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Wang M, Sasaki Y, Sakagami R, Minamikawa T, Tsuda M, Ueno R, Deguchi S, Negoro R, So K, Higuchi Y, Yokokawa R, Takayama K, Yamashita F. Perfluoropolyether-Based Gut-Liver-on-a-Chip for the Evaluation of First-Pass Metabolism and Oral Bioavailability of Drugs. ACS Biomater Sci Eng 2024; 10:4635-4644. [PMID: 38822812 DOI: 10.1021/acsbiomaterials.4c00605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2024]
Abstract
In the evolving field of drug discovery and development, multiorgans-on-a-chip and microphysiological systems are gaining popularity owing to their ability to emulate in vivo biological environments. Among the various gut-liver-on-a-chip systems for studying oral drug absorption, the chip developed in this study stands out with two distinct features: incorporation of perfluoropolyether (PFPE) to effectively mitigate drug sorption and a unique enterohepatic single-passage system, which simplifies the analysis of first-pass metabolism and oral bioavailability. By introducing a bolus drug injection into the liver compartment, hepatic extraction alone could be evaluated, further enhancing our estimation of intestinal availability. In a study on midazolam (MDZ), PFPE-based chips showed more than 20-times the appearance of intact MDZ in the liver compartment effluent compared to PDMS-based counterparts. Notably, saturation of hepatic metabolism at higher concentrations was confirmed by observations when the dose was reduced from 200 μM to 10 μM. This result was further emphasized when the metabolism was significantly inhibited by the coadministration of ketoconazole. Our chip, which is designed to minimize the dead volume between the gut and liver compartments, is adept at sensitively observing the saturation of metabolism and the effect of inhibitors. Using genome-edited CYP3A4/UGT1A1-expressing Caco-2 cells, the estimates for intestinal and hepatic availabilities were 0.96 and 0.82, respectively; these values are higher than the known human in vivo values. Although the metabolic activity in each compartment can be further improved, this gut-liver-on-a-chip can not only be used to evaluate oral bioavailability but also to carry out individual assessment of both intestinal and hepatic availability.
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Affiliation(s)
- Mengyang Wang
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Yuko Sasaki
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Rena Sakagami
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Tomotaka Minamikawa
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Masahiro Tsuda
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Ryohei Ueno
- Department of Micro Engineering, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, Japan
| | - Sayaka Deguchi
- Center for iPS Cell Research and Application, Kyoto University, Kyoto 606-8507, Japan
| | - Ryosuke Negoro
- Laboratory of Molecular Pharmacokinetics, College of Pharmaceutical Sciences, Ritsumeikan University, Shiga 525-8577, Japan
| | - Kanako So
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Yuriko Higuchi
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Ryuji Yokokawa
- Department of Micro Engineering, Graduate School of Engineering, Kyoto University, Kyoto 615-8540, Japan
| | - Kazuo Takayama
- Center for iPS Cell Research and Application, Kyoto University, Kyoto 606-8507, Japan
| | - Fumiyoshi Yamashita
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
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2
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Nilles J, Weiss J, Masin M, Tuffs C, Strowitzki MJ, Haefeli WE, Ruez S, Theile D. The differences in drug disposition gene induction by rifampicin and rifabutin are unlikely due to different effects on important pregnane X receptor (NR1I2) splice variants. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2024; 397:2485-2496. [PMID: 37851058 PMCID: PMC10933196 DOI: 10.1007/s00210-023-02768-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 10/02/2023] [Indexed: 10/19/2023]
Abstract
Rifampicin and rifabutin can activate the pregnane X receptor (PXR, NR1I2), thereby inducing pharmacokinetically important genes/proteins and reducing exposure to co-administered drugs. Because induction effects vary considerably between these antibiotics, differences could be due to unequal rifamycin-induced activation or tissue expression of the three major NR1I2 splice variants, PXR.1 (NM_003889), PXR.2 (NM_022002), and PXR.3 (NM_033013). Consequently, PXR activation (PXR reporter gene assays) and mRNA expression levels of total NR1I2, PXR.1, PXR.2, and PXR.3 were investigated by polymerase chain reaction in colon and liver samples from eleven surgical patients, in LS180 cells, and primary human hepatocytes. Compared to the colon, total NR1I2 mRNA expression was higher in the liver. Both tissues showed similar expression levels of PXR.1 and PXR.3, respectively. PXR.2 was not quantifiable in the colon samples. Rifampicin and rifabutin similarly enhanced PXR.1 and PXR.2 activity when transfected into LS180 cells, while PXR.3 could not be activated. In LS180 cells, rifampicin (10 μM) reduced total NR1I2 and PXR.3 expression 2-fold after 24 h, while rifabutin (10 μM) increased total NR1I2, PXR.1, PXR.2, and PXR.3 mRNA by approx. 50% after 96-h exposure. In primary human hepatocytes, rifampicin (10 μM) suppressed total NR1I2, PXR.1, and PXR.3 after 48-h exposure, and rifabutin (10 μM) had no significant impact on total NR1I2 or any of the splice variants studied. In conclusion, both antibiotics activated the studied PXR splice variants similarly but modified their expression differently. While rifampicin can suppress mRNA of PXR forms, rifabutin rather increases their expression levels.
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Affiliation(s)
- Julie Nilles
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
- Boehringer Ingelheim Pharma GmbH & Co, KG, Birkendorfer Str. 65, 88397, Biberach an der Riss, Germany
| | - Johanna Weiss
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
| | - Martin Masin
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
| | - Christopher Tuffs
- Departments of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Moritz J Strowitzki
- Departments of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany
| | - Walter E Haefeli
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany
| | - Stephanie Ruez
- Boehringer Ingelheim Pharma GmbH & Co, KG, Birkendorfer Str. 65, 88397, Biberach an der Riss, Germany
| | - Dirk Theile
- Department of Clinical Pharmacology and Pharmacoepidemiology, Heidelberg University Hospital, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.
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3
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Tsutsui H, Kato M, Kuramoto S, Yoshinari K. Quantitative prediction of CYP3A induction-mediated drug-drug interactions in clinical practice. Drug Metab Pharmacokinet 2024; 57:101010. [PMID: 39043066 DOI: 10.1016/j.dmpk.2024.101010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 03/04/2024] [Accepted: 03/04/2024] [Indexed: 07/25/2024]
Abstract
There have been no reports on the quantitative prediction of CYP3A induction-mediated decreases in AUC and Cmax for drug candidates identified as a "victims" of CYP3A induction. Our previous study separately evaluated the fold-induction of hepatic and intestinal CYP3A by known inducers using clinical induction data and revealed that we were able to quantitatively predict the AUC ratio (AUCR) of a few CYP3A substrates in the presence and absence of CYP3A inducers. In the present study, we investigate the predictability of AUCR and also Cmax ratio (CmaxR) in additional 54 clinical studies. The fraction metabolized by CYP3A (fm), the intestinal bioavailability (Fg), and the hepatic intrinsic clearance (CLint) of substrates were determined by the in vitro experiments as well as clinical data used for calculating AUCR and CmaxR. The result showed that 65-69% and 65-67% of predictions were within 2-fold of observed AUCR and CmaxR, respectively. A simulation using multiple parameter combinations suggested that the variability of fm and Fg within a certain range might have a minimal impact on the calculation output. These findings suggest that clinical AUCR and CmaxR of CYP3A substrates can be quantitatively predicted from the preclinical stage.
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Affiliation(s)
- Haruka Tsutsui
- Chugai Pharmaceutical Co., Ltd., 216 Totsukacho, Totsuka-ku, Yokohama-shi, Kanagawa, 244-8602, Japan; Department of Molecular Toxicology, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
| | - Motohiro Kato
- Research Institute of Pharmaceutical Sciences, Musashino University, 1-1-20, Shinmachi, Nishitokyo, Tokyo, 202-8585, Japan
| | - Shino Kuramoto
- Chugai Pharmaceutical Co., Ltd., 216 Totsukacho, Totsuka-ku, Yokohama-shi, Kanagawa, 244-8602, Japan
| | - Kouichi Yoshinari
- Department of Molecular Toxicology, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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Zhang M, Bai LB, Yau LF, Tong TT, Zhang W, Jiang ZH. Identification of Cannabidivarin Metabolites in Different Mouse Organs Using Ultra-Performance Liquid Chromatography Coupled to a Quadrupole Time-of-Flight Mass Spectrometer. Cannabis Cannabinoid Res 2024; 9:386-396. [PMID: 36342908 DOI: 10.1089/can.2022.0161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Background and Objectives: As a natural analog of cannabidiol (CBD), nonpsychoactive cannabidivarin (CBDV) has therapeutic potential. However, the precise metabolism of CBDV either in vivo or in vitro has not been fully understood. Objective and Experimental Approach: Therefore, mice were intragastrically administered CBDV, and metabolite-rich and potential target organs and tissues were collected and analyzed by ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The metabolic pathways of CBDV in mice were illustrated more comprehensively for the first time. Results: Twenty-one metabolites were found, all of which, except decarbonylated CBDV, were initially identified. Compared with CBD, the newly identified metabolic pathways were single dehydrogenation, combined decarbonylation and monohydroxylation, and glutathione conjugations of CBDV and its phase I metabolite. Conclusions: According to the very low response in plasma and the extremely high response in intestinal contents 1 h later after the administration, it was assumed that the oral bioavailability of CBDV was as poor as that of CBD, and the major forms to excrete were conjugates of glutathione and glucuronic acid. In contrast to CBDV, decarbonylated CBDV in the keto form and enol form had considerable responses in plasma and preferred to target fatty tissues and organs owing to their higher lipophilicity. Whether these forms can function as genuine active substances in vivo instead of CBDV is worthy of investigation. These results and supposes contribute notable information regarding the pharmacokinetics and pharmacodynamics of CBDV.
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Affiliation(s)
- Min Zhang
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
| | - Long-Bo Bai
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
| | - Lee-Fong Yau
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
| | - Tian-Tian Tong
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
| | - Wei Zhang
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
| | - Zhi-Hong Jiang
- State Key Laboratory of Quality Research in Chinese Medicines, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China
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An L, De Bruyn T, Pang J, Ubhayakar S, Salphati L, Zhang X, Liu L, Li R, Chan B, Dey A, Levy ES. Early Stage Preclinical Formulation Strategies to Alter the Pharmacokinetic Profile of Two Small Molecule Therapeutics. Pharmaceuticals (Basel) 2024; 17:179. [PMID: 38399394 PMCID: PMC10892288 DOI: 10.3390/ph17020179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/21/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
Early stage chemical development presents numerous challenges, and achieving a functional balance is a major hurdle, with many early compounds not meeting the clinical requirements for advancement benchmarks due to issues like poor oral bioavailability. There is a need to develop strategies for achieving the desired systemic concentration for these compounds. This will enable further evaluation of the biological response upon a compound-target interaction, providing deeper insight into the postulated biological pathways. Our study elucidates alternative drug delivery paradigms by comparing formulation strategies across oral (PO), intraperitoneal (IP), subcutaneous (SC), and intravenous (IV) routes. While each modality boasts its own set of merits and constraints, it is the drug's formulation that crucially influences its pharmacokinetic (PK) trajectory and the maintenance of its therapeutic levels. Our examination of model compounds G7883 and G6893 highlighted their distinct physio-chemical attributes. By harnessing varied formulation methods, we sought to fine-tune their PK profiles. PK studies showcased G7883's extended half-life using an SC oil formulation, resulting in a 4.5-fold and 2.5-fold enhancement compared with the IP and PO routes, respectively. In contrast, with G6893, we achieved a prolonged systemic coverage time above the desired target concentration through a different approach using an IV infusion pump. These outcomes underscore the need for tailored formulation strategies, which are dictated by the compound's innate properties, to reach the optimal in vivo systemic concentrations. Prioritizing formulation and delivery optimization early on is pivotal for effective systemic uptake, thereby facilitating a deeper understanding of biological pathways and expediting the overall clinical drug development timeline.
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Affiliation(s)
- Le An
- Small Molecules Pharmaceutics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA;
| | - Tom De Bruyn
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Jodie Pang
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Savita Ubhayakar
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Laurent Salphati
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Xing Zhang
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Liling Liu
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Ruina Li
- Drug Metabolism and Pharmacokinetics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA; (T.D.B.); (J.P.); (S.U.); (L.S.); (X.Z.); (L.L.); (R.L.)
| | - Bryan Chan
- Discovery Chemistry, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA;
| | - Anwesha Dey
- Discovery Oncology, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA;
| | - Elizabeth S. Levy
- Small Molecules Pharmaceutics, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA;
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Alorfi NM, Alqurashi RS, Algarni AS. Assessment of community pharmacists' knowledge about drug-drug interactions in Jeddah, Saudi Arabia. Front Pharmacol 2023; 14:1209318. [PMID: 37324452 PMCID: PMC10267452 DOI: 10.3389/fphar.2023.1209318] [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: 04/20/2023] [Accepted: 05/25/2023] [Indexed: 06/17/2023] Open
Abstract
Background: Drug-drug interactions (DDIs) have the potential to result in severe adverse drug events and profoundly affect patient outcomes. The pivotal role community pharmacists assume in recognizing and effectively managing these interactions necessitates a comprehensive understanding and heightened awareness of their implications. Such knowledge and awareness among community pharmacists are fundamental for ensuring the delivery of safe and efficacious care to patients. Aim: This study aimed to assess the knowledge of community pharmacists in Jeddah, Saudi Arabia, regarding drug-drug interactions (DDIs). Method: A cross-sectional survey was administered to a cohort of 147 community pharmacists through the utilization of a self-administered questionnaire. The questionnaire encompassed a comprehensive range of 30 multiple-choice questions, encompassing various facets pertaining to drug-drug interactions (DDIs). Results: A total of 147 community pharmacists working in Jeddah City, Saudi Arabia, completed the survey. The majority of them were male (89.1%, n = 131), and had bachelor's degrees in pharmacy. Results showed that the lowest correct response of DDIs was between Theophylline/Omeprazole, while the highest was between amoxicillin and acetaminophen. Results revealed that among the 28 drug pairs, only six pairs were determined correctly by most participants. The study found that majority of the studied community pharmacist could not determine the correct answer on drug-drug interaction knowledge, as also seen with the measured below half mean DDIs knowledge of 38.22 ± 22.0 (min = 0, max = 89.29, median = 35.71). Conclusion: The study highlights the need for ongoing training and education programs for community pharmacists in Saudi Arabia to enhance their knowledge and understanding of DDIs, ultimately leading to improved patient care and safety.
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Lee SJ, Joo SA, Kim H, Lee Y, Chung SJ, Chae YJ, Maeng HJ. Involvement of CYP3A4 and MDR1 in altered metabolism and transport of indinavir in 1,25(OH) 2D 3-treated Caco-2 cells. Eur J Pharm Sci 2023; 183:106396. [PMID: 36736464 DOI: 10.1016/j.ejps.2023.106396] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/02/2023] [Accepted: 01/30/2023] [Indexed: 02/02/2023]
Abstract
Altered drug concentrations may induce unexpected toxicity or treatment failure; thus, understanding the factors that alter the pharmacokinetic profiles of drugs is crucial for optimal disease treatment. Vitamin D receptor (VDR), a nuclear receptor, regulates the expression of cytochrome P450 3A4 (CYP3A4) and multidrug resistance protein 1 (MDR1), which are crucial determinants of drug pharmacokinetics. In this study, we investigated the effects of 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3], a VDR ligand, on the metabolism, transport, and pharmacokinetics of indinavir, a dual substrate of CYP3A4 and MDR1. 1,25(OH)2D3 treatment for three days upregulated the expression levels of CYP3A4 and MDR1 in Caco-2 cells and consequently led to an increase in the level of a metabolite formed via CYP3A4 (indinavir M6) and the efflux ratio of indinavir in transport study. The increase in the metabolic reaction was also confirmed through a metabolism assay performed using the lysate of 1,25(OH)2D3-treated Caco-2 cells. In the Ussing chamber study conducted with the rat intestine, 1,25(OH)2D3 treatment did not alter the transport of indinavir into the basolateral side but increased indinavir M6 formation. Similarly, plasma levels of the metabolite increased in 1,25(OH)2D3-treated rats; however, systemic exposure to indinavir led to insignificant alterations. Considering the overlapping substrate specificities for CYP3A4 and MDR1 and their significant roles in drug pharmacokinetics, VDR may play an important role in drug interactions of CYP3A4 and MDR1 substrates for accessing more effective and safe disease treatments.
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Affiliation(s)
- Su-Jin Lee
- College of Pharmacy, Gachon University, Incheon 21936, Korea
| | - Seul-A Joo
- College of Pharmacy, Gachon University, Incheon 21936, Korea
| | - Heejeong Kim
- Department of Pharmacology, Sungkyunkwan University School of Medicine, Suwon 16419, Korea
| | - Yunjong Lee
- Department of Pharmacology, Sungkyunkwan University School of Medicine, Suwon 16419, Korea
| | - Suk-Jae Chung
- College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Korea
| | - Yoon-Jee Chae
- College of Pharmacy and Research Institute of Pharmaceutical Sciences, Woosuk University, Wanju 55338, Korea.
| | - Han-Joo Maeng
- College of Pharmacy, Gachon University, Incheon 21936, Korea.
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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: 0] [Impact Index Per Article: 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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Vijaywargi G, Kollipara S, Ahmed T, Chachad S. Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward. Biopharm Drug Dispos 2022. [PMID: 36413625 DOI: 10.1002/bdd.2339] [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: 06/30/2022] [Revised: 10/07/2022] [Accepted: 11/04/2022] [Indexed: 11/23/2022]
Abstract
The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.
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Affiliation(s)
- Gautam Vijaywargi
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Hyderabad, Telangana, India
| | - Sivacharan Kollipara
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Hyderabad, Telangana, India
| | - Tausif Ahmed
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Hyderabad, Telangana, India
| | - Siddharth Chachad
- Biopharmaceutics Group, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Integrated Product Development Organization (IPDO), Hyderabad, Telangana, India
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10
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The impact of inflammation on the expression of drug transporters and metabolic enzymes in colonic tissue from ulcerative colitis patients. Int J Pharm 2022; 628:122282. [DOI: 10.1016/j.ijpharm.2022.122282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 10/04/2022] [Accepted: 10/07/2022] [Indexed: 12/08/2022]
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11
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Study on the Absorption of Arsenic Species in Realgar Based on the Form and Valence. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:1026672. [PMID: 36051493 PMCID: PMC9427252 DOI: 10.1155/2022/1026672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 08/01/2022] [Indexed: 11/29/2022]
Abstract
At present, several experiments have been carried out to study the changes in total arsenic content of realgar and its prescription, but few researches on its form and valence. We evaluated the change in arsenic species concentration in realgar from the perspective of absorption by using an in vitro dissolution study, an in vivo unidirectional intestinal perfusion study, transmembrane transport in Caco-2 cells, and a pharmacokinetic study in rats. In the gastrointestinal tract, arsenic species are mainly present inorganic forms of AsIII and AsV. The cumulative dissolution rates of soluble arsenic in 4 h artificial gastric fluid and 8 h artificial intestinal fluid were 21.99% and 59.20%, respectively. The Papp values of soluble arsenic in realgar in the duodenum, jejunum, and ileum of rats were 5.4 × 10−3, 6.1 × 10−3 and 5.8 × 10−3 cm/min, respectively. In the process of small intestine perfusion, the AsIII of realgar was partially converted into AsV in the duodenum and jejunum. As the transport time increased, the transmembrane transport rate and Papp value of soluble arsenic in realgar were increased in Caco-2 cells, and it also suggested that arsenic species may be passively transported across the Caco-2 cell monolayer. The Cmax and AUC (0-24) of AsIII, AsV, and DMA in plasma of realgar were 41.26 ng L−1/343.977 ng h mL−1, 21.626 ng L−1/47.310 ng h mL−1, and 2.372 ng L−1/30.429 ng h mL−1, respectively. Tmax and MRT (0-∞) of AsIII, AsV, and DMA were 2.571 h/9.649 h, 0.393 h/2.790 h, and 3.143 h/23.145 h, respectively. It is hoped to provide a basis for clarifying the arsenic species in realgar.
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12
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Volpe DA, Joshi A, Arya V. Do differences in cell lines and methods used for calculation of IC 50 values influence categorisation of drugs as P-glycoprotein substrates and inhibitors? Xenobiotica 2022; 52:751-757. [PMID: 36218364 DOI: 10.1080/00498254.2022.2135040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In vitro bidirectional assays are employed to determine whether a drug is a substrate and/or inhibitor of P-glycoprotein (P-gp) transport. Differences between cell lines and calculation methods can lead to variations in the determination of efflux ratios (ER) and IC50 values used to classify a drug as a P-gp substrate and inhibitor, respectively.Information was collected from the literature on ER and IC50 values with digoxin as the probe substrate using different cell lines and inhibition calculation methods. Predictive performance was evaluated by comparing [Igut]/IC50 ratios versus reported in vivo results.For known P-gp substrates, 50% of the drugs had their highest ER value in MDCK-MDR1 cells while 81% had their lowest ER value in Caco-2 cells. For 30 drugs with inhibition data, lower mean IC50 values were often observed with the Caco-2 cells and calculations based on ER. Based on the cut-off criteria of [Igut]/IC50 ≥ 10, there were no significant differences in positive or negative predictive values based on either cell line or calculation method for the drugs.Within this limited dataset, differences between cell lines or IC50 calculation methods do not seem to impact the prediction of in vivo P-gp inhibitor classification.
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Affiliation(s)
- Donna A Volpe
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - Abhay Joshi
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
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13
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Noh K, Chow ECY, Quach HP, Groothuis GMM, Tirona RG, Pang KS. Significance of the Vitamin D Receptor on Crosstalk with Nuclear Receptors and Regulation of Enzymes and Transporters. AAPS J 2022; 24:71. [PMID: 35650371 DOI: 10.1208/s12248-022-00719-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/16/2022] [Indexed: 11/30/2022] Open
Abstract
The vitamin D receptor (VDR), in addition to other nuclear receptors, the pregnane X receptor (PXR) and constitutive androstane receptor (CAR), is involved in the regulation of enzymes, transporters and receptors, and therefore intimately affects drug disposition, tissue health, and the handling of endogenous and exogenous compounds. This review examines the role of 1α,25-dihydroxyvitamin D3 or calcitriol, the natural VDR ligand, on activation of the VDR and its crosstalk with other nuclear receptors towards the regulation of enzymes and transporters, notably many of the cytochrome P450s including CYP3A4 and sulfotransferase 2A1 (SULT2A1) as well as cholesterol 7α-hydroxylase (CYP7A1). Moreover, the VDR upregulates the intestinal channel, TRPV6, for calcium absorption, LDL receptor-related protein 1 (LRP1) and receptor for advanced glycation end products (RAGE) in brain for β-amyloid peptide efflux and influx, the sodium phosphate transporters (NaPi), the apical sodium-dependent bile acid transporter (ASBT) and organic solute transporters (OSTα-OSTβ) for bile acid absorption and efflux, respectively, the renal organic anion transporter 3 (OAT3) and several of the ATP-binding cassette protein transporters-the multidrug resistance protein 1 (MDR1) and the multidrug resistance-associated proteins (MRPs). Hence, the role of the VDR is increasingly being recognized for its therapeutic potential and pharmacologic activity, giving rise to drug-drug interactions (DDI). Therapeutically, ligand-activated VDR shows anti-inflammatory effects towards the suppression of inflammatory mediators, improves cognition by upregulating amyloid-beta (Aβ) peptide clearance in brain, and maintains phosphate, calcium, and parathyroid hormone (PTH) balance and kidney function and bone health, demonstrating the crucial roles of the VDR in disease progression and treatment of diseases.
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Affiliation(s)
- Keumhan Noh
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada.,Drug Metabolism and Pharmacokinetics, Biogen, 225 Binney Street, Cambridge, Massachusetts, 02142, USA
| | - Edwin C Y Chow
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada.,Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Holly P Quach
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada
| | - Geny M M Groothuis
- Pharmacokinetics, Toxicology and Targeting, Department of Pharmacy, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Rommel G Tirona
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, N6A 5C1, Canada
| | - K Sandy Pang
- Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada.
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14
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Ning J, Tian Z, Wang J, Wang B, Tian X, Yu Z, Huo X, Feng L, Cui J, James TD, Ma X. Rational Design of a Two‐Photon Fluorescent Probe for Human Cytochrome P450 3A and the Visualization of Mechanism‐Based Inactivation. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202113191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Jing Ning
- Second Affiliated Hospital of Dalian Medical University Dalian 116023 China
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
| | - Zhenhao Tian
- School of Life Sciences Northwestern Polytechnical University Xi'an 710072 China
| | - Jiayue Wang
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
- Department of Pharmacy Peking University Shenzhen Hospital Shenzhen 518036 China
| | - Bo Wang
- School of Medicine & Holistic Integrative Medicine Nanjing University of Chinese Medicine Nanjing China
| | - Xiangge Tian
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
| | - Zhenlong Yu
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
| | - Xiaokui Huo
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
| | - Lei Feng
- Second Affiliated Hospital of Dalian Medical University Dalian 116023 China
- School of Chemistry and Chemical Engineering Henan Normal University Xinxiang 453007 China
| | - Jingnan Cui
- State Key Laboratory of Fine Chemicals Dalian University of Technology Dalian 116024 China
| | - Tony D. James
- School of Chemistry and Chemical Engineering Henan Normal University Xinxiang 453007 China
- Department of Chemistry University of Bath Bath BA2 7AY United Kingdom
| | - Xiaochi Ma
- Second Affiliated Hospital of Dalian Medical University Dalian 116023 China
- College of Integrative Medicine College of Pharmacy Dalian Medical University Dalian 116044 China
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15
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Ning J, Tian Z, Wang J, Wang B, Tian X, Yu Z, Huo X, Feng L, Cui J, James TD, Ma X. Rational Design of a Two-Photon Fluorescent Probe for Human Cytochrome P450 3A and the Visualization of Mechanism-Based Inactivation. Angew Chem Int Ed Engl 2022; 61:e202113191. [PMID: 34851011 DOI: 10.1002/anie.202113191] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Indexed: 12/18/2022]
Abstract
Mechanism-based inactivation (MBI) can mediate adverse reactions and hepatotoxicity from drugs, which is a result of their conversion into highly reactive metabolites catalyzed by enzymes such as cytochrome P450 3A (CYP3A). In the present research, we optimized the key interaction domain of the fluorophore with the target protein to develop a two-photon fluorescent probe for CYP3A that is involved in the metabolism of more than half of all clinical drugs. The developed BN-1 probe exhibited appropriate selectivity and sensitivity for the semi-quantitative detection and imaging of endogenous CYP3A activity in various living systems, thereby providing a high-throughput screening system enabling evaluation of MBI-associated hepatotoxicity by CYP3A. Using BN-1 as a fluorescent molecular tool facilitates the efficient discovery and characterization of CYP3A-induced MBI in natural systems.
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Affiliation(s)
- Jing Ning
- Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
| | - Zhenhao Tian
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Jiayue Wang
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
- Department of Pharmacy, Peking University Shenzhen Hospital, Shenzhen, 518036, China
| | - Bo Wang
- School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xiangge Tian
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
| | - Zhenlong Yu
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
| | - Xiaokui Huo
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
| | - Lei Feng
- Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China
- School of Chemistry and Chemical Engineering, Henan Normal University, Xinxiang, 453007, China
| | - Jingnan Cui
- State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian, 116024, China
| | - Tony D James
- School of Chemistry and Chemical Engineering, Henan Normal University, Xinxiang, 453007, China
- Department of Chemistry, University of Bath, Bath, BA2 7AY, United Kingdom
| | - Xiaochi Ma
- Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China
- College of Integrative Medicine, College of Pharmacy, Dalian Medical University, Dalian, 116044, China
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16
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Cleary Y, Gertz M, Grimsey P, Günther A, Heinig K, Ogungbenro K, Aarons L, Galetin A, Kletzl H. Model-Based Drug-Drug Interaction Extrapolation Strategy From Adults to Children: Risdiplam in Pediatric Patients With Spinal Muscular Atrophy. Clin Pharmacol Ther 2021; 110:1547-1557. [PMID: 34347881 PMCID: PMC9291816 DOI: 10.1002/cpt.2384] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 07/14/2021] [Indexed: 12/14/2022]
Abstract
Risdiplam (Evrysdi) improves motor neuron function in patients with spinal muscular atrophy (SMA) and has been approved for the treatment of patients ≥2 months old. Risdiplam exhibits time‐dependent inhibition of cytochrome P450 (CYP) 3A in vitro. While many pediatric patients receive risdiplam, a drug–drug interaction (DDI) study in pediatric patients with SMA was not feasible. Therefore, a novel physiologically‐based pharmacokinetic (PBPK) model‐based strategy was proposed to extrapolate DDI risk from healthy adults to children with SMA in an iterative manner. A clinical DDI study was performed in healthy adults at relevant risdiplam exposures observed in children. Risdiplam caused an 1.11‐fold increase in the ratio of midazolam area under the curve with and without risdiplam (AUCR)), suggesting an 18‐fold lower in vivo CYP3A inactivation constant compared with the in vitro value. A pediatric PBPK model for risdiplam was validated with independent data and combined with a validated midazolam pediatric PBPK model to extrapolate DDI from adults to pediatric patients with SMA. The impact of selected intestinal and hepatic CYP3A ontogenies on the DDI susceptibility in children relative to adults was investigated. The PBPK analysis suggests that primary CYP3A inhibition by risdiplam occurs in the intestine rather than the liver. The PBPK‐predicted risdiplam CYP3A inhibition risk in pediatric patients with SMA aged 2 months–18 years was negligible (midazolam AUCR of 1.09–1.18) and included in the US prescribing information of risdiplam. Comprehensive evaluation of the sensitivity of predicted CYP3A DDI on selected intestinal and hepatic CYP3A ontogeny functions, together with PBPK model‐based strategy proposed here, aim to guide and facilitate DDI extrapolations in pediatric populations.
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Affiliation(s)
- Yumi Cleary
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland.,Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Michael Gertz
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland
| | - Paul Grimsey
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Welwyn, UK
| | - Andreas Günther
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland
| | - Katja Heinig
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland
| | - Kayode Ogungbenro
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Leon Aarons
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | - Heidemarie Kletzl
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland
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17
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Tseng E, Eng H, Lin J, Cerny MA, Tess DA, Goosen TC, Obach RS. Static and Dynamic Projections of Drug-Drug Interactions Caused by Cytochrome P450 3A Time-Dependent Inhibitors Measured in Human Liver Microsomes and Hepatocytes. Drug Metab Dispos 2021; 49:947-960. [PMID: 34326140 DOI: 10.1124/dmd.121.000497] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/01/2021] [Indexed: 11/22/2022] Open
Abstract
Cytochrome P450 3A (CYP3A) is a frequent target for time-dependent inhibition (TDI) that can give rise to drug-drug interactions (DDI). Yet many drugs that exhibit in vitro TDI for CYP3A, do not result in DDI. Twenty-three drugs with published clinical DDI were evaluated for CYP3A TDI in human liver microsomes (HLM) and hepatocytes (HHEP), and these data were utilized in static and dynamic models for projecting DDI caused by inactivation of CYP3A in both liver and intestine. TDI parameters measured in HHEP, particularly kinact, were generally lower than those measured in HLM. In static models, the use of average unbound organ exit concentrations offered the most accurate projections of DDI with geometric mean fold errors of 2.2 and 1.7 for HLM and HHEP, respectively. Use of maximum organ entry concentrations yielded marked overestimates of DDI. When evaluated in a binary fashion (i.e. projection of DDI of 1.25-fold or greater), data from HLM offered the greatest sensitivity (100%) and specificity (42%) and yielded no missed DDI when average unbound organ exit concentrations were used. In dynamic physiologically-based pharmacokinetic modeling, accurate projections of DDI were obtained with geometric mean fold errors of 1.7 and 1.6 for HLM and HHEP, respectively. Sensitivity and specificity were 100% and 67% when using TDI data generated in HLM and Simcyp modeling. Overall, DDI caused by CYP3A-mediated TDI can be reliably projected using dynamic or static models. For static models, average organ unbound exit concentrations must be used as input values otherwise DDI will be markedly overestimated. Significance Statement CYP3A time-dependent inhibitors are important in design and development of new drugs. The prevalence of CYP3A TDI is high among newly synthesized drug candidates and understanding the potential need for running clinical DDI studies is essential during drug development. Ability to reliably predict DDI caused by CYP3A TDI has been difficult to achieve. We report a thorough evaluation of CYP3A TDI and demonstrate that DDI can be predicted when using appropriate models and input parameters generated in HLM or HHEP.
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Affiliation(s)
- Elaine Tseng
- Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, United States
| | - Heather Eng
- Pharmacokinetics, Dynamics, and Metabolism, Pfizer Global Research and Development, United States
| | | | | | | | - Theunis C Goosen
- Pharmacokinetics, Dynamics & Metabolism, Pfizer, Inc, United States
| | - R Scott Obach
- Groton Laboratories, Pfizer Global Research and Development, United States
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18
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Wang Z, Wang X, Wang Z, Jia Y, Feng Y, Jiang L, Xia Y, Cao J, Liu Y. In vitro inhibition of human UDP-glucuronosyltransferase (UGT) 1A1 by osimertinib, and prediction of in vivo drug-drug interactions. Toxicol Lett 2021; 348:10-17. [PMID: 34044055 DOI: 10.1016/j.toxlet.2021.05.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 05/18/2021] [Accepted: 05/21/2021] [Indexed: 11/25/2022]
Abstract
Osimertinib is the only third-generation epidermal growth factor receptor tyrosine-kinase inhibitor (EGFR-TKI) approved by Food and Drug Administration (FDA). This study aimed to know the inhibitory effect of osimertinib on human UDP-glucosyltransferases (UGTs) and human liver microsomes (HLMs), as well as to identify its potential to cause drug-drug interaction (DDI) arising from the modulation of UGT activity. High inhibitory effect of osimertinib was shown towards UGT1A1, 1A3, 1A6, 1A7, 1A8, 1A10, 2B7 and 2B15. Especially, osimertinib exhibited competitive inhibition against UGT1A1 with a Ki,u of 0.87 ± 0.12 μM. It also noncompetitively inhibited SN-38 glucuronidation in pooled HLMs with a Ki,u of 3.32 ± 0.25 μM. Results from quantitative prediction study indicated that osimertinib administered at 80 mg/day may result in a 4.83 % increase in the AUC of drugs mainly metabolized by UGT1A1, implying low risk of DDI via liver metabolism. However, the ratios of [I]gut/Ki,u are much higher than 11 in HLMs and recombinant UGT1A1, indicating a risk for interaction in intestine. The effects of osimertinib on intestinal UGT should be paid more attention on to avoid unnecessary clinical DDI risks.
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Affiliation(s)
- Zhe Wang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Xiaoyu Wang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Zhen Wang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Yaqin Jia
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Yuyi Feng
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Lili Jiang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Yangliu Xia
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China
| | - Jun Cao
- Department of Occupational and Environmental Health, Dalian Medical University, Dalian, 116044, China.
| | - Yong Liu
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin, 124221, China.
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19
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Tsutsui H, Kuramoto S, Ozeki K. Evaluation of Methods to Assess CYP3A Induction Risk in Clinical Practice Using in Vitro Induction Parameters. Biol Pharm Bull 2021; 44:338-349. [PMID: 33642543 DOI: 10.1248/bpb.b20-00578] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Established guidelines have recommended a number of methods based on in vitro data to assess the CYP3A induction risk of new chemical entities in clinical practice. In this study, we evaluated the predictability of various assessment methods. We collected in vitro parameters from a variety of literature that includes data on 19 batches of hepatocytes. Clinical CYP3A induction was predicted using 3 direct approaches-the fold-change, basic model, and mechanistic static models-as well as 5 correlation approaches, including the relative induction score (RIS) and the relative factor (RF) method. These predictions were then compared with data from 30 clinical inductions. Collected in vitro parameters varied greatly between hepatocyte batches. Direct assessment methods using fixed cut-off values provided a lot of false predictions due to hepatocyte variability, which can overlook induction risk or lead to needless clinical drug-drug interaction (DDI) studies. On the other hand, correlation methods with the cut-off values set for each batch of hepatocytes accurately predicted the induction risk. Among these, the AUCu/inducer concentrations for half the maximum induction (EC50) and the RF methods which use the area under the curve (AUC) of the unbound inducers for calculating induction potential showed an especially good correlation with clinical induction. Correlation methods were better at predicting clinical induction risk than the other methods, regardless of hepatocyte variability. The AUCu/EC50 and the RF methods in particular had a small number of false predictions, and can therefore be used to assess induction risk along with the other correlation methods recommended in guidelines.
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20
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Li Y, Qin J, Wu H, Xu Y, Zhang L, Su K, Cui Y, Wang H. In vitro inhibitory effect of lysionotin on the activity of cytochrome P450 enzymes. PHARMACEUTICAL BIOLOGY 2020; 58:695-700. [PMID: 32673137 PMCID: PMC7470033 DOI: 10.1080/13880209.2020.1787468] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
CONTEXT Lysionotin, a major extraction of Lysionotus pauciflorus Maxim (Gesneriaceae), has a variety of pharmacological properties commonly used in the treatment of lung disease. A study of lysionotin on the activity of human liver cytochrome P450 (CYP) enzymes can provide guidance on the clinical application of lysionotin. OBJECTIVE This study investigated the interaction between lysionotin and CYPs. MATERIAL AND METHOD The effects of 100 μM lysionotin on eight human liver CYP isoforms (i.e., 1A2, 3A4, 2A6, 2E1, 2D6, 2C9, 2C19 and 2C8) were investigated in vitro using human liver microsomes (HLMs) with specific inhibitor as positive control and untreated HLMs as control. Meanwhile, the enzyme kinetic parameters were calculated. A time-dependent study was performed with a time interval of 5 min in 30 min. RESULTS Lysionotin was found to inhibit the activity of CYP3A4, 2C19, and 2C8, with IC50 values of 13.85, 24.95, and 30.05 μM, respectively. The inhibition of CYP3A4 was performed in a non-competitive manner with the Ki value of 6.83 μM, while the inhibition of CYP2C19 and 2C8 was performed in a competitive manner with Ki values of 12.41 and 14.51 μM. Moreover, it was found that the inhibition of CYP3A4 was time-dependent with K I/K inact value of 6.618/0.048 min/μM. Discussion and conclusions: The in vitro inhibitory effect of lysionotin on the activity of CYP3A4, 2C19, and 2C8 indicated potential drug interactions between lysionotin and drugs metabolised by CYP3A4, 2C19, and 2C8. Further in vivo experiments are needed to assess the potential interactions.
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Affiliation(s)
- Yang Li
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
- Department of Neurology, Zibo No. 4 People’s Hospital, Zibo, China
| | - Jing Qin
- Department of Laboratory, Yidu Central Hospital of Weifang, Weifang, China
| | - Hong Wu
- Department of Oncology, Binzhou Medical University Hospital, Binzhou, China
| | - Yongmei Xu
- Department of Cardiology, Shanxian Central Hospital, Heze, China
| | - Li Zhang
- Department of Pharmacy, Shanxian Central Hospital, Heze, China
| | - Keren Su
- Department of Pharmacy, Shanxian Central Hospital, Heze, China
| | - Ying Cui
- Department of Hematology and Nephrology, Shanxian Central Hospital, Heze, China
- CONTACT Ying Cui Department of Hematology and Nephrology, Shanxian Central Hospital, No. 1, Wenhua Road, Heze274300, Shandong, China
| | - Haiping Wang
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
- Haiping Wang Department of Neurology, The Affiliated Hospital of Qingdao University, No. 16, Jiangsu Road, Qingdao266000, Shandong, China
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21
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Tanna RS, Tian DD, Cech NB, Oberlies NH, Rettie AE, Thummel KE, Paine MF. Refined Prediction of Pharmacokinetic Kratom-Drug Interactions: Time-Dependent Inhibition Considerations. J Pharmacol Exp Ther 2020; 376:64-73. [PMID: 33093187 DOI: 10.1124/jpet.120.000270] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 10/08/2020] [Indexed: 02/06/2023] Open
Abstract
Preparations from the leaves of the kratom plant (Mitragyna speciosa) are consumed for their opioid-like effects. Several deaths have been associated with kratom used concomitantly with some drugs. Pharmacokinetic interactions are potential underlying mechanisms of these fatalities. Accumulating in vitro evidence has demonstrated select kratom alkaloids, including the abundant indole alkaloid mitragynine, as reversible inhibitors of several cytochromes P450 (CYPs). The objective of this work was to refine the mechanistic understanding of potential kratom-drug interactions by considering both reversible and time-dependent inhibition (TDI) of CYPs in the liver and intestine. Mitragynine was tested against CYP2C9 (diclofenac 4'-hydroxylation), CYP2D6 (dextromethorphan O-demethylation), and CYP3A (midazolam 1'-hydroxylation) activities in human liver microsomes (HLMs) and CYP3A activity in human intestinal microsomes (HIMs). Comparing the absence to presence of NADPH during preincubation of mitragynine with HLMs or HIMs, an ∼7-fold leftward shift in IC50 (∼20 to 3 μM) toward CYP3A resulted, prompting determination of TDI parameters (HLMs: K I , 4.1 ± 0.9 μM; k inact , 0.068 ± 0.01 min-1; HIMs: K I , 4.2 ± 2.5 μM; k inact , 0.079 ± 0.02 min-1). Mitragynine caused no leftward shift in IC50 toward CYP2C9 (∼40 μM) and CYP2D6 (∼1 μM) but was a strong competitive inhibitor of CYP2D6 (K i , 1.17 ± 0.07 μM). Using a recommended mechanistic static model, mitragynine (2-g kratom dose) was predicted to increase dextromethorphan and midazolam area under the plasma concentration-time curve by 1.06- and 5.69-fold, respectively. The predicted midazolam area under the plasma concentration-time curve ratio exceeded the recommended cutoff (1.25), which would have been missed if TDI was not considered. SIGNIFICANCE STATEMENT: Kratom, a botanical natural product increasingly consumed for its opioid-like effects, may precipitate potentially serious pharmacokinetic interactions with drugs. The abundant kratom indole alkaloid mitragynine was shown to be a time-dependent inhibitor of hepatic and intestinal cytochrome P450 3A activity. A mechanistic static model predicted mitragynine to increase systemic exposure to the probe drug substrate midazolam by 5.7-fold, necessitating further evaluation via dynamic models and clinical assessment to advance the understanding of consumer safety associated with kratom use.
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Affiliation(s)
- Rakshit S Tanna
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Dan-Dan Tian
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Nadja B Cech
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Nicholas H Oberlies
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Allan E Rettie
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Kenneth E Thummel
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
| | - Mary F Paine
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington (R.S.T., D.-D.T., M.F.P.); Department of Chemistry and Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina (N.B.C., N.H.O.); Departments of Medicinal Chemistry (A.E.R.) and Pharmaceutics (K.E.T.), School of Pharmacy, University of Washington, Seattle, Washington; and Center of Excellence for Natural Product Drug Interaction Research, Spokane, Washington (N.B.C., N.H.O., A.E.R., K.E.T., M.F.P.)
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22
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Li AP. In Vitro Human Cell–Based Experimental Models for the Evaluation of Enteric Metabolism and Drug Interaction Potential of Drugs and Natural Products. Drug Metab Dispos 2020; 48:980-992. [DOI: 10.1124/dmd.120.000053] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/18/2020] [Indexed: 12/14/2022] Open
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Posada MM, Morse BL, Turner PK, Kulanthaivel P, Hall SD, Dickinson GL. Predicting Clinical Effects of CYP3A4 Modulators on Abemaciclib and Active Metabolites Exposure Using Physiologically Based Pharmacokinetic Modeling. J Clin Pharmacol 2020; 60:915-930. [PMID: 32080863 PMCID: PMC7318171 DOI: 10.1002/jcph.1584] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 01/01/2020] [Indexed: 11/09/2022]
Abstract
Abemaciclib, a selective inhibitor of cyclin‐dependent kinases 4 and 6, is metabolized mainly by cytochrome P450 (CYP)3A4. Clinical studies were performed to assess the impact of strong inhibitor (clarithromycin) and inducer (rifampin) on the exposure of abemaciclib and active metabolites. A physiologically based pharmacokinetic (PBPK) model incorporating the metabolites was developed to predict the effect of other strong and moderate CYP3A4 inhibitors and inducers. Clarithromycin increased the area under the plasma concentration‐time curve (AUC) of abemaciclib and potency‐adjusted unbound active species 3.4‐fold and 2.5‐fold, respectively. Rifampin decreased corresponding exposures 95% and 77%, respectively. These changes influenced the fraction metabolized via CYP3A4 in the model. An absolute bioavailability study informed the hepatic and gastric availability. In vitro data and a human radiolabel study determined the fraction and rate of formation of the active metabolites as well as absorption‐related parameters. The predicted AUC ratios of potency‐adjusted unbound active species with rifampin and clarithromycin were within 0.7‐ and 1.25‐fold of those observed. The PBPK model predicted 3.78‐ and 7.15‐fold increases in the AUC of the potency‐adjusted unbound active species with strong CYP3A4 inhibitors itraconazole and ketoconazole, respectively; and 1.62‐ and 2.37‐fold increases with the concomitant use of moderate CYP3A4 inhibitors verapamil and diltiazem, respectively. The model predicted modafinil, bosentan, and efavirenz would decrease the AUC of the potency‐adjusted unbound active species by 29%, 42%, and 52%, respectively. The current PBPK model, which considers changes in unbound potency‐adjusted active species, can be used to inform dosing recommendations when abemaciclib is coadministered with CYP3A4 perpetrators.
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Yadav J, Paragas E, Korzekwa K, Nagar S. Time-dependent enzyme inactivation: Numerical analyses of in vitro data and prediction of drug-drug interactions. Pharmacol Ther 2020; 206:107449. [PMID: 31836452 PMCID: PMC6995442 DOI: 10.1016/j.pharmthera.2019.107449] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Cytochrome P450 (CYP) enzyme kinetics often do not conform to Michaelis-Menten assumptions, and time-dependent inactivation (TDI) of CYPs displays complexities such as multiple substrate binding, partial inactivation, quasi-irreversible inactivation, and sequential metabolism. Additionally, in vitro experimental issues such as lipid partitioning, enzyme concentrations, and inactivator depletion can further complicate the parameterization of in vitro TDI. The traditional replot method used to analyze in vitro TDI datasets is unable to handle complexities in CYP kinetics, and numerical approaches using ordinary differential equations of the kinetic schemes offer several advantages. Improvement in the parameterization of CYP in vitro kinetics has the potential to improve prediction of clinical drug-drug interactions (DDIs). This manuscript discusses various complexities in TDI kinetics of CYPs, and numerical approaches to model these complexities. The extrapolation of CYP in vitro TDI parameters to predict in vivo DDIs with static and dynamic modeling is discussed, along with a discussion on current gaps in knowledge and future directions to improve the prediction of DDI with in vitro data for CYP catalyzed drug metabolism.
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Affiliation(s)
- Jaydeep Yadav
- Amgen Inc., 360 Binney Street, Cambridge, MA 02142, United States; Department of Pharmaceutical Sciences, Temple University, Philadelphia, PA 19140, United States
| | - Erickson Paragas
- Department of Pharmaceutical Sciences, Temple University, Philadelphia, PA 19140, United States
| | - Ken Korzekwa
- Department of Pharmaceutical Sciences, Temple University, Philadelphia, PA 19140, United States
| | - Swati Nagar
- Department of Pharmaceutical Sciences, Temple University, Philadelphia, PA 19140, United States.
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25
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Yamada M, Inoue SI, Sugiyama D, Nishiya Y, Ishizuka T, Watanabe A, Watanabe K, Yamashita S, Watanabe N. Critical Impact of Drug-Drug Interactions via Intestinal CYP3A in the Risk Assessment of Weak Perpetrators Using Physiologically Based Pharmacokinetic Models. Drug Metab Dispos 2020; 48:288-296. [PMID: 31996361 DOI: 10.1124/dmd.119.089599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 01/18/2020] [Indexed: 12/11/2022] Open
Abstract
A great deal of effort has been being made to improve the accuracy of the prediction of drug-drug interactions (DDIs). In this study, we addressed CYP3A-mediated weak DDIs, in which a relatively high false prediction rate was pointed out. We selected 17 orally administered drugs that have been reported to alter area under the curve (AUC) of midazolam, a typical CYP3A substrate, 0.84-1.47 times. For weak CYP3A perpetrators, the predicted AUC ratio mainly depends on intestinal DDIs rather than hepatic DDIs because the drug concentration in the enterocytes is higher. Thus, DDI prediction using simulated concentration-time profiles in each segment of the digestive tract was made by physiologically based pharmacokinetic (PBPK) modeling software GastroPlus. Although mechanistic static models tend to overestimate the risk to ensure the safety of patients, some underestimation is reported about PBPK modeling. Our in vitro studies revealed that 16 out of 17 tested drugs exhibited time-dependent inhibition (TDI) of CYP3A, and the subsequent DDI simulation that ignored these TDIs provided false-negative results. This is considered to be the cause of past underestimation. Inclusion of the DDI parameters of all the known DDI mechanisms, reversible inhibition, TDI, and induction, which have opposite effects on midazolam AUC, to PBPK model was successful in improving predictability of the DDI without increasing false-negative prediction as trade-off. This comprehensive model-based analysis suggests the importance of the intestine in assessing weak DDIs via CYP3A and the usefulness of PBPK in predicting intestinal DDIs. SIGNIFICANCE STATEMENT: Although drug-drug interaction (DDI) prediction has been extensively performed previously, the accuracy of prediction for weak interactions via CYP3A has not been thoroughly investigated. In this study, we simulate DDIs considering drug concentration-time profile in the enterocytes and discuss the importance and the predictability of intestinal DDIs about weak CYP3A perpetrators.
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Affiliation(s)
- Makiko Yamada
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Shin-Ichi Inoue
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Daisuke Sugiyama
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Yumi Nishiya
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Tomoko Ishizuka
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Akiko Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Kengo Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Shinji Yamashita
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Nobuaki Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
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26
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Tres F, Posada MM, Hall SD, Mohutsky MA, Taylor LS. The Effect of Promiscuous Aggregation on in Vitro Drug Metabolism Assays. Pharm Res 2019; 36:170. [PMID: 31654151 DOI: 10.1007/s11095-019-2713-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 10/09/2019] [Indexed: 11/26/2022]
Abstract
PURPOSE Many bioactive molecules show a type of solution phase behavior, termed promiscuous aggregation, whereby at micromolar concentrations, colloidal drug-rich aggregates are formed in aqueous solution. These aggregates are known to be a major cause of false positives and false negatives in select enzymatic high-throughput screening assays. The goal of this study was to investigate the impact of drug-rich aggregates on in vitro drug screening metabolism assays. METHODS Cilnidipine was selected as an aggregate former and its impact on drug metabolism was evaluated against rCYP2D6, rCYP1A2, rCYP2C9 and human liver microsomes. RESULTS The cilnidipine aggregates were shown to non-specifically inhibit multiple cytochrome P450 enzymes with an IC50 comparable with the IC50 of potent model inhibitors. CONCLUSIONS This newly demonstrated mode of "promiscuous inhibition" is of great importance as it can lead to false positives during drug metabolism evaluations and thus it needs to be considered in the future to better predict in vivo drug-drug interactions.
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Affiliation(s)
- Francesco Tres
- Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University, West Lafayette, Indiana, 47907, USA
| | - Maria M Posada
- Drug Disposition, Lilly Research Laboratories, Eli Lilly and Co., Indianapolis, Indiana, 46285, USA
| | - Stephen D Hall
- Drug Disposition, Lilly Research Laboratories, Eli Lilly and Co., Indianapolis, Indiana, 46285, USA
| | - Michael A Mohutsky
- Drug Disposition, Lilly Research Laboratories, Eli Lilly and Co., Indianapolis, Indiana, 46285, USA
| | - Lynne S Taylor
- Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University, West Lafayette, Indiana, 47907, USA.
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Prediction of pharmacokinetic drug-drug interactions causing atorvastatin-induced rhabdomyolysis using physiologically based pharmacokinetic modelling. Biomed Pharmacother 2019; 119:109416. [PMID: 31518878 DOI: 10.1016/j.biopha.2019.109416] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 08/29/2019] [Accepted: 08/29/2019] [Indexed: 12/12/2022] Open
Abstract
Atorvastatin and its lactone form metabolite are reported to be associated with statin-induced myopathy (SIM) such as myalgia and life-threatening rhabdomyolysis. Though the statin-induced rhabdomyolysis is not common during statin therapy, its incidence will significantly increase due to pharmacokinetic drug-drug interactions (DDIs) with inhibitor drugs which inhibit atorvastatin's and its lactone's metabolism and hepatic uptake. Thus, the quantitative analysis of DDIs of atorvastatin and its lactone with cytochrome P450 3A4 (CYP3A4) and organic anion-transporting polypeptide (OATP) inhibitors is of great importance. This study aimed to predict pharmacokinetic DDIs possibly causing atorvastatin-induced rhabdomyolysis using Physiologically Based Pharmacokinetic (PBPK) Modelling. Firstly, we refined the PBPK models of atorvastatin and atorvastatin lactone for predicting the DDIs with CYP3A4 and OATP inhibitors. Thereafter, we predicted the exposure changes of atorvastatin and atorvastatin lactone originating from the case reports of atorvastatin-induced rhabdomyolysis using the refined models. The simulation results show that pharmacokinetic DDIs of atorvastatin and its lactone with fluconazole, palbociclib diltiazem and cyclosporine are significant. Consequently, clinicians should be aware of necessary dose adjustment of atorvastatin being used with these four inhibitor drugs.
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28
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Darwich AS, Burt HJ, Rostami-Hodjegan A. The nested enzyme-within-enterocyte (NEWE) turnover model for predicting dynamic drug and disease effects on the gut wall. Eur J Pharm Sci 2019; 131:195-207. [PMID: 30776469 DOI: 10.1016/j.ejps.2019.02.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 02/11/2019] [Accepted: 02/12/2019] [Indexed: 01/25/2023]
Abstract
Physiologically-based pharmacokinetic (PBPK) models provide a framework for in vitro-in vivo extrapolation of metabolic drug clearance. Many of the concepts in PBPK can have consequential impact on more mechanistic systems pharmacology models. In the gut wall, turnover of enzymes and enterocytes are typically lumped into one rate constant that describes the time dependent enzyme activity. This assumption may influence predictability of any sustained and dynamic effects such as mechanism-based inhibition (MBI), particularly when considering translation from healthy to gut disease. A novel multi-level systems PBPK model was developed. This model comprised a 'nested enzyme-within enterocyte' (NEWE) turnover model to describe levels of drug-metabolising enzymes. The ability of the model to predict gut metabolism following MBI and gut disease was investigated and compared to the conventional modelling approach. For MBI, the default NEWE model performed comparably to the conventional model. However, when drug-specific spatial crypt-villous absorption was considered, up to approximately 50% lower impact of MBI was simulated for substrates highly metabolised by cytochrome P450 (CYP) 3A4, interacting with potent inhibitors. Further, the model showed potential in predicting the disease effect of gastrointestinal mucositis and untreated coeliac disease when compared to indirect clinical pharmacokinetic parameters. Considering the added complexity of the NEWE model, it does not provide an attractive solution for improving upon MBI predictions in healthy individuals. However, nesting turnover may enable extrapolation to gut disease-drug interactions. The principle detailed herein may be useful for modelling drug interactions with cellular targets where turnover is significant enough to affect this process.
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Affiliation(s)
- Adam S Darwich
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom.
| | | | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, School of Health Sciences, The University of Manchester, Manchester, United Kingdom; Certara UK Ltd., Sheffield, United Kingdom
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29
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Fritz A, Busch D, Lapczuk J, Ostrowski M, Drozdzik M, Oswald S. Expression of clinically relevant drug-metabolizing enzymes along the human intestine and their correlation to drug transporters and nuclear receptors: An intra-subject analysis. Basic Clin Pharmacol Toxicol 2018; 124:245-255. [PMID: 30253071 DOI: 10.1111/bcpt.13137] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 09/18/2018] [Indexed: 12/23/2022]
Abstract
The oral bioavailability of many drugs is highly influenced not only by hepatic but also by intestinal biotransformation. To estimate the impact of intestinal phase I and II metabolism on oral drug absorption, knowledge on the expression levels of the respective enzymes is an essential prerequisite. In addition, the potential interplay of metabolism and transport contributes to drug disposition. Both mechanisms may be subjected to coordinative regulation by nuclear receptors, leading to unwanted drug-drug interactions due to induction of intestinal metabolism and transport. Thus, it was the aim of this study to comprehensively analyse the regional expression of clinically relevant phase I and II enzymes along the entire human intestine and to correlate these data to expression data of drug transporters and nuclear receptors of pharmacokinetic relevance. Gene expression of 11 drug-metabolizing enzymes (CYP2B6, 2C8, 2C9, 2C19, 2D6, 3A4, 3A5, SULT1A, UGT1A, UGT2B7, UGT2B15) was studied in duodenum, jejunum, ileum and colon from six organ donors by real-time RT-PCR. Enzyme expression was correlated with expression data of the nuclear receptors PXR, CAR and FXR as well as drug transporters observed in the same cohort. Intestinal expression of all studied metabolizing enzymes was significantly higher in the small intestine compared to colonic tissue. CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4/5, SULT1A, UGT1A and UGT2B7 expression increased from the duodenum to jejunum but was markedly lower in the ileum. In the small intestine, that is, the predominant site of drug absorption, the highest expression has been observed for CYP3A4, CYP2C9, SULT1A and UGT1A. In addition, significant correlations were found between several enzymes and PXR as well as ABC transporters in the small intestine. In conclusion, the observed substantial site-dependent intestinal expression of several enzymes may explain regional differences in intestinal drug absorption. The detected correlations between intestinal enzymes, transporters and nuclear receptors provide indirect evidence for their coordinative expression, regulation and function in the human small intestine.
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Affiliation(s)
- Anja Fritz
- Department of Clinical Pharmacology, Center of Drug Absorption and Transport, University Medicine Greifswald, Greifswald, Germany
| | - Diana Busch
- Department of Clinical Pharmacology, Center of Drug Absorption and Transport, University Medicine Greifswald, Greifswald, Germany
| | - Joanna Lapczuk
- Department of Experimental and Clinical Pharmacology, Pomeranian Medical University, Szczecin, Poland
| | - Marek Ostrowski
- Department of General and Transplantation Surgery, Pomeranian Medical University, Szczecin, Poland
| | - Marek Drozdzik
- Department of Experimental and Clinical Pharmacology, Pomeranian Medical University, Szczecin, Poland
| | - Stefan Oswald
- Department of Clinical Pharmacology, Center of Drug Absorption and Transport, University Medicine Greifswald, Greifswald, Germany
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Yadav J, Korzekwa K, Nagar S. Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A. Mol Pharm 2018; 15:1979-1995. [PMID: 29608318 PMCID: PMC5938745 DOI: 10.1021/acs.molpharmaceut.8b00129] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug-drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N-demethyl erythromycin (NDE), norverapamil (NV), and N-desmethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasi-irreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro-in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000 146 min-1, the average fold difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesis-rate constant of 0.000 32 min-1. These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.
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Affiliation(s)
- Jaydeep Yadav
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 North Broad Street, Philadelphia, Pennsylvania 19140, United States
| | - Ken Korzekwa
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 North Broad Street, Philadelphia, Pennsylvania 19140, United States
| | - Swati Nagar
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 North Broad Street, Philadelphia, Pennsylvania 19140, United States
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Huang CS, Chen HW, Lin TY, Lin AH, Lii CK. Shikonin upregulates the expression of drug-metabolizing enzymes and drug transporters in primary rat hepatocytes. JOURNAL OF ETHNOPHARMACOLOGY 2018; 216:18-25. [PMID: 29414119 DOI: 10.1016/j.jep.2018.01.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Revised: 01/17/2018] [Accepted: 01/19/2018] [Indexed: 06/08/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Shikonin, a naphthoquinone pigment abundant in the root of the Chinese herb Lithospermum erythrorhizon, has been widely used to treat inflammatory diseases for thousands of years. Whether shikonin changes drug metabolism remains unclear. AIM OF THE STUDY We investigated whether shikonin modulates the expression of hepatic drug-metabolizing enzymes and transporters as well as the possible mechanisms of this action. MATERIALS AND METHODS Primary hepatocytes isolated from Sprague-Dawley rats were treated with 0-2 μM shikonin and the protein and mRNA levels of drug-metabolizing enzymes and transporters as well as the activation of aryl hydrocarbon receptor (AhR) and NF-E2-related factor 2 (Nrf2) were determined. RESULTS Shikonin dose-dependently increased the protein and RNA expression of phase I enzymes, i.e., cytochrome P450 (CYP) 1A1/2, CYP3A2, CYP2D1, and CYP2C6; phase II enzymes, i.e., glutathione S-transferase (GST), NADP(H) quinone oxidoreductase 1 (NQO1), and UDP glucuronosyltransferase 1A1; and phase III drug transporters, i.e., P-glycoprotein, multidrug resistance-associated protein 2/3, organic anion transporting polypeptide (OATP) 1B1, and OATP2B1. Immunoblot analysis and EMSA revealed that shikonin increased AhR and Nrf2 nuclear contents and DNA binding activity. AhR and Nrf2 knockdown by siRNA attenuated the ability of shikonin to induce drug-metabolizing enzyme expression. In addition, shikonin increased p38, JNK, and ERK1/2 phosphorylation, and inhibitors of the respective kinases inhibited shikonin-induced Nrf2 nuclear translocation. CONCLUSIONS Shikonin effectively upregulates the transcription of CYP isozymes, phase II detoxification enzymes, and phase III membrane transporters and this function is at least partially through activation of AhR and Nrf2. Moreover, Nrf2 activation is dependent on mitogen-activated protein kinases.
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MESH Headings
- Animals
- Anti-Inflammatory Agents/pharmacology
- Basic Helix-Loop-Helix Transcription Factors/agonists
- Basic Helix-Loop-Helix Transcription Factors/genetics
- Basic Helix-Loop-Helix Transcription Factors/metabolism
- Biotransformation
- Cells, Cultured
- Dose-Response Relationship, Drug
- Drugs, Chinese Herbal/pharmacology
- Extracellular Signal-Regulated MAP Kinases
- Gene Expression Regulation, Enzymologic/drug effects
- Hepatocytes/drug effects
- Hepatocytes/enzymology
- JNK Mitogen-Activated Protein Kinases
- Male
- Membrane Transport Proteins/drug effects
- Membrane Transport Proteins/genetics
- Membrane Transport Proteins/metabolism
- NF-E2-Related Factor 2/genetics
- NF-E2-Related Factor 2/metabolism
- Naphthoquinones/pharmacology
- Phosphorylation
- Primary Cell Culture
- RNA, Messenger/genetics
- RNA, Messenger/metabolism
- Rats, Sprague-Dawley
- Receptors, Aryl Hydrocarbon/agonists
- Receptors, Aryl Hydrocarbon/genetics
- Receptors, Aryl Hydrocarbon/metabolism
- Transcriptional Activation/drug effects
- p38 Mitogen-Activated Protein Kinases/metabolism
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Affiliation(s)
- Chin-Shiu Huang
- Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan; Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Haw-Wen Chen
- Department of Nutrition, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan
| | - Tzu-Yu Lin
- Department of Nutrition, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan
| | - Ai-Hsuan Lin
- Department of Nutrition, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan
| | - Chong-Kuei Lii
- Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan; Department of Nutrition, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan.
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32
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Gao X, Hu J, Zhang X, Zuo Y, Wang Y, Zhu S. Research progress of aconitine toxicity and forensic analysis of aconitine poisoning. Forensic Sci Res 2018; 5:25-31. [PMID: 32490307 PMCID: PMC7241456 DOI: 10.1080/20961790.2018.1452346] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Accepted: 03/12/2018] [Indexed: 12/18/2022] Open
Abstract
Chinese herbal medicines have been extensively used in China and other countries for centuries. Aconitine, a diterpenoid alkaloid extracted from Aconitum plants, has anti-inflammatory and analgesic activities, but can also induce severe arrhythmia and neurotoxicity. Aconitine poisoning accidents caused by misuse, suicide, or homicide have been reported in recent years. In China, fatal aconitine poisoning can occasionally happen on account of accidental ingestion of some wild plants or consumption of herbal decoction made from the roots of Aconitum plants. However, it is rather difficult for forensic experts to find the specific results in present forensic autopsy of aconitine-induced death. To further clarify its potential risk following the widespread application of aconitine, toxicological characteristics and pharmacokinetics of aconitine are reviewed. Moreover, gastrointestinal, neurological, and cardiovascular symptoms were observed frequently in aconitine poisoning cases. In addition, the review also aims at providing some convincing evidences for forensic experts to identify unexplained death with postmortem examination.
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Affiliation(s)
- Xiangting Gao
- Department of Forensic Medicine, Soochow University, Suzhou, China
| | - Jun Hu
- Department of Forensic Medicine, Soochow University, Suzhou, China.,Laboratory of Biomedical Technology, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Xincai Zhang
- Department of Forensic Medicine, Soochow University, Suzhou, China
| | - Yuanyi Zuo
- Department of Forensic Medicine, Soochow University, Suzhou, China.,Department of Forensic Sciences, Binhai People's Hospital, Yancheng, China
| | - Yun Wang
- Department of Forensic Medicine, Soochow University, Suzhou, China
| | - Shaohua Zhu
- Department of Forensic Medicine, Soochow University, Suzhou, China
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33
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Zhang M, Peng CS, Li XB. Human intestine and liver microsomal metabolic differences between C19-diester and monoester diterpenoid alkaloids from the roots of Aconitum carmichaelii Debx. Toxicol In Vitro 2017; 45:318-333. [DOI: 10.1016/j.tiv.2017.09.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 09/11/2017] [Accepted: 09/12/2017] [Indexed: 11/30/2022]
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34
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Kosaka M, Kosugi Y, Hirabayashi H. Risk Assessment Using Cytochrome P450 Time-Dependent Inhibition Assays at Single Time and Concentration in the Early Stage of Drug Discovery. J Pharm Sci 2017; 106:2839-2846. [DOI: 10.1016/j.xphs.2017.04.077] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 04/28/2017] [Accepted: 04/28/2017] [Indexed: 02/07/2023]
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35
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Ho MCD, Ring N, Amaral K, Doshi U, Li AP. Human Enterocytes as an In Vitro Model for the Evaluation of Intestinal Drug Metabolism: Characterization of Drug-Metabolizing Enzyme Activities of Cryopreserved Human Enterocytes from Twenty-Four Donors. Drug Metab Dispos 2017; 45:686-691. [PMID: 28396528 DOI: 10.1124/dmd.116.074377] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 04/05/2017] [Indexed: 01/09/2023] Open
Abstract
We report in this work successful isolation and cryopreservation of enterocytes from human small intestine. The enterocytes were isolated by enzyme digestion of the intestinal lumen, followed by partial purification via differential centrifugation. The enterocytes were cryopreserved directly after isolation without culturing to maximize retention of in vivo drug-metabolizing enzyme activities. Post-thaw viability of the cryopreserved enterocytes was consistently over 80% based on trypan blue exclusion. Cryopreserved enterocytes pooled from eight donors (four male and four female) were evaluated for their metabolism of 14 pathway-selective substrates: CYP1A2 (phenacetin hydroxylation), CYP2A6 (coumarin 7-hydroxylation), CYP2B6 (bupropion hydroxylation), CYP2C8 (paclitaxel 6α-hydroxylation), CYP2C9 (diclofenac 4-hydroxylation), CYP2C19 (S-mephenytoin 4-hydroxylation), CYP2D6 (dextromethorphan hydroxylation), CYP2E1 (chlorzoxazone 6-hydroxylation), CYP3A4 (midazolam 1'-hydroxylation and testosterone 6β-hydroxylation), CYP2J2 (astemizole O-demethylation), UDP-glucuronosyltransferase (UGT; 7-hydroxycoumarin glucuronidation), sulfotransferase (SULT; 7-hydroxycoumarin sulfation), and carboxylesterase 2 (CES2; irinotecan hydrolysis) activities. Quantifiable activities were observed for CYP2C8, CYP2C9, CYP2C19, CYP2E1, CYP3A4, CYPJ2, CES2, UGT, and SULT, but not for CYP1A2, CYP2A6, CYP2B6, and CYP2D6. Enterocytes from all 24 donors were then individually evaluated for the quantifiable drug metabolism pathways. All demonstrated quantifiable activities with the expected individual variations. Our results suggest that cryopreserved human enterocytes represent a physiologically relevant and convenient in vitro experimental system for the evaluation of intestinal metabolism, akin to cryopreserved human hepatocytes for hepatic metabolism.
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Affiliation(s)
| | | | | | | | - Albert P Li
- In Vitro ADMET Laboratories, Columbia, Maryland
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36
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In Vitro – In Vivo Extrapolation of Intestinal Availability for Carboxylesterase Substrates Using Portal Vein–Cannulated Monkey. J Pharm Sci 2017; 106:898-905. [DOI: 10.1016/j.xphs.2016.12.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 11/04/2016] [Accepted: 12/02/2016] [Indexed: 10/20/2022]
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37
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Hatley OJD, Jones CR, Galetin A, Rostami-Hodjegan A. Quantifying gut wall metabolism: methodology matters. Biopharm Drug Dispos 2017; 38:155-160. [PMID: 28039878 PMCID: PMC5412859 DOI: 10.1002/bdd.2062] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 12/16/2016] [Accepted: 12/21/2016] [Indexed: 12/21/2022]
Affiliation(s)
- Oliver J D Hatley
- Simcyp Ltd (A Certara Company), Blades Enterprise Centre, Sheffield, S2 4SU, UK
| | | | - Aleksandra Galetin
- Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, M13 9PT, UK
| | - Amin Rostami-Hodjegan
- Simcyp Ltd (A Certara Company), Blades Enterprise Centre, Sheffield, S2 4SU, UK.,Centre for Applied Pharmacokinetic Research, Manchester Pharmacy School, University of Manchester, Manchester, M13 9PT, UK
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38
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Xie F, Ding X, Zhang QY. An update on the role of intestinal cytochrome P450 enzymes in drug disposition. Acta Pharm Sin B 2016; 6:374-383. [PMID: 27709006 PMCID: PMC5045550 DOI: 10.1016/j.apsb.2016.07.012] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 07/12/2016] [Accepted: 07/14/2016] [Indexed: 12/05/2022] Open
Abstract
Oral administration is the most commonly used route for drug treatment. Intestinal cytochrome P450 (CYP)-mediated metabolism can eliminate a large proportion of some orally administered drugs before they reach systemic circulation, while leaving the passage of other drugs unimpeded. A better understanding of the ability of intestinal P450 enzymes to metabolize various clinical drugs in both humans and preclinical animal species, including the identification of the CYP enzymes expressed, their regulation, and the relative importance of intestinal metabolism compared to hepatic metabolism, is important for improving bioavailability of current drugs and new drugs in development. Here, we briefly review the expression of drug-metabolizing P450 enzymes in the small intestine of humans and several preclinical animal species, and provide an update of the various factors or events that regulate intestinal P450 expression, including a cross talk between the liver and the intestine. We further compare various clinical and preclinical approaches for assessing the impact of intestinal drug metabolism on bioavailability, and discuss the utility of the intestinal epithelium–specific NADPH-cytochrome P450 reductase-null (IECN) mouse as a useful model for studying in vivo roles of intestinal P450 in the disposition of orally administered drugs.
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39
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Abstract. Drug Metab Rev 2016. [DOI: 10.1080/03602532.2016.1191843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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40
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Peters SA, Jones CR, Ungell AL, Hatley OJD. Predicting Drug Extraction in the Human Gut Wall: Assessing Contributions from Drug Metabolizing Enzymes and Transporter Proteins using Preclinical Models. Clin Pharmacokinet 2016; 55:673-96. [PMID: 26895020 PMCID: PMC4875961 DOI: 10.1007/s40262-015-0351-6] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Intestinal metabolism can limit oral bioavailability of drugs and increase the risk of drug interactions. It is therefore important to be able to predict and quantify it in drug discovery and early development. In recent years, a plethora of models-in vivo, in situ and in vitro-have been discussed in the literature. The primary objective of this review is to summarize the current knowledge in the quantitative prediction of gut-wall metabolism. As well as discussing the successes of current models for intestinal metabolism, the challenges in the establishment of good preclinical models are highlighted, including species differences in the isoforms; regional abundances and activities of drug metabolizing enzymes; the interplay of enzyme-transporter proteins; and lack of knowledge on enzyme abundances and availability of empirical scaling factors. Due to its broad specificity and high abundance in the intestine, CYP3A is the enzyme that is frequently implicated in human gut metabolism and is therefore the major focus of this review. A strategy to assess the impact of gut wall metabolism on oral bioavailability during drug discovery and early development phases is presented. Current gaps in the mechanistic understanding and the prediction of gut metabolism are highlighted, with suggestions on how they can be overcome in the future.
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Affiliation(s)
- Sheila Annie Peters
- Translational Quantitative Pharmacology, BioPharma, R&D Global Early Development, Merck KGaA, Frankfurter Str. 250, F130/005, 64293, Darmstadt, Germany.
| | | | - Anna-Lena Ungell
- Investigative ADME, Non-Clinical Development, UCB New Medicines, BioPharma SPRL, Braine l'Alleud, Belgium
| | - Oliver J D Hatley
- Simcyp Limited (A Certara Company), Blades Enterprise Centre, Sheffield, UK
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41
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Bohnert T, Patel A, Templeton I, Chen Y, Lu C, Lai G, Leung L, Tse S, Einolf HJ, Wang YH, Sinz M, Stearns R, Walsky R, Geng W, Sudsakorn S, Moore D, He L, Wahlstrom J, Keirns J, Narayanan R, Lang D, Yang X. Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions-an Industry Perspective. ACTA ACUST UNITED AC 2016; 44:1399-423. [PMID: 27052879 DOI: 10.1124/dmd.115.069096] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 03/31/2016] [Indexed: 12/15/2022]
Abstract
Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome.
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Affiliation(s)
- Tonika Bohnert
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Aarti Patel
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Ian Templeton
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Yuan Chen
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Chuang Lu
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - George Lai
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Louis Leung
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Susanna Tse
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Heidi J Einolf
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Ying-Hong Wang
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Michael Sinz
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Ralph Stearns
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Robert Walsky
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Wanping Geng
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Sirimas Sudsakorn
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - David Moore
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Ling He
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Jan Wahlstrom
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Jim Keirns
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Rangaraj Narayanan
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Dieter Lang
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
| | - Xiaoqing Yang
- Biogen, Cambridge, Massachusetts (T.B.); GlaxoSmithKline R&D, Hertfordshire, United Kingdom (A.P.); Janssen R&D, Spring House, Pennsylvania (I.T.); Genentech, South San Francisco, California (Y.C.); Takeda, Cambridge, Massachusetts (C.L.); Eisai Inc., Andover, Massachusetts (G.L.); Pfizer Inc., Groton, Connecticut (L.L., S.T.); Novartis, East Hanover, New Jersey (H.J.E.); Merck & Co., Inc., Kenilworth, New Jersey (Y.-H.W.); Bristol Myers Squibb, Wallingford, Connecticut (M.S.); Vertex Pharmaceuticals Inc., Boston, Massachusetts (R.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.W., W.G.); Sanofi, Waltham, Massachusetts (S.S.); Roche Innovation Center, New York, New York (D.M.); Daiichi Sankyo, Edison, New Jersey (L.H.); Amgen Inc., Thousand Oaks, California (J.W.); Astellas, Northbrook, Illinois (J.K.); Celgene Corporation, Summit, New Jersey (R.N.); Bayer Pharma AG, Wuppertal, Germany (D.L.); and Incyte Corporation, Wilmington, Delaware (X.Y.)
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Jones CR, Hatley OJD, Ungell AL, Hilgendorf C, Peters SA, Rostami-Hodjegan A. Gut Wall Metabolism. Application of Pre-Clinical Models for the Prediction of Human Drug Absorption and First-Pass Elimination. AAPS JOURNAL 2016; 18:589-604. [PMID: 26964996 DOI: 10.1208/s12248-016-9889-y] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 12/07/2015] [Indexed: 12/21/2022]
Abstract
Quantifying the multiple processes which control and modulate the extent of oral bioavailability for drug candidates is critical to accurate projection of human pharmacokinetics (PK). Understanding how gut wall metabolism and hepatic elimination factor into first-pass clearance of drugs has improved enormously. Typically, the cytochrome P450s, uridine 5'-diphosphate-glucuronosyltransferases and sulfotransferases, are the main enzyme classes responsible for drug metabolism. Knowledge of the isoforms functionally expressed within organs of first-pass clearance, their anatomical topology (e.g. zonal distribution), protein homology and relative abundances and how these differ across species is important for building models of human metabolic extraction. The focus of this manuscript is to explore the parameters influencing bioavailability and to consider how well these are predicted in human from animal models or from in vitro to in vivo extrapolation. A unique retrospective analysis of three AstraZeneca molecules progressed to first in human PK studies is used to highlight the impact that species differences in gut wall metabolism can have on predicted human PK. Compared to the liver, pharmaceutical research has further to go in terms of adopting a common approach for characterisation and quantitative prediction of intestinal metabolism. A broad strategy is needed to integrate assessment of intestinal metabolism in the context of typical DMPK activities ongoing within drug discovery programmes up until candidate drug nomination.
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Affiliation(s)
- Christopher R Jones
- Oncology Innovative Medicines DMPK, AstraZeneca, Alderley Park, Cheshire, UK. .,Heptares Therapeutics Ltd, BioPark Broadwater Road, Welwyn Garden City, AL73AX, UK.
| | - Oliver J D Hatley
- Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK
| | - Anna-Lena Ungell
- CVMD Innovative Medicines DMPK, AstraZeneca, Mölndal, Sweden.,Investigative ADME, Non Clinical Development, UCB New Medicines, BioPharma SPRL, Chemin de Foriest, B-1420, Braine A'lleud, Belgium
| | | | - Sheila Annie Peters
- Modelling and Simulation, Respiratory, Inflammation and Autoimmunity Innovative Medicines DMPK, AstraZeneca, Mölndal, Sweden
| | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, Manchester School of Pharmacy, University of Manchester, Manchester, M13 9PT, UK
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Wong SG, Lee M, Wong BK. Single concentration loss of activity assay provides an improved assessment of drug-drug interaction risk compared to IC50-shift. Xenobiotica 2016; 46:953-66. [PMID: 26956546 DOI: 10.3109/00498254.2016.1143139] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
1. The utility of two abbreviated, higher-throughput assays [IC50-shift and the loss of activity (LOA) assay] to evaluate time-dependent inhibition (TDI) of 24 structurally related compounds was compared. 2. Good correlation (R(2) = 0.90) between % inhibition and kinact/KI suggested that the LOA assay has utility as an indicator of TDI potential. Weaker correlation was observed for the shifted IC50 (IC50(T = 30)) (R(2) = 0.61) and the fold-shift in IC50 (R(2) = 0.17). 3. Primary mechanism for poor correlation was depletion of active enzyme at concentrations > 1 μM leading to greater than predicted inhibition in the IC50-shift assay. 4. Previously reported strong correlations between IC50(T = 30) and kinact/KI were found to be dependent on potent TDI compounds with kinact/KI > 30; correlation was reduced for moderate inhibitors (kinact/KI < 30). LOA assay maintained good correlation even when strong TDI compounds were excluded. 5. LOA assay (% Inhibition at 30 min, 10 μM) was a good predictor of in vivo DDI (AUCr), providing a graded response with low potential for false negatives or positives. IC50-shift assay had bias for over-predicting in vivo DDI and was more likely to identify false positives.
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Affiliation(s)
- Simon G Wong
- a Department of Pharmacokinetics and Drug Metabolism , Amgen , South San Francisco , CA , USA
| | - Mey Lee
- a Department of Pharmacokinetics and Drug Metabolism , Amgen , South San Francisco , CA , USA
| | - Bradley K Wong
- a Department of Pharmacokinetics and Drug Metabolism , Amgen , South San Francisco , CA , USA
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Explication of Definitional Description and Empirical Use of Fraction of Orally Administered Drugs Absorbed From the Intestine (F a ) and Intestinal Availability (F g ): Effect of P-glycoprotein and CYP3A on F a and F g. J Pharm Sci 2016; 105:431-442. [DOI: 10.1016/j.xphs.2015.11.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Revised: 11/05/2015] [Accepted: 11/10/2015] [Indexed: 01/13/2023]
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Sane RS, Ramsden D, Sabo JP, Cooper C, Rowland L, Ting N, Whitcher-Johnstone A, Tweedie DJ. Contribution of Major Metabolites toward Complex Drug-Drug Interactions of Deleobuvir: In Vitro Predictions and In Vivo Outcomes. Drug Metab Dispos 2015; 44:466-75. [DOI: 10.1124/dmd.115.066985] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Accepted: 12/17/2015] [Indexed: 12/13/2022] Open
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Mano Y, Sugiyama Y, Ito K. Use of a Physiologically Based Pharmacokinetic Model for Quantitative Prediction of Drug-Drug Interactions via CYP3A4 and Estimation of the Intestinal Availability of CYP3A4 Substrates. J Pharm Sci 2015; 104:3183-93. [PMID: 26045365 DOI: 10.1002/jps.24495] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Revised: 04/21/2015] [Accepted: 04/21/2015] [Indexed: 11/09/2022]
Abstract
The purpose of this study was to predict the drug-drug interactions (DDIs) via CYP3A4 by estimating the extent of hepatic CYP3A4 inhibition based on a physiologically based pharmacokinetic (PBPK) model of both substrate and inhibitor and the increase in the intestinal availability (Fg ) due to the enzyme inhibition. For the DDIs resulting from reversible inhibition of CYP3A4, the prediction using in vivo Ki values estimated from other clinical DDI studies and predicted in vivo Ki values calculated using the correlation between the log P and the in vivo Ki /in vitro Ki ratio was more accurate than that using in vitro Ki values. Incorporating inhibition of both intestinal and hepatic metabolism resulted in better prediction than that obtained considering inhibition in the liver alone, and all the DDIs (AUC increase by the inhibitor) were predicted within 2-fold accuracy when in vivo Ki values were used. In addition, Fg values were successfully back-calculated from the clinical DDI data based on the present model. In conclusion, the present PBPK model incorporating the in vivo Ki values was found to be useful for quantitative prediction of clinical DDIs and for estimation of the Fg values for CYP3A4 substrates for which intravenous data were not available.
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Affiliation(s)
- Yoko Mano
- Pharmacokinetics and Metabolism, Drug Safety and Pharmacokinetics Laboratories, Taisho Pharmaceutical Company Ltd, Saitama, 331-9530, Japan
| | - Yuichi Sugiyama
- Sugiyama Laboratory, RIKEN Innovation Center, RIKEN Research Cluster for Innovation, RIKEN, Kanagawa, 230-0045, Japan
| | - Kiyomi Ito
- Research Institute of Pharmaceutical Sciences, Musashino University, Tokyo, 202-8585, Japan
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Riley RJ, Wilson CE. Cytochrome P450 time-dependent inhibition and induction: advances in assays, risk analysis and modelling. Expert Opin Drug Metab Toxicol 2015; 11:557-72. [PMID: 25659570 DOI: 10.1517/17425255.2015.1013095] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION It is widely accepted that current practice of polypharmacy inevitably increases the incidence of drug-drug interactions (DDIs). Serious DDIs are a major liability for new molecular entities entering the pharmaceutical market. Various strategies are employed to avoid problematic compounds for clinical development. Progress made with reversible CYP DDIs has prompted a switch to study and model time-dependent inhibition and induction interactions. AREAS COVERED An overview of popular experimental practices is presented with discussion of techniques and algorithms used to analyse the clinical DDI risk. Emphasis is placed on the transition from early, simple static equations, via more complex net mechanistic, static models to dynamic approaches involving multiple perpetrators and metabolites, simultaneous inhibition and induction. EXPERT OPINION Inclusion of the more conservative terms for parameters required for DDI evaluation may eliminate promising chemical space, encourages poor practice and hampers innovation. Breakthroughs have originated from understanding of 'outliers' from such analyses where CYP enzyme-transporter interplay may be involved. The role of key transporters in drug disposition is firmly established as the chemistry required to address new targets deviates from traditional 'drug-like' space. Attempts to model more complex interactions for substrates of both CYP enzymes and drug transporters are still in their infancy and will benefit from dynamic modelling.
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Affiliation(s)
- Robert J Riley
- Evotec (UK) Ltd , 114 Innovation Drive, Milton Park, Abingdon, Oxon, OX14 4RZ , UK +44 1235 861561 ; +44 1235 863139 ;
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Zhang M, Peng CS, Li XB. In vivo and in vitro metabolites from the main diester and monoester diterpenoid alkaloids in a traditional chinese herb, the aconitum species. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2015; 2015:252434. [PMID: 25705235 PMCID: PMC4332761 DOI: 10.1155/2015/252434] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Accepted: 11/13/2014] [Indexed: 01/08/2023]
Abstract
Diester diterpenoid alkaloids (DDAs), such as aconitine (AC), mesaconitine (MA), and hypaconitine (HA), are both pharmacologically active compounds and toxic ingredients in a traditional Chinese herb, the Aconitum species. Many DDA metabolism studies have been performed to explore mechanisms for reducing toxicity in these compounds and in Aconitum species extracts for safe clinical administration. In this review, we summarize recent progress on the metabolism of toxic AC, MA, and HA and corresponding monoester diterpenoid alkaloids (MDAs) in the gastrointestinal tract and liver in different animal species and humans in vivo and/or in vitro, where these alkaloids are primarily metabolized by cytochrome P450 enzymes, carboxylesterases, and intestinal bacteria, which produces phase I metabolites, ester hydrolysed products, and lipoalkaloids. Furthermore, we classify metabolites detected in the blood and urine, where the aforementioned metabolites are absorbed and excreted. Less toxic MDAs and nontoxic alcohol amines are the primary DDA metabolites detected in the blood. Most other DDAs metabolites produced in the intestine and liver detected in the urine have not been reported in the blood. We propose an explanation for this nonconformity. Finally, taking AC, for instance, we generalize a process of toxicity reduction in the body after oral AC administration for the first time.
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Affiliation(s)
- Min Zhang
- School of Pharmacy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Chong-sheng Peng
- School of Pharmacy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Xiao-bo Li
- School of Pharmacy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
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Pharmacokinetic interactions between simvastatin and setipiprant, a CRTH2 antagonist. Eur J Clin Pharmacol 2014; 71:15-23. [PMID: 25323804 DOI: 10.1007/s00228-014-1767-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Accepted: 10/06/2014] [Indexed: 01/21/2023]
Abstract
PURPOSE Setipiprant, a selective oral CRTH2 antagonist, has been investigated for the treatment of allergic rhinitis and asthma. In vitro data showed that setipiprant has a weak induction potential on CYP3A4. An interaction at the hepatic level between setipiprant and CYP3A4 substrates was not expected even at the dosing regimen of 1,000 mg setipiprant b.i.d. due to the high plasma protein binding. However, at this dosing regimen, interactions at the gut level could not be excluded. METHODS In this single-center, open-label study, 40 mg of simvastatin was administered orally on Day 1, and then concomitantly with setipiprant on Day 10 following 9 days of setipiprant 1,000 mg b.i.d. to 22 healthy male subjects. RESULTS In the presence of setipiprant, the simvastatin concentration-time profile was similar to that of simvastatin alone. The concentrations of simvastatin were, however, slightly lower, resulting in a 9 % decrease in C max (geometric mean ratio (GMR) 0.91, 90 % confidence interval (CI) (0.73, 1.13)) and in a 16 % lower AUC0-∞ (GMR 0.84, 90 % CI (0.72, 0.99)). Exposure to simvastatin acid was similar when comparing simvastatin with or without setipiprant. The GMR and 90 % CI for AUC0-∞ were within the 0.8 to 1.25 limits, whereas those for C max were outside (GMR 2.73, 90 % CI (2.11, 3.53)). Moreover, the median t max of simvastatin acid occurred earlier (1.8 h) when combined compared to 3.0 h when administered alone. CONCLUSIONS As setipiprant has little impact on simvastatin pharmacokinetics, it does not modulate CYP3A4 in a clinically relevant manner.
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Mitsui T, Nemoto T, Miyake T, Nagao S, Ogawa K, Kato M, Ishigai M, Yamada H. A Useful Model Capable of Predicting the Clearance of Cytochrome P450 3A4 (CYP3A4) Substrates in Humans: Validity of CYP3A4 Transgenic Mice Lacking Their Own Cyp3a Enzymes. Drug Metab Dispos 2014; 42:1540-7. [DOI: 10.1124/dmd.114.057935] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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