns about human specificity for accurate clinical assessment. In this study, we demonstrated a PHH-only liver microphysiological system in the Liver Tissue Chip is capable of maintaining long-term functional and metabolic activity of PHH from 3 individual donors and thus a suitable platform for long-term DDI induction studies. The responses to rifampicin induction of 3 PHH donors were assessed using cytochrome P450 activity and mRNA changes. Additionally, victim pharmacokinetic studies were conducted with midazolam (high clearance) and alprazolam (low clearance) following perpetrator drug treatment, rifampicin-mediated induction, which resulted in a 2-fold and a 2.6-fold increase in midazolam and alprazolam intrinsic clearance values, respectively, compared with the untreated liver microphysiological system. We also investigated the induction effects of different dosing regimens of the perpetrator drug (rifampicin) on cytochrome P450 activity levels, showing minimal variation in the intrinsic clearance of the victim drug (midazolam). This study illustrates the utility of the Liver Tissue Chip for in vitro liver-specific DDI induction studies, providing a translational experimental system to predict clinical clearance values of both perpetrator and victim drugs. SIGNIFICANCE STATEMENT: This study demonstrated the utility of the Liver Tissue Chip with a primary human hepatocyte-only liver microphysiological system for drug-drug interaction induction studies. This unique in vitro system with continuous recirculation maintains long-term functionality and metabolic activity for up to 4 weeks, enabling the study of perpetrator and victim drug pharmacokinetics, quantification of drug-induced cytochrome P450 mRNA and activity levels, investigation of patient variability, and ultimately clinical predictions.
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Affiliation(s)
| | | | | | | | - Murat Cirit
- Javelin Biotech, Inc, Woburn, Massachusetts.
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Nørgaard RA, Bhatt DK, Järvinen E, Stage TB, Gabel-Jensen C, Galetin A, Säll C. Evaluating Drug-Drug Interaction Risk Associated with Peptide Analogs Using advanced In Vitro Systems. Drug Metab Dispos 2024; 52:1170-1180. [PMID: 38050097 DOI: 10.1124/dmd.123.001441] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/10/2023] [Accepted: 10/25/2023] [Indexed: 12/06/2023] Open
Abstract
Drug-drug interaction (DDI) assessment of therapeutic peptides is an evolving area. The industry generally follows DDI guidelines for small molecules, but the translation of data generated with commonly used in vitro systems to in vivo is sparse. In the current study, we investigated the ability of advanced human hepatocyte in vitro systems, namely HepatoPac, spheroids, and Liver-on-a-chip, to assess potential changes in regulation of CYP1A2, CYP2B6, CYP3A4, SLCO1B1, and ABCC2 in the presence of selected therapeutic peptides, proteins, and small molecules. The peptide NN1177, a glucagon and GLP-1 receptor co-agonist, did not suppress mRNA expression or activity of CYP1A2, CYP2B6, and CYP3A4 in HepatoPac, spheroids, or Liver-on-a-chip; these findings were in contrast to the data obtained in sandwich cultured hepatocytes. No effect of NN1177 on SLCO1B1 and ABCC2 mRNA was observed in any of the complex systems. The induction magnitude differed across the systems (e.g., rifampicin induction of CYP3A4 mRNA ranged from 2.8-fold in spheroids to 81.2-fold in Liver-on-a-chip). Small molecules, obeticholic acid and abemaciclib, showed varying responses in HepatoPac, spheroids, and Liver-on-a-chip, indicating a need for EC50 determinations to fully assess translatability data. HepatoPac, the most extensively investigated in this study (3 donors), showed high potential to investigate DDIs associated with CYP regulation by therapeutic peptides. Spheroids and Liver-on-a-chip were only assessed in one hepatocyte donor and further evaluations are required to confirm their potential. This study establishes an excellent foundation toward the establishment of more clinically-relevant in vitro tools for evaluation of potential DDIs with therapeutic peptides. SIGNIFICANT STATEMENT: At present, there are no guidelines for drug-drug interaction (DDI) assessment of therapeutic peptides. Existing in vitro methods recommended for assessing small molecule DDIs do not appear to translate well for peptide drugs, complicating drug development for these moieties. Here, we establish evidence that complex cellular systems have potential to be used as more clinically-relevant tools for the in vitro DDI evaluation of therapeutic peptides.
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Affiliation(s)
- Rune Aa Nørgaard
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Deepak K Bhatt
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Erkka Järvinen
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Tore B Stage
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Charlotte Gabel-Jensen
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Aleksandra Galetin
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
| | - Carolina Säll
- Development ADME, Novo Nordisk A/S, Måløv, Denmark (R.A.N., D.K.B., C.G.-J., C.S.); Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark (E.J., T.B.S.); Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark (T.B.S.); and Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom (A.G.)
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5
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Zerdoug A, Le Vée M, Le Mentec H, Carteret J, Jouan E, Jamin A, Lopez B, Uehara S, Higuchi Y, Yoneda N, Chesné C, Suemizu H, Fardel O. Induction of drug metabolizing enzyme and drug transporter expression by antifungal triazole pesticides in human HepaSH hepatocytes. CHEMOSPHERE 2024; 366:143474. [PMID: 39369742 DOI: 10.1016/j.chemosphere.2024.143474] [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: 06/23/2024] [Revised: 08/27/2024] [Accepted: 10/03/2024] [Indexed: 10/08/2024]
Abstract
Triazole pesticides are widely used fungicides, to which humans are rather highly exposed. They are known to activate drug-sensing receptors regulating expression of hepatic drug metabolizing enzymes and drug transporters, thus suggesting that the hepatic drug detoxification system is modified by these agrochemicals. To investigate this hypothesis, the effects of 9 triazole fungicides towards expression of drug metabolizing enzymes and transporters were characterized in cultured human HepaSH cells, that are human hepatocytes deriving from chimeric humanized liver TK-NOG mice. Most of triazoles used at 10 μM were found to act as inducers of cytochrome P-450 (CYP) 1A1, CYP1A2, CYP2B6, CYP3A4 and UDP-glucuronosyltransferase 1A1 mRNA levels and of CYP3A4 protein; some triazoles also enhanced mRNA expression of the canalicular transporters P-glycoprotein/MDR1, multidrug resistance-associated protein 2 and breast cancer resistance protein. Triazoles however concomitantly inhibited CYP2B6 and CYP3A4 activities and thus appeared as dual regulators of these CYPs, being both inducers of their expression and inhibitors of their activity. The inducing effect however predominated, at least for bromuconazole, propiconazole and tebuconazole. Bromuconazole was moreover predicted to enhance CYP2B6 and CYP3A4 expression in humans exposed to this fungicide in a chronic, acute or occupational context. These data demonstrate that key-actors of the human hepatic detoxification system are impacted by triazole pesticides, which may have to be considered for the risk assessment of these agrochemicals. They additionally highlight that the use of human HepaSH cells as surrogates to primary human hepatocytes represents an attractive and promising way for studying hepatic effects of environmental chemicals.
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Affiliation(s)
- Anna Zerdoug
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France; Biopredic International, F-35760, Saint Grégoire, France
| | - Marc Le Vée
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France
| | - Hélène Le Mentec
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France
| | - Jennifer Carteret
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France
| | - Elodie Jouan
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France
| | - Agnès Jamin
- Biopredic International, F-35760, Saint Grégoire, France
| | - Béatrice Lopez
- Biopredic International, F-35760, Saint Grégoire, France
| | - Shotaro Uehara
- Central Institute for Experimental Medicine and Life Science, 210-0821, Kawasaki, Japan
| | - Yuichiro Higuchi
- Central Institute for Experimental Medicine and Life Science, 210-0821, Kawasaki, Japan
| | - Nao Yoneda
- Central Institute for Experimental Medicine and Life Science, 210-0821, Kawasaki, Japan
| | | | - Hiroshi Suemizu
- Central Institute for Experimental Medicine and Life Science, 210-0821, Kawasaki, Japan
| | - Olivier Fardel
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000, Rennes, France.
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6
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Chen J, Li J, Wu J, Song Y, Li L, Zhang J, Dong R. An open-label study to explore the optimal design of CYP3A drug-drug interaction clinical trials in healthy Chinese people. Pharmacol Res Perspect 2024; 12:e1252. [PMID: 39073244 PMCID: PMC11284260 DOI: 10.1002/prp2.1252] [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: 07/20/2023] [Revised: 05/29/2024] [Accepted: 07/04/2024] [Indexed: 07/30/2024] Open
Abstract
A drug-drug interaction (DDI) trial of cytochrome P450 3A (CYP3A) is a necessary part of early-phase trials of drugs mainly metabolized by this enzyme, but CYP3A DDI clinical trials do not have a standard design, especially for Chinese people. We aimed to offer specific recommendations for CYP3A DDI clinical trial design. This was an open, three-cycle, self-controlled study. Healthy subjects were given different administration strategies of CYP3A4 perpetrators. In each cycle, blood samples were collected before and within 24 h after the administration of midazolam, the CYP3A indicator substrate. The plasma concentrations of midazolam and 1-hydroxymidazolam was obtained using liquid chromatography tandem mass spectrometry assay. For CYP3A inhibition, itraconazole exposure with a loading dose could increase the exposure of midazolam by 3.21-fold based on maximum plasma concentration (Cmax), 8.37-fold based on area under the curve Pharmacology Research & Perspectives for review only from zero to the time point (AUC0-t), and 11.22-fold based on area under the curve from zero to infinity (AUC0-∞). The data were similar for itraconazole pretreatment without a loading dose. For CYP3A induction, the exposure of rifampin for 7 days decreased the plasma concentration of midazolam ~0.27-fold based on Cmax, ~0.18-fold based on AUC0-t, and ~0.18-fold based on AUC0-∞. Midazolam exposure did not significantly change when the pretreatment of rifampin increased to 14 days. This study showed that itraconazole pretreatment for 3 days without a loading dose was enough for CYP3A inhibition, and pretreatment with rifampin for 7 days could induce near-maximal CYP3A levels.
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Affiliation(s)
- Jingcheng Chen
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Jiangshuo Li
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Jingxuan Wu
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Yuqin Song
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Lijun Li
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Jianxiong Zhang
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
| | - Ruihua Dong
- Research Ward, Beijing Friendship HospitalCapital Medical UniversityBeijingChina
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Yadav J, Maldonato BJ, Roesner JM, Vergara AG, Paragas EM, Aliwarga T, Humphreys S. Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic. Drug Metab Rev 2024:1-33. [PMID: 39057923 DOI: 10.1080/03602532.2024.2381021] [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: 02/23/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024]
Abstract
Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.
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Affiliation(s)
- Jaydeep Yadav
- Department of Pharmacokinetics, Dynamics, Metabolism & Bioanalytics (PDMB), Merck & Co., Inc., Boston, MA, USA
| | - Benjamin J Maldonato
- Department of Nonclinical Development and Clinical Pharmacology, Revolution Medicines, Inc., Redwood City, CA, USA
| | - Joseph M Roesner
- Department of Pharmacokinetics, Dynamics, Metabolism & Bioanalytics (PDMB), Merck & Co., Inc., Boston, MA, USA
| | - Ana G Vergara
- Department of Pharmacokinetics, Dynamics, Metabolism & Bioanalytics (PDMB), Merck & Co., Inc., Rahway, NJ, USA
| | - Erickson M Paragas
- Pharmacokinetics and Drug Metabolism Department, Amgen Research, South San Francisco, CA, USA
| | - Theresa Aliwarga
- Pharmacokinetics and Drug Metabolism Department, Amgen Research, South San Francisco, CA, USA
| | - Sara Humphreys
- Pharmacokinetics and Drug Metabolism Department, Amgen Research, South San Francisco, CA, USA
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8
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Yu J, Tang F, Ma F, Wong S, Wang J, Ly J, Chen L, Mao J. Human Pharmacokinetic and CYP3A Drug-Drug Interaction Prediction of GDC-2394 Using Physiologically Based Pharmacokinetic Modeling and Biomarker Assessment. Drug Metab Dispos 2024; 52:765-774. [PMID: 38811156 DOI: 10.1124/dmd.123.001633] [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: 12/15/2023] [Revised: 05/20/2024] [Accepted: 05/22/2024] [Indexed: 05/31/2024] Open
Abstract
Physiologically based pharmacokinetic (PBPK) modeling was used to predict the human pharmacokinetics and drug-drug interaction (DDI) of GDC-2394. PBPK models were developed using in vitro and in vivo data to reflect the oral and intravenous PK profiles of mouse, rat, dog, and monkey. The learnings from preclinical PBPK models were applied to a human PBPK model for prospective human PK predictions. The prospective human PK predictions were within 3-fold of the clinical data from the first-in-human study, which was used to optimize and validate the PBPK model and subsequently used for DDI prediction. Based on the majority of PBPK modeling scenarios using the in vitro CYP3A induction data (mRNA and activity), GDC-2394 was predicted to have no-to-weak induction potential at 900 mg twice daily (BID). Calibration of the induction mRNA and activity data allowed for the convergence of DDI predictions to a narrower range. The plasma concentrations of the 4β-hydroxycholesterol (4β-HC) were measured in the multiple ascending dose study to assess the hepatic CYP3A induction risk. There was no change in plasma 4β-HC concentrations after 7 days of GDC-2394 at 900 mg BID. A dedicated DDI study found that GDC-2394 has no induction effect on midazolam in humans, which was reflected by the totality of predicted DDI scenarios. This work demonstrates the prospective utilization of PBPK for human PK and DDI prediction in early drug development of GDC-2394. PBPK modeling accompanied with CYP3A biomarkers can serve as a strategy to support clinical pharmacology development plans. SIGNIFICANCE STATEMENT: This work presents the application of physiologically based pharmacokinetic modeling for prospective human pharmacokinetic (PK) and drug-drug interaction (DDI) prediction in early drug development. The strategy taken in this report represents a framework to incorporate various approaches including calibration of in vitro induction data and consideration of CYP3A biomarkers to inform on the overall CYP3A-related DDI risk of GDC-2394.
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Affiliation(s)
- Jesse Yu
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Fei Tang
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Fang Ma
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Susan Wong
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Jing Wang
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Justin Ly
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Liuxi Chen
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
| | - Jialin Mao
- Departments of Drug Metabolism and Pharmacokinetics (J.Y., S.W., J.W., J.L., L.C., J.M.) and Drug Metabolism and Pharmacokinetics (F.T., F.M.), Genentech, Inc., South San Francisco, California
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9
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de Vries M, Bonsmann S, Pausch J, Sumner M, Birkmann A, Zimmermann H, Kropeit D. Evaluation of the Clinical Drug-Drug Interaction Potential of Pritelivir on Transporters and CYP450 Enzymes Using a Cocktail Approach. Clin Pharmacol Drug Dev 2024; 13:755-769. [PMID: 38752475 DOI: 10.1002/cpdd.1408] [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: 11/16/2023] [Accepted: 04/08/2024] [Indexed: 07/05/2024]
Abstract
Pritelivir is a novel viral helicase-primase inhibitor active against herpes simplex virus. In vitro drug-drug interaction studies indicated that pritelivir has the potential for clinically relevant interactions on the cytochrome P450 (CYP) enzymes 2C8, 2C9, 3A4, and 2B6, and intestinal uptake transporter organic anion transporting polypeptide (OATP) 2B1 and efflux transporter breast cancer resistance protein (BCRP). This was evaluated in 2 clinical trials. In 1 trial the substrates flurbiprofen (CYP2C9), bupropion (CYP2B6), and midazolam (CYP3A4) were administered simultaneously as part of the Geneva cocktail, while the substrate celiprolol (OAPT2B1) was administered separately. In another trial, the substrates repaglinide (CYP2C8) and rosuvastatin (BCRP) were administered separately. Exposure parameters of the substrates and their metabolites (flurbiprofen and bupropion only) were compared after administration with or without pritelivir under therapeutic concentrations. The results of these trials indicated that pritelivir has no clinically relevant effect on the exposure of substrates for the intestinal uptake transporter OATP2B1 and the CYP enzymes 3A4, 2B6, 2C9, and 2C8, and has a weak inhibitory effect on the intestinal efflux transporter BCRP. In summary, the results suggest that pritelivir has a low drug-drug interaction potential.
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Affiliation(s)
| | | | - Jörg Pausch
- AiCuris Anti-infective Cures AG, Wuppertal, Germany
- Present affiliation: BioNTech SE, Mainz, Germany
| | | | | | | | - Dirk Kropeit
- AiCuris Anti-infective Cures AG, Wuppertal, Germany
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10
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Zhao D, Huang P, Yu L, He Y. Pharmacokinetics-Pharmacodynamics Modeling for Evaluating Drug-Drug Interactions in Polypharmacy: Development and Challenges. Clin Pharmacokinet 2024; 63:919-944. [PMID: 38888813 DOI: 10.1007/s40262-024-01391-2] [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] [Accepted: 06/03/2024] [Indexed: 06/20/2024]
Abstract
Polypharmacy is commonly employed in clinical settings. The potential risks of drug-drug interactions (DDIs) can compromise efficacy and pose serious health hazards. Integrating pharmacokinetics (PK) and pharmacodynamics (PD) models into DDIs research provides a reliable method for evaluating and optimizing drug regimens. With advancements in our comprehension of both individual drug mechanisms and DDIs, conventional models have begun to evolve towards more detailed and precise directions, especially in terms of the simulation and analysis of physiological mechanisms. Selecting appropriate models is crucial for an accurate assessment of DDIs. This review details the theoretical frameworks and quantitative benchmarks of PK and PD modeling in DDI evaluation, highlighting the establishment of PK/PD modeling against a backdrop of complex DDIs and physiological conditions, and further showcases the potential of quantitative systems pharmacology (QSP) in this field. Furthermore, it explores the current advancements and challenges in DDI evaluation based on models, emphasizing the role of emerging in vitro detection systems, high-throughput screening technologies, and advanced computational resources in improving prediction accuracy.
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Affiliation(s)
- Di Zhao
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
- Henan University of Chinese Medicine, Zhengzhou, China
| | - Ping Huang
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China
| | - Li Yu
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yu He
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310000, China.
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11
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Kerhoas M, Carteret J, Huchet L, Jouan E, Huc L, Vée ML, Fardel O. Induction of human hepatic cytochrome P-450 3A4 expression by antifungal succinate dehydrogenase inhibitors. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 276:116261. [PMID: 38574644 DOI: 10.1016/j.ecoenv.2024.116261] [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: 12/12/2023] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/06/2024]
Abstract
Succinate dehydrogenase inhibitors (SDHIs) are widely-used fungicides, to which humans are exposed and for which putative health risks are of concern. In order to identify human molecular targets for these agrochemicals, the interactions of 15 SDHIs with expression and activity of human cytochrome P-450 3A4 (CYP3A4), a major hepatic drug metabolizing enzyme, were investigated in vitro. 12/15 SDHIs, i.e., bixafen, boscalid, fluopyram, flutolanil, fluxapyroxad, furametpyr, isofetamid, isopyrazam, penflufen, penthiopyrad, pydiflumetofen and sedaxane, were found to enhance CYP3A4 mRNA expression in human hepatic HepaRG cells and primary human hepatocytes exposed for 48 h to 10 µM SDHIs, whereas 3/15 SDHIs, i.e., benzovindiflupyr, carboxin and thifluzamide, were without effect. The inducing effects were concentrations-dependent for boscalid (EC50=22.5 µM), fluopyram (EC50=4.8 µM) and flutolanil (EC50=53.6 µM). They were fully prevented by SPA70, an antagonist of the Pregnane X Receptor, thus underlining the implication of this xenobiotic-sensing receptor. Increase in CYP3A4 mRNA in response to SDHIs paralleled enhanced CYP3A4 protein expression for most of SDHIs. With respect to CYP3A4 activity, it was directly inhibited by some SDHIs, including bixafen, fluopyram, fluxapyroxad, isofetamid, isopyrazam, penthiopyrad and sedaxane, which therefore appears as dual regulators of CYP3A4, being both inducer of its expression and inhibitor of its activity. The inducing effect nevertheless predominates for these SDHIs, except for isopyrazam and sedaxane, whereas boscalid and flutolanil were pure inducers of CYP3A4 expression and activity. Most of SDHIs appear therefore as in vitro inducers of CYP3A4 expression in cultured hepatic cells, when, however, used at concentrations rather higher than those expected in humans in response to environmental or dietary exposure to these agrochemicals.
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Affiliation(s)
- Marie Kerhoas
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France
| | - Jennifer Carteret
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France
| | - Lilou Huchet
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France
| | - Elodie Jouan
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France
| | - Laurence Huc
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France; Laboratoire Interdisciplinaire Sciences Innovations Sociétés (LISIS), INRAE/CNRS/Université Gustave Eiffel, Marne-La-Vallée 77454, France
| | - Marc Le Vée
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France.
| | - Olivier Fardel
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Rennes 35000, France
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12
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Ekiciler A, Chen WLK, Bo Y, Pugliano A, Donzelli M, Parrott N, Umehara K. Quantitative Cytochrome P450 3A4 Induction Risk Assessment Using Human Hepatocytes Complemented with Pregnane X Receptor-Activating Profiles. Drug Metab Dispos 2023; 51:276-284. [PMID: 36460477 DOI: 10.1124/dmd.122.001132] [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: 09/23/2022] [Revised: 11/14/2022] [Accepted: 11/23/2022] [Indexed: 12/05/2022] Open
Abstract
Reliable in vitro to in vivo translation of cytochrome P450 (CYP) 3A4 induction potential is essential to support risk mitigation for compounds during pharmaceutical discovery and development. In this study, a linear correlation of CYP3A4 mRNA induction potential in human hepatocytes with the respective pregnane-X receptor (PXR) activation in a reporter gene assay using DPX2 cells was successfully demonstrated for 13 clinically used drugs. Based on this correlation, using rifampicin as a positive control, the magnitude of CYP3A4 mRNA induction for 71 internal compounds at several concentrations up to 10 µM (n = 90) was predicted within 2-fold error for 64% of cases with only a few false positives (19%). Furthermore, the in vivo area under the curve reduction of probe CYP substrates was reasonably predicted for eight marketed drugs (carbamazepine, dexamethasone, enzalutamide, nevirapine, phenobarbital, phenytoin, rifampicin, and rufinamide) using the static net effect model using both the PXR activation and CYP3A4 mRNA induction data. The liver exit concentrations were used for the model in place of the inlet concentrations to avoid false positive predictions and the concentration achieving twofold induction (F2) was used to compensate for the lack of full induction kinetics due to cytotoxicity and solubility limitations in vitro. These findings can complement the currently available induction risk mitigation strategy and potentially influence the drug interaction modeling work conducted at clinical stages. SIGNIFICANCE STATEMENT: The established correlation of CYP3A4 mRNA in human hepatocytes to PXR activation provides a clear cut-off to identify a compound showing an in vitro induction risk, complementing current regulatory guidance. Also, the demonstrated in vitro-in vivo translation of induction data strongly supports a clinical development program although limitations remain for drug candidates showing complex disposition pathways, such as involvement of auto-inhibition/induction, active transport and high protein binding.
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Affiliation(s)
- Aynur Ekiciler
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Wen Li Kelly Chen
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Yan Bo
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Alessandra Pugliano
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Massimiliano Donzelli
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Neil Parrott
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Kenichi Umehara
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
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13
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Gomez-Mantilla JD, Huang F, Peters SA. Can Mechanistic Static Models for Drug-Drug Interactions Support Regulatory Filing for Study Waivers and Label Recommendations? Clin Pharmacokinet 2023; 62:457-480. [PMID: 36752991 PMCID: PMC10042977 DOI: 10.1007/s40262-022-01204-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2022] [Indexed: 02/09/2023]
Abstract
BACKGROUND AND OBJECTIVE Mechanistic static and dynamic physiologically based pharmacokinetic models are used in clinical drug development to assess the risk of drug-drug interactions (DDIs). Currently, the use of mechanistic static models is restricted to screening DDI risk for an investigational drug, while dynamic physiologically based pharmacokinetic models are used for quantitative predictions of DDIs to support regulatory filing. As physiologically based pharmacokinetic model development by sponsors as well as a review of models by regulators require considerable resources, we explored the possibility of using mechanistic static models to support regulatory filing, using representative cases of successful physiologically based pharmacokinetic submissions to the US Food and Drug Administration under different classes of applications. METHODS Drug-drug interaction predictions with mechanistic static models were done for representative cases in the different classes of applications using the same data and modelling workflow as described in the Food and Drug Administration clinical pharmacology reviews. We investigated the hypothesis that the use of unbound average steady-state concentrations of modulators as driver concentrations in the mechanistic static models should lead to the same conclusions as those from physiologically based pharmacokinetic modelling for non-dynamic measures of DDI risk assessment such as the area under the plasma concentration-time curve ratio, provided the same input data are employed for the interacting drugs. RESULTS Drug-drug interaction predictions of area under the plasma concentration-time curve ratios using mechanistic static models were mostly comparable to those reported in the Food and Drug Administration reviews using physiologically based pharmacokinetic models for all representative cases in the different classes of applications. CONCLUSIONS The results reported in this study should encourage the use of models that best fit an intended purpose, limiting the use of physiologically based pharmacokinetic models to those applications that leverage its unique strengths, such as what-if scenario testing to understand the effect of dose staggering, evaluating the role of uptake and efflux transporters, extrapolating DDI effects from studied to unstudied populations, or assessing the impact of DDIs on the exposure of a victim drug with concurrent mechanisms. With this first step, we hope to trigger a scientific discussion on the value of a routine comparison of the two methods for regulatory submissions to potentially create a best practice that could help identify examples where the use of dynamic changes in modulator concentrations could make a difference to DDI risk assessment.
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Affiliation(s)
- Jose David Gomez-Mantilla
- Boehringer Ingelheim Pharma GmbH & Co. KG, TMCP Therapeutic Areas, Binger Str. 173, 55218, Ingelheim am Rhein, Germany
| | | | - Sheila Annie Peters
- Boehringer Ingelheim Pharma GmbH & Co. KG, TMCP Therapeutic Areas, Binger Str. 173, 55218, Ingelheim am Rhein, Germany.
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14
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Chen Q, Zhou X, Rehmel J, Steele JP, Svensson KA, Beck JP, Hembre EJ, Hao J. Ensemble Docking Approach to Mitigate Pregnane X Receptor-Mediated CYP3A4 Induction Risk. J Chem Inf Model 2023; 63:173-186. [PMID: 36473234 DOI: 10.1021/acs.jcim.2c01175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Three structurally closely related dopamine D1 receptor positive allosteric modulators (D1 PAMs) based on a tetrahydroisoquinoline (THIQ) scaffold were profiled for their CYP3A4 induction potentials. It was found that the length of the linker at the C5 position greatly affected the potentials of these D1 PAMs as CYP3A4 inducers, and the level of induction correlated well with the activation of the pregnane X receptor (PXR). Based on the published PXR X-ray crystal structures, we built a binding model specifically for these THIQ-scaffold-based D1 PAMs in the PXR ligand-binding pocket via an ensemble docking approach and found the model could explain the observed CYP induction disparity. Combined with our previously reported D1 receptor homology model, which identified the C5 position as pointing toward the solvent-exposed space, our PXR-binding model coincidentally suggested that structural modifications at the C5 position could productively modulate the CYP induction potential while maintaining the D1 PAM potency of these THIQ-based PAMs.
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Affiliation(s)
- Qi Chen
- Discovery Chemistry Research and Technologies, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - Xin Zhou
- Drug Disposition, Lilly Biotechnology Center, Eli Lilly and Company, 10290 Campus Point Drive, San Diego, California92121, United States
| | - Jessica Rehmel
- Drug Disposition, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - James P Steele
- Quantitative Biology, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - Kjell A Svensson
- Neuroscience Discovery, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - James P Beck
- Discovery Chemistry Research and Technologies, Lilly Biotechnology Center, Eli Lilly and Company, 10290 Campus Point Drive, San Diego, California92121, United States
| | - Erik J Hembre
- Discovery Chemistry Research and Technologies, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana46285, United States
| | - Junliang Hao
- Discovery Chemistry Research and Technologies, Lilly Biotechnology Center, Eli Lilly and Company, 10290 Campus Point Drive, San Diego, California92121, United States
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15
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Vu NAT, Song YM, Tran QT, Yun HY, Kim SK, Chae JW, Kim JK. Beyond the Michaelis-Menten: Accurate Prediction of Drug Interactions through Cytochrome P450 3A4 Induction. Clin Pharmacol Ther 2022; 113:1048-1057. [PMID: 36519932 DOI: 10.1002/cpt.2824] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 12/09/2022] [Indexed: 12/23/2022]
Abstract
The US Food and Drug Administration (FDA) guidance has recommended several model-based predictions to determine potential drug-drug interactions (DDIs) mediated by cytochrome P450 (CYP) induction. In particular, the ratio of substrate area under the plasma concentration-time curve (AUCR) under and not under the effect of inducers is predicted by the Michaelis-Menten (MM) model, where the MM constant ( K m $$ {K}_{\mathrm{m}} $$ ) of a drug is implicitly assumed to be sufficiently higher than the concentration of CYP enzymes that metabolize the drug ( E T $$ {E}_{\mathrm{T}} $$ ) in both the liver and small intestine. Furthermore, the fraction absorbed from gut lumen ( F a $$ {F}_{\mathrm{a}} $$ ) is also assumed to be one because F a $$ {F}_{\mathrm{a}} $$ is usually unknown. Here, we found that such assumptions lead to serious errors in predictions of AUCR. To resolve this, we propose a new framework to predict AUCR. Specifically, F a $$ {F}_{\mathrm{a}} $$ was re-estimated from experimental permeability values rather than assuming it to be one. Importantly, we used the total quasi-steady-state approximation to derive a new equation, which is valid regardless of the relationship between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ , unlike the MM model. Thus, our framework becomes much more accurate than the original FDA equation, especially for drugs with high affinities, such as midazolam or strong inducers, such as rifampicin, so that the ratio between K m $$ {K}_{\mathrm{m}} $$ and E T $$ {E}_{\mathrm{T}} $$ becomes low (i.e., the MM model is invalid). Our work greatly improves the prediction of clinical DDIs, which is critical to preventing drug toxicity and failure.
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Affiliation(s)
- Ngoc-Anh Thi Vu
- College of Pharmacy, Chungnam National University, Daejeon, Korea
| | - Yun Min Song
- Department of Mathematical Sciences, KAIST, Daejeon, Korea.,Biomedical Mathematics Group, Institute for Basic Science, Daejeon, Korea
| | - Quyen Thi Tran
- College of Pharmacy, Chungnam National University, Daejeon, Korea
| | - Hwi-Yeol Yun
- College of Pharmacy, Chungnam National University, Daejeon, Korea.,Department of Bio-AI convergence, Chungnam National University, Daejeon, Korea
| | - Sang Kyum Kim
- College of Pharmacy, Chungnam National University, Daejeon, Korea
| | - Jung-Woo Chae
- College of Pharmacy, Chungnam National University, Daejeon, Korea.,Department of Bio-AI convergence, Chungnam National University, Daejeon, Korea
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, KAIST, Daejeon, Korea.,Biomedical Mathematics Group, Institute for Basic Science, Daejeon, Korea
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16
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Kane NF, Kiani BH, Desrosiers MR, Towler MJ, Weathers PJ. Artemisia extracts differ from artemisinin effects on human hepatic CYP450s 2B6 and 3A4 in vitro. JOURNAL OF ETHNOPHARMACOLOGY 2022; 298:115587. [PMID: 35934190 DOI: 10.1016/j.jep.2022.115587] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/25/2022] [Accepted: 07/26/2022] [Indexed: 06/15/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE The Chinese medicinal herb, Artemisia annua L., has been used for >2,000 yr as traditional tea infusions to treat a variety of infectious diseases including malaria, and its use is spreading globally (along with A. afra Jacq. ex Willd.) mainly through grassroots efforts. AIM OF THE STUDY Artemisinin is more bioavailable delivered from the plant, Artemisia annua L. than the pure drug, but little is known about how delivery via a hot water infusion (tea) alters induction of hepatic CYP2B6 and CYP3A4 that metabolize artemisinin. MATERIALS AND METHODS HepaRG cells were treated with 10 μM artemisinin or rifampicin (positive control), and teas (10 g/L) of A. annua SAM, and A. afra SEN and MAL with 1.6, 0.05 and 0 mg/g DW artemisinin in the leaves, respectively; qPCR and Western blots were used to measure CYP2B6 and CYP3A4 responses. Enzymatic activity of these P450s was measured using human liver microsomes and P450-Glo assays. RESULTS All teas inhibited activity of CYP2B6 and CYP3A4. Artemisinin and the high artemisinin-containing tea infusion (SAM) induced CYP2B6 and CYP3A4 transcription, but artemisinin-deficient teas, MAL and SEN, did not. Artemisinin increased CYP2B6 and CYP3A4 protein levels, but none of the three teas did, indicating a post-transcription inhibition by all three teas. CONCLUSIONS This study showed that Artemisia teas inhibit activity and artemisinin autoinduction of CYP2B6 and CYP3A4 post transcription, a response likely the effect of other phytochemicals in these teas. Results are important for understanding Artemisia tea posology.
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Affiliation(s)
- Ndeye F Kane
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
| | - Bushra H Kiani
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
| | - Matthew R Desrosiers
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
| | - Melissa J Towler
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
| | - Pamela J Weathers
- Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
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17
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Ramsden D, Fullenwider CL. Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models. Eur J Drug Metab Pharmacokinet 2022; 47:467-482. [PMID: 35344159 PMCID: PMC9232448 DOI: 10.1007/s13318-022-00763-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2022] [Indexed: 11/29/2022]
Abstract
Background and Objective Induction of drug-metabolizing enzymes can lead to drug-drug interactions (DDIs); therefore, early assessment is often conducted. Previous reports focused on true positive cytochrome P450 3A (CYP3A) inducers leaving a gap in translation for in vitro inducers which do not manifest in clinical induction. The goal herein was to expand the in vitro induction dataset by including true negative clinical inducers to identify a correction factor to basic DDI models, which reduces false positives without impacting false negatives. Methods True negative clinical inducers were identified through a literature search, in vitro induction parameters were generated in three human hepatocyte donors, and the performance of basic induction models proposed by regulatory agencies, concentration producing twofold induction (F2), basic static model (R3) and relative induction score (RIS), was used to characterize clinical induction risk. Results The data demonstrated the importance of correcting for in vitro binding and metabolism to derive induction parameters. The aggregate analysis indicates that the RIS with a positive cut-off of < 0.7-fold area under the curve ratio (AUCR) provides the best quantitative prediction. Additionally, correction factors of ten and two times the unbound peak plasma concentration at steady state (Cmax,ss,u) can be confidently used to identify true positive inducers when referenced against the concentration resulting in twofold increase in messenger ribonucleic acid (mRNA) or using the R3 equation, respectively. Conclusions These iterative improvements, which reduce the number of false positives, could aid regulatory recommendations and limit unnecessary clinical explorations into CYP3A induction. Graphical abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1007/s13318-022-00763-y.
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Affiliation(s)
- Diane Ramsden
- Takeda Development Center Americas, Inc., Cambridge, MA, USA. .,Department of Oncology Research and Early Development, Drug Metabolism and Pharmacokinetics, AstraZeneca, 35 Gatehouse Park, Waltham, MA, 02451, USA.
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18
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Savaryn JP, Sun J, Ma J, Jenkins GJ, Stresser DM. Broad Application of CYP3A4 Liquid Chromatography-Mass Spectrometry Protein Quantification in Hepatocyte Cytochrome P450 Induction Assays Identifies Nonuniformity in mRNA and Protein Induction Responses. Drug Metab Dispos 2022; 50:105-113. [PMID: 34857529 DOI: 10.1124/dmd.121.000638] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/30/2021] [Indexed: 11/22/2022] Open
Abstract
Screening for cytochrome P450 (CYP) induction potential is routine in drug development. Induction results in a net increase in CYP protein and is assessed typically by measuring indirect endpoints, i.e., enzyme activity and mRNA in vitro. Recent methodological advancements have made CYP protein quantification by liquid chromatography-mass spectrometry in vitro induction studies more accessible and amenable to routine testing. In this study, we evaluated CYP3A4 concentration dependence of induction response for 11 compounds (rifampin, rifabutin, carbamazepine, efavirenz, nitrendipine, flumazenil, pioglitazone, rosiglitazone, troglitazone, pazopanib, and ticagrelor) in plated hepatocytes from two or three donors incorporating in the assessment all three endpoints. In addition, the time-dependence of the induction was examined over 1, 2, or 3 days of treatment. For most compounds, mRNA, enzyme activity, and protein endpoints exhibited similarity in induction responses. Pazopanib and ticagrelor were notable exceptions as neither protein nor enzyme activity were induced despite mRNA induction of a magnitude similar to efavirenz, pioglitazone, or rosiglitazone, which clearly induced in all three endpoints. Static modeling of clinical induction responses supported a role for protein as a predictive endpoint. These data highlight the value of including CYP protein quantification as an induction assay endpoint to provide a more comprehensive assessment of induction liability. SIGNIFICANCE STATEMENT: Direct, liquid chromatography-mass spectrometry (LC-MS)-based quantification of cytochrome P450 (CYP) protein is a desirable induction assay endpoint; however such application has been limited due to inefficient workflows. Here, we incorporate recent advancements in protein quantitation methods to efficiently quantify CYP3A4 protein in in vitro induction assays with 11 compounds in up to 3 donors. The data indicate induction responses from mRNA do not always align with those of protein suggesting assessment of induction liability is more complex than thought previously.
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Affiliation(s)
| | - Jun Sun
- AbbVie Inc., DMPK-BA, North Chicago, Illinois
| | - Junli Ma
- AbbVie Inc., DMPK-BA, North Chicago, Illinois
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19
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Hariparsad N, Ramsden D, Taskar K, Badée J, Venkatakrishnan K, Reddy MB, Cabalu T, Mukherjee D, Rehmel J, Bolleddula J, Emami Riedmaier A, Prakash C, Chanteux H, Mao J, Umehara K, Shah K, De Zwart L, Dowty M, Kotsuma M, Li M, Pilla Reddy V, McGinnity DF, Parrott N. Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective. Clin Pharmacol Ther 2021; 112:770-781. [PMID: 34862964 DOI: 10.1002/cpt.2503] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/18/2021] [Indexed: 12/21/2022]
Abstract
The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.
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Affiliation(s)
- Niresh Hariparsad
- DMPK, Research and Early Development, Oncology R&D, AstraZeneca, Boston, Massachusetts, USA
| | - Diane Ramsden
- Takeda Development Center Americas, Inc., Cambridge, Massachusetts, USA
| | - Kunal Taskar
- Drug Metabolism and Pharmacokinetics, IVIVT, GlaxoSmithKline, Stevenage, UK
| | - Justine Badée
- PK Sciences, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Karthik Venkatakrishnan
- EMD Serono Research & Development Institute, Inc, Billerica, Massachusetts, USA.,Merck KGaA, Darmstadt, Germany
| | - Micaela B Reddy
- Department of Clinical Pharmacology, Oncology, Pfizer, Boulder, Colorado, USA
| | | | - Dwaipayan Mukherjee
- Clinical Pharmacology & Pharmacometrics, AbbVie, Inc., North Chicago, Illinois, USA
| | - Jessica Rehmel
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Jayaprakasam Bolleddula
- EMD Serono Research & Development Institute, Inc, Billerica, Massachusetts, USA.,Merck KGaA, Darmstadt, Germany
| | | | | | | | - Jialin Mao
- Department of Drug Metabolism and Pharmacokinetics, Genentech, A Member of the Roche Group, South San Francisco, California, USA
| | - Kenichi Umehara
- Pharmaceutical Sciences, Roche Pharma Research & Early Development, Roche Innovation Center Basel, Basel, Switzerland
| | - Kushal Shah
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts, USA
| | | | - Martin Dowty
- Department of Pharmacokinetics, Dynamic, and Metabolism, Pfizer, Cambridge, Massachusetts, USA
| | - Masakatsu Kotsuma
- Quantitative Clinical Pharmacology, Daiichi-Sankyo, Inc., New Jersey, USA
| | - Mengyao Li
- Pharmacokinetics, Dynamics and Metabolism, Sanofi, Bridgewater, New Jersey, USA
| | - Venkatesh Pilla Reddy
- Clinical Pharmacology and Pharmacometrics, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dermot F McGinnity
- DMPK, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Neil Parrott
- Pharmaceutical Sciences, Roche Pharma Research & Early Development, Roche Innovation Center Basel, Basel, Switzerland
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20
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Zhang H, Ou YC, Su D, Wang F, Wang L, Sahasranaman S, Tang Z. In vitro investigations into the roles of CYP450 enzymes and drug transporters in the drug interactions of zanubrutinib, a covalent Bruton's tyrosine kinase inhibitor. Pharmacol Res Perspect 2021; 9:e00870. [PMID: 34664792 PMCID: PMC8524670 DOI: 10.1002/prp2.870] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/25/2021] [Indexed: 11/27/2022] Open
Abstract
Zanubrutinib is a highly selective, potent, orally available, targeted covalent inhibitor (TCI) of Bruton's tyrosine kinase (BTK). This work investigated the in vitro drug metabolism and transport of zanubrutinib, and its potential for clinical drug-drug interactions (DDIs). Phenotyping studies indicated cytochrome P450 (CYP) 3A are the major CYP isoform responsible for zanubrutinib metabolism, which was confirmed by a clinical DDI study with itraconazole and rifampin. Zanubrutinib showed mild reversible inhibition with half maximal inhibitory concentration (IC50 ) of 4.03, 5.69, and 7.80 μM for CYP2C8, CYP2C9, and CYP2C19, respectively. Data in human hepatocytes disclosed induction potential for CYP3A4, CYP2B6, and CYP2C enzymes. Transport assays demonstrated that zanubrutinib is not a substrate of human breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP)1B1/1B3, organic cation transporter (OCT)2, or organic anion transporter (OAT)1/3 but is a potential substrate of the efflux transporter P-glycoprotein (P-gp). Additionally, zanubrutinib is neither an inhibitor of P-gp at concentrations up to 10.0 μM nor an inhibitor of BCRP, OATP1B1, OATP1B3, OAT1, and OAT3 at concentrations up to 5.0 μM. The in vitro results with CYPs and transporters were correlated with the available clinical DDIs using basic models and mechanistic static models. Zanubrutinib is not likely to be involved in transporter-mediated DDIs. CYP3A inhibitors and inducers may impact systemic exposure of zanubrutinib. Dose adjustments may be warranted depending on the potency of CYP3A modulators.
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Affiliation(s)
| | | | - Dan Su
- BeiGene (Beijing) Co., LtdBeijingChina
| | - Fan Wang
- BeiGene (Beijing) Co., LtdBeijingChina
| | - Lai Wang
- BeiGene (Beijing) Co., LtdBeijingChina
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21
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Smutny T, Bernhauerova V, Smutna L, Tebbens JD, Pavek P. Expression dynamics of pregnane X receptor-controlled genes in 3D primary human hepatocyte spheroids. Arch Toxicol 2021; 96:195-210. [PMID: 34689256 DOI: 10.1007/s00204-021-03177-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/06/2021] [Indexed: 02/07/2023]
Abstract
The pregnane X receptor (PXR) is a ligand-activated nuclear receptor controlling hepatocyte expression of numerous genes. Although expression changes in xenobiotic-metabolizing, lipogenic, gluconeogenic and bile acid synthetic genes have been described after PXR activation, the temporal dynamics of their expression is largely unknown. Recently, 3D spheroids of primary human hepatocytes (PHHs) have been characterized as the most phenotypically relevant hepatocyte model. We used 3D PHHs to assess time-dependent expression profiles of 12 prototypic PXR-controlled genes in the time course of 168 h of rifampicin treatment (1 or 10 µM). We observed a similar bell-shaped time-induction pattern for xenobiotic-handling genes (CYP3A4, CYP2C9, CYP2B6, and MDR1). However, we observed either biphasic profiles for genes involved in endogenous metabolism (FASN, GLUT2, G6PC, PCK1, and CYP7A1), a decrease for SHP or oscillation for PDK4 and PXR. The rifampicin concentration determined the expression profiles for some genes. Moreover, we calculated half-lives of CYP3A4 and CYP2C9 mRNA under induced or basal conditions and we used a mathematical model to describe PXR-mediated regulation of CYP3A4 expression employing 3D PHHs. The study shows the importance of long-term time-expression profiling of PXR target genes in phenotypically stable 3D PHHs and provides insight into PXR function in liver beyond our knowledge from conventional 2D in vitro models.
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Affiliation(s)
- Tomas Smutny
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, Hradec Kralove, 500 05, Czech Republic.
| | - Veronika Bernhauerova
- Department of Biophysics and Physical Chemistry, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, Hradec Kralove, 500 05, Czech Republic
| | - Lucie Smutna
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, Hradec Kralove, 500 05, Czech Republic
| | - Jurjen Duintjer Tebbens
- Department of Biophysics and Physical Chemistry, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, Hradec Kralove, 500 05, Czech Republic
| | - Petr Pavek
- Department of Pharmacology and Toxicology, Faculty of Pharmacy in Hradec Kralove, Charles University, Akademika Heyrovskeho 1203, Hradec Kralove, 500 05, Czech Republic
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22
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Steinbronn C, Yang X, Yu J, Dimova H, Huang SM, Ragueneau-Majlessi I, Isoherranen N. Do Inhibitory Metabolites Impact DDI Risk Assessment? Analysis of in vitro and in vivo Data from NDA Reviews Between 2013 and 2018. Clin Pharmacol Ther 2021; 110:452-463. [PMID: 33835478 PMCID: PMC9794360 DOI: 10.1002/cpt.2259] [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: 01/25/2021] [Revised: 03/05/2021] [Accepted: 03/16/2021] [Indexed: 12/30/2022]
Abstract
Evaluating the potential of new drugs and their metabolites to cause drug-drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite-to-parent area under the curve ratios (AUCM /AUCP ), inhibitory potency of parent and metabolites, and clinical DDIs were collected. Sixty-four percent of the metabolites quantified in vivo had AUCM /AUCP ≥ 0.25 and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. Although 50% of the metabolites with AUCM /AUCP < 0.25 were also tested in vitro, none of them showed meaningful CYP inhibition potential. The metabolite percentage of plasma total radioactivity cutoff of ≥ 10% did not appear to add value to metabolite testing strategies. No relationship between metabolite versus parent drug polarity and inhibition potency was observed. Comparison of metabolite and parent maximum concentration (Cmax ) divided by inhibition constant (Ki ) values suggested that metabolites can contribute to in vivo DDIs and, hence, quantitative prediction of clinical DDI magnitude may require both parent and metabolite data. This systematic analysis of metabolite data for newly approved drugs supports an AUCM /AUCP cutoff of ≥ 0.25 to warrant metabolite in vitro CYP screening to adequately characterize metabolite inhibitory DDI potential and support quantitative DDI predictions.
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Affiliation(s)
| | - Xinning Yang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Jingjing Yu
- Department of Pharmaceutics, University of Washington, Seattle, WA,UW Drug Interaction Solutions, University of Washington, Seattle, WA
| | - Hristina Dimova
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Shiew-Mei Huang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Isabelle Ragueneau-Majlessi
- Department of Pharmaceutics, University of Washington, Seattle, WA,UW Drug Interaction Solutions, University of Washington, Seattle, WA
| | - Nina Isoherranen
- Department of Pharmaceutics, University of Washington, Seattle, WA
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23
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Ly JQ, Wong S, Liu L, Li R, Messick K, Chang JH. Investigating the Utility of Humanized Pregnane X Receptor-Constitutive Androstane Receptor-CYP3A4/7 Mouse Model to Assess CYP3A-Mediated Induction. Drug Metab Dispos 2021; 49:540-547. [PMID: 33863817 DOI: 10.1124/dmd.121.000439] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 04/02/2021] [Indexed: 11/22/2022] Open
Abstract
Clinical induction liability is assessed with human hepatocytes. However, underpredictions in the magnitude of clinical induction have been reported. Unfortunately, in vivo studies in animals do not provide additional insight because of species differences in drug metabolizing enzymes and their regulatory pathways. To circumvent this limitation, transgenic animals expressing human orthologs were developed. The aim of this work was to investigate the utility of mouse models expressing human orthologs of pregnane X receptor, constitutive androstane receptor, and CYP3A4/7 (Tg-Composite) in evaluating clinical induction. Rifampin, efavirenz, and pioglitazone, which were employed to represent strong, moderate, and weak inducers, were administered at multiple doses to Tg-Composite animals. In vivo CYP3A activity was monitored by measuring changes in the exposure of the CYP3A probe substrate triazolam. After the in vivo studies, microsomes were prepared from their livers to measure changes of in vitro CYP3A4 activity. In both in vivo and in vitro, distinction of clinic induction was recapitulated as rifampin yielded the greatest inductive effect followed by efavirenz and pioglitazone. Interestingly, with rifampin, in vivo CYP3A activity was approximately 4-fold higher than in vitro activity. Conversely, there was no difference between in vivo and in vitro CYP3A activity with efavirenz. These findings are consistent with the report that, although rifampin exhibits differential inductive effects between the intestines and liver, efavirenz does not. These data highlight the promise of transgenic models, such as Tg-Composite, to complement human hepatocytes to enhance the translatability of clinical induction as well as become a powerful tool to further study mechanisms of drug disposition. SIGNIFICANCE STATEMENT: Underprediction of the magnitude of clinical induction when using human hepatocytes has been reported, and transgenic models may improve clinical translatability. The work presented here showcases the human orthologs of pregnane X receptor, constitutive androstane receptor, and CYP3A4/7 model, which was able to recapitulate the magnitude of clinical induction and to differentiate tissue-dependent induction observed with rifampin but not with efavirenz. These results not only foreshadow the potential application of such transgenic models in assessing clinical induction but also in further investigation of the mechanism of drug disposition.
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Affiliation(s)
- Justin Q Ly
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
| | - Susan Wong
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
| | - Liling Liu
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
| | - Ruina Li
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
| | - Kirsten Messick
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
| | - Jae H Chang
- Genentech, Inc., South San Francisco, California (J.Q.L., S.W., L.L., R.L., K.M.), and ORIC Pharmaceuticals, South San Francisco, California (J.H.C.)
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24
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Hall A, Chanteux H, Ménochet K, Ledecq M, Schulze MSED. Designing Out PXR Activity on Drug Discovery Projects: A Review of Structure-Based Methods, Empirical and Computational Approaches. J Med Chem 2021; 64:6413-6522. [PMID: 34003642 DOI: 10.1021/acs.jmedchem.0c02245] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
This perspective discusses the role of pregnane xenobiotic receptor (PXR) in drug discovery and the impact of its activation on CYP3A4 induction. The use of structural biology to reduce PXR activity on drug discovery projects has become more common in recent years. Analysis of this work highlights several important molecular interactions, and the resultant structural modifications to reduce PXR activity are summarized. The computational approaches undertaken to support the design of new drugs devoid of PXR activation potential are also discussed. Finally, the SAR of empirical design strategies to reduce PXR activity is reviewed, and the key SAR transformations are discussed and summarized. In conclusion, this perspective demonstrates that PXR activity can be greatly diminished or negated on active drug discovery projects with the knowledge now available. This perspective should be useful to anyone who seeks to reduce PXR activity on a drug discovery project.
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Affiliation(s)
- Adrian Hall
- UCB, Avenue de l'Industrie, Braine-L'Alleud 1420, Belgium
| | | | | | - Marie Ledecq
- UCB, Avenue de l'Industrie, Braine-L'Alleud 1420, Belgium
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25
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Wong SG, Ramsden D, Dallas S, Fung C, Einolf HJ, Palamanda J, Chen L, Goosen TC, Siu YA, Zhang G, Tweedie D, Hariparsad N, Jones B, Yates PD. Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Guidelines on Model Fitting and Recommendations on Time Course for In Vitro Cytochrome P450 Induction Studies Including Impact on Drug Interaction Risk Assessment. Drug Metab Dispos 2021; 49:94-110. [PMID: 33139460 DOI: 10.1124/dmd.120.000055] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 10/21/2020] [Indexed: 02/13/2025] Open
Abstract
Translational and ADME Sciences Leadership Group Induction Working Group (IWG) presents an analysis on the time course for cytochrome P450 induction in primary human hepatocytes. Induction of CYP1A2, CYP2B6, and CYP3A4 was evaluated by seven IWG laboratories after incubation with prototypical inducers (omeprazole, phenobarbital, rifampicin, or efavirenz) for 6-72 hours. The effect of incubation duration and model-fitting approaches on induction parameters (Emax and EC50) and drug-drug interaction (DDI) risk assessment was determined. Despite variability in induction response across hepatocyte donors, the following recommendations are proposed: 1) 48 hours should be the primary time point for in vitro assessment of induction based on mRNA level or activity, with no further benefit from 72 hours; 2) when using mRNA, 24-hour incubations provide reliable assessment of induction and DDI risk; 3) if validated using prototypical inducers (>10-fold induction), 12-hour incubations may provide an estimate of induction potential, including characterization as negative if <2-fold induction of mRNA and no concentration dependence; 4) atypical dose-response ("bell-shaped") curves can be addressed by removing points outside an established confidence interval and %CV; 5) when maximum fold induction is well defined, the choice of nonlinear regression model has limited impact on estimated induction parameters; 6) when the maximum fold induction is not well defined, conservative DDI risk assessment can be obtained using sigmoidal three-parameter fit or constraining logistic three- or four-parameter fits to the maximum observed fold induction; 7) preliminary data suggest initial slope of the fold induction curve can be used to estimate Emax/EC50 and for induction risk assessment. SIGNIFICANCE STATEMENT: Regulatory agencies provide inconsistent guidance on the optimum length of time to evaluate cytochrome P450 induction in human hepatocytes, with EMA recommending 72 hours and FDA suggesting 48-72 hours. The Induction Working Group analyzed a large data set generated by seven member companies and determined that induction response and drug-drug risk assessment determined after 48-hour incubations were representative of 72-hour incubations. Additional recommendations are provided on model-fitting techniques for induction parameter estimation and addressing atypical concentration-response curves.
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Affiliation(s)
- Simon G Wong
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Diane Ramsden
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Shannon Dallas
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Conrad Fung
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Heidi J Einolf
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Jairam Palamanda
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Liangfu Chen
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Theunis C Goosen
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Y Amy Siu
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - George Zhang
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Donald Tweedie
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Niresh Hariparsad
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Barry Jones
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
| | - Phillip D Yates
- Genentech, South San Francisco, California (S.G.W.); Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Pfizer Global Research and Development, Cambridge, Massachusetts (P.D.Y.); Eisai, Cambridge, Massachusetts (Y.A.S.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); Merck & Co., Inc., Kenilworth, New Jersey (D.T., J.P.); and AstraZeneca, Cambridge, Cambridgeshire, United Kingdom (B.J.)
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26
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Sudsakorn S, Bahadduri P, Fretland J, Lu C. 2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists. Curr Drug Metab 2020; 21:403-426. [DOI: 10.2174/1389200221666200620210522] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/28/2020] [Accepted: 05/28/2020] [Indexed: 12/26/2022]
Abstract
Background:
In January 2020, the US FDA published two final guidelines, one entitled “In vitro Drug
Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry”
and the other entitled “Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated
Drug Interactions Guidance for Industry”. These were updated from the 2017 draft in vitro and clinical DDI
guidance.
Methods:
This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines
published by the European Medicines Agency (EMA) and Japanese Pharmaceuticals and Medical Devices Agency
(PMDA) along with the current literature.
Results:
The updates were provided in the final FDA DDI guidelines and explained the rationale of those changes
based on the understanding from research and literature. Furthermore, a comparison among the FDA, EMA, and
PMDA DDI guidelines are presented in Tables 1, 2 and 3.
Conclusion:
The new 2020 clinical DDI guidance from the FDA now has even higher harmonization with the
guidance (or guidelines) from the EMA and PMDA. A comparison of DDI guidance from the FDA 2017, 2020,
EMA, and PMDA on CYP and transporter based DDI, mathematical models, PBPK, and clinical evaluation of DDI
is presented in this review.
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Affiliation(s)
- Sirimas Sudsakorn
- Department of Drug Metabolism and Pharmacokinetics, Sanofi-Genzyme, Waltham, MA 02451, United States
| | - Praveen Bahadduri
- Department of Drug Metabolism and Pharmacokinetics, Sanofi-Genzyme, Waltham, MA 02451, United States
| | - Jennifer Fretland
- Department of Drug Metabolism and Pharmacokinetics, Sanofi-Genzyme, Waltham, MA 02451, United States
| | - Chuang Lu
- Department of Drug Metabolism and Pharmacokinetics, Sanofi-Genzyme, Waltham, MA 02451, United States
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27
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Ito K, Sjöstedt N, Malinen MM, Guo C, Brouwer KLR. Hepatic Transporter Alterations by Nuclear Receptor Agonist T0901317 in Sandwich-Cultured Human Hepatocytes: Proteomic Analysis and PBPK Modeling to Evaluate Drug-Drug Interaction Risk. J Pharmacol Exp Ther 2020; 373:261-268. [PMID: 32127372 DOI: 10.1124/jpet.119.263459] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 02/26/2020] [Indexed: 01/07/2023] Open
Abstract
In vitro approaches for predicting drug-drug interactions (DDIs) caused by alterations in transporter protein regulation are not well established. However, reports of transporter regulation via nuclear receptor (NR) modulation by drugs are increasing. This study examined alterations in transporter protein levels in sandwich-cultured human hepatocytes (SCHH; n = 3 donors) measured by liquid chromatography-tandem mass spectrometry-based proteomic analysis after treatment with N-[4-(1,1,1,3,3,3-hexafluoro-2-hydroxypropan-2-yl)phenyl]-N-(2,2,2-trifluoroethyl)benzenesulfonamide (T0901317), the first described synthetic liver X receptor agonist. T0901317 treatment (10 μM, 48 hours) decreased the levels of organic cation transporter (OCT) 1 (0.22-, 0.43-, and 0.71-fold of control) and organic anion transporter (OAT) 2 (0.38-, 0.38-, and 0.53-fold of control) and increased multidrug resistance protein (MDR) 1 (1.37-, 1.48-, and 1.59-fold of control). The induction of NR downstream gene expression supports the hypothesis that T0901317 off-target effects on farnesoid X receptor and pregnane X receptor activation are responsible for the unexpected changes in OCT1, OAT2, and MDR1. Uptake of the OCT1 substrate metformin in SCHH was decreased by T0901317 treatment. Effects of decreased OCT1 levels on metformin were simulated using a physiologically-based pharmacokinetic (PBPK) model. Simulations showed a clear decrease in metformin hepatic exposure resulting in a decreased pharmacodynamic effect. This DDI would not be predicted by the modest changes in simulated metformin plasma concentrations. Altogether, the current study demonstrated that an approach combining SCHH, proteomic analysis, and PBPK modeling is useful for revealing tissue concentration-based DDIs caused by unexpected regulation of hepatic transporters by NR modulators. SIGNIFICANCE STATEMENT: This study utilized an approach combining sandwich-cultured human hepatocytes, proteomic analysis, and physiologically based pharmacokinetic modeling to evaluate alterations in pharmacokinetics (PK) and pharmacodynamics (PD) caused by transporter regulation by nuclear receptor modulators. The importance of this approach from a mechanistic and clinically relevant perspective is that it can reveal drug-drug interactions (DDIs) caused by unexpected regulation of hepatic transporters and enable prediction of altered PK and PD changes, especially for tissue concentration-based DDIs.
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Affiliation(s)
- Katsuaki Ito
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (K.I., N.S., M.M.M., C.G., K.L.R.B.) and Drug Metabolism and Pharmacokinetics Research Department, Teijin Pharma Limited, Hino, Tokyo, Japan (K.I.)
| | - Noora Sjöstedt
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (K.I., N.S., M.M.M., C.G., K.L.R.B.) and Drug Metabolism and Pharmacokinetics Research Department, Teijin Pharma Limited, Hino, Tokyo, Japan (K.I.)
| | - Melina M Malinen
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (K.I., N.S., M.M.M., C.G., K.L.R.B.) and Drug Metabolism and Pharmacokinetics Research Department, Teijin Pharma Limited, Hino, Tokyo, Japan (K.I.)
| | - Cen Guo
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (K.I., N.S., M.M.M., C.G., K.L.R.B.) and Drug Metabolism and Pharmacokinetics Research Department, Teijin Pharma Limited, Hino, Tokyo, Japan (K.I.)
| | - Kim L R Brouwer
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (K.I., N.S., M.M.M., C.G., K.L.R.B.) and Drug Metabolism and Pharmacokinetics Research Department, Teijin Pharma Limited, Hino, Tokyo, Japan (K.I.)
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28
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Lu C, Di L. In vitro
and
in vivo
methods to assess pharmacokinetic drug– drug interactions in drug discovery and development. Biopharm Drug Dispos 2020; 41:3-31. [DOI: 10.1002/bdd.2212] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 09/27/2019] [Accepted: 10/28/2019] [Indexed: 12/11/2022]
Affiliation(s)
- Chuang Lu
- Department of DMPKSanofi Company Waltham MA 02451
| | - Li Di
- Pharmacokinetics, Dynamics and MetabolismPfizer Worldwide Research & Development Groton CT 06340
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29
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Evaluation of drug-drug interactions in drug metabolism: Differences and harmonization in guidance/guidelines. Drug Metab Pharmacokinet 2019; 35:71-75. [PMID: 31757749 DOI: 10.1016/j.dmpk.2019.10.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 10/10/2019] [Accepted: 10/15/2019] [Indexed: 02/03/2023]
Abstract
The U.S. Drugs and Food Administration (FDA) and the Ministry of Health, Labor and Welfare of Japan (MHLW) issued the drastically revised draft guidance and final guideline on drug-drug interactions (DDI) in 2017 and 2018, respectively. One of the most drastic changes for the evaluation of inhibition potential of drug metabolizing enzymes in the liver using a basic model in these guidance and guideline are represented by the concept to use the unbound maximum concentration in the systemic circulation as the investigational drug concentration instead of the total maximum concentration and the corresponding cutoff values are applied in harmonization with the current DDI guideline of Europe. In this review, the current DDI guidance and guidelines of the three regions are compared and the points which are in common are described. In addition, several issues to be considered and/or clarified such as a criterion for the metabolites to be evaluated as perpetrator drugs, details of in vitro study design etc. are also briefly summarized. Based on further accumulation of data and information, and their continuous international scientific discussion, these issues are expected to be solved to make the current DDI guidance and guidelines be much more harmonized and practically available standards.
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30
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Ramsden D, Fung C, Hariparsad N, Kenny JR, Mohutsky M, Parrott NJ, Robertson S, Tweedie DJ. Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates. Drug Metab Dispos 2019; 47:1206-1221. [PMID: 31439574 DOI: 10.1124/dmd.119.087270] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.
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Affiliation(s)
- Diane Ramsden
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Conrad Fung
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Niresh Hariparsad
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Jane R Kenny
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Michael Mohutsky
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Neil J Parrott
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Sarah Robertson
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Donald J Tweedie
- Alnylam Pharmaceuticals, Cambridge, Massachusetts (D.R.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H., S.R.); Genentech, South San Francisco, California (J.R.K.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Roche Innovation Center, Basel, Switzerland (N.J.P.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
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31
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Badhan RKS, Gittins R, Al Zabit D. The optimization of methadone dosing whilst treating with rifampicin: A pharmacokinetic modeling study. Drug Alcohol Depend 2019; 200:168-180. [PMID: 31122724 DOI: 10.1016/j.drugalcdep.2019.03.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 02/28/2019] [Accepted: 03/18/2019] [Indexed: 01/09/2023]
Abstract
BACKGROUND The use of oral methadone in opioid substitution treatment (OST) for the management of opioid use disorder is established clinical practice. Confounding treatment is the increased risks of contracting Mycobacterium tuberculosis, the mainstay treatment of which incorporates the potent CYP 2B6 inducer rifampicin. METHODS This study applied pharmacokinetic modelling using virtual clinical trials, to pharmacokinetically quantify the extent and impact of rifampicin-mediated drug-drug interactions (DDI) on methadone plasma concentrations. An R-methadone model was developed and validated against 11 retrospective clinical studies prior to use in all subsequent studies. The aims were to investigate: (i) the impact of the DDI on daily methadone doses of 60 mg, 90 mg and 120 mg; (ii) dose escalation during rifampicin and (iii) dose reduction following rifampicin cessation. RESULTS A dose increase to 160 mg daily during rifampicin treatment phases was required to maintain peak methadone plasma concentrations within a derived therapeutic window of 80-700 ng/mL. Dose escalation prior to rifampicin initiation was not required and resulted in an increase in subjects with supra-therapeutic concentrations. However, during rifampicin cessation, a dose reduction of 10 mg every 2 days commencing prior to rifampicin cessation, ensured that most patients possessed a peak methadone plasma concentration within an optimal therapeutic window. IMPLICATIONS Rifampicin significantly alters methadone plasma concentrations and necessitates dose adjustments. Daily doses of almost double those used perhaps more commonly in clinical practice are required for optimal plasma concentration and careful consideration of dose reduction strategies would be required during the deinduction phase.
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Affiliation(s)
- Raj K S Badhan
- Medicines Optimisation Research Group, Aston Pharmacy School, Aston University, Birmingham, B4 7ET, United Kingdom.
| | | | - Dina Al Zabit
- Medicines Optimisation Research Group, Aston Pharmacy School, Aston University, Birmingham, B4 7ET, United Kingdom
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32
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Kapetas AJ, Sorich MJ, Rodrigues AD, Rowland A. Guidance for Rifampin and Midazolam Dosing Protocols To Study Intestinal and Hepatic Cytochrome P450 (CYP) 3A4 Induction and De-induction. AAPS JOURNAL 2019; 21:78. [DOI: 10.1208/s12248-019-0341-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 05/15/2019] [Indexed: 12/24/2022]
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33
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Stevison F, Kosaka M, Kenny JR, Wong S, Hogarth C, Amory JK, Isoherranen N. Does In Vitro Cytochrome P450 Downregulation Translate to In Vivo Drug-Drug Interactions? Preclinical and Clinical Studies With 13-cis-Retinoic Acid. Clin Transl Sci 2019; 12:350-360. [PMID: 30681285 PMCID: PMC6617839 DOI: 10.1111/cts.12616] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 12/28/2018] [Indexed: 12/23/2022] Open
Abstract
All‐trans‐retinoic acid (atRA) downregulates cytochrome P450 (CYP)2D6 in several model systems. The aim of this study was to determine whether all active retinoids downregulate CYP2D6 and whether in vitro downregulation translates to in vivo drug–drug interactions (DDIs). The retinoids atRA, 13cisRA, and 4‐oxo‐13cisRA all decreased CYP2D6 mRNA in human hepatocytes in a concentration‐dependent manner. The in vitro data predicted ~ 50% decrease in CYP2D6 activity in humans after dosing with 13cisRA. However, the geometric mean area under plasma concentration‐time curve (AUC) ratio for dextromethorphan between treatment and control was 0.822, indicating a weak induction of dextromethorphan clearance following 13cisRA treatment. Similarly, in mice treatment with 4‐oxo‐13cisRA–induced mRNA expression of multiple mouse Cyp2d genes. In comparison, a weak induction of CYP3A4 in human hepatocytes translated to a weak in vivo induction of CYP3A4. These data suggest that in vitro CYP downregulation may not translate to in vivo DDIs, and better understanding of the mechanisms of CYP downregulation is needed.
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Affiliation(s)
- Faith Stevison
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA
| | - Mika Kosaka
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Jane R Kenny
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Susan Wong
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - Cathryn Hogarth
- The Center for Reproductive Biology, School of Molecular Biosciences, Washington State University, Pullman, Washington, USA
| | - John K Amory
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Nina Isoherranen
- Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA
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