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Russell LE, Yadav J, Maldonato BJ, Chien HC, Zou L, Vergara AG, Villavicencio EG. Transporter-mediated drug-drug interactions: regulatory guidelines, in vitro and in vivo methodologies and translation, special populations, and the blood-brain barrier. Drug Metab Rev 2024:1-28. [PMID: 38967415 DOI: 10.1080/03602532.2024.2364591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 05/31/2024] [Indexed: 07/06/2024]
Abstract
This review, part of a special issue on drug-drug interactions (DDIs) spearheaded by the International Society for the Study of Xenobiotics (ISSX) New Investigators, explores the critical role of drug transporters in absorption, disposition, and clearance in the context of DDIs. Over the past two decades, significant advances have been made in understanding the clinical relevance of these transporters. Current knowledge on key uptake and efflux transporters that affect drug disposition and development is summarized. Regulatory guidelines from the FDA, EMA, and PMDA that inform the evaluation of potential transporter-mediated DDIs are discussed in detail. Methodologies for preclinical and clinical testing to assess potential DDIs are reviewed, with an emphasis on the utility of physiologically based pharmacokinetic (PBPK) modeling. This includes the application of relative abundance and expression factors to predict human pharmacokinetics (PK) using preclinical data, integrating the latest regulatory guidelines. Considerations for assessing transporter-mediated DDIs in special populations, including pediatric, hepatic, and renal impairment groups, are provided. Additionally, the impact of transporters at the blood-brain barrier (BBB) on the disposition of CNS-related drugs is explored. Enhancing the understanding of drug transporters and their role in drug disposition and toxicity can improve efficacy and reduce adverse effects. Continued research is essential to bridge remaining gaps in knowledge, particularly in comparison with cytochrome P450 (CYP) enzymes.
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Affiliation(s)
- Laura E Russell
- Department of Quantitative, Translational, and ADME Sciences, AbbVie Inc, North Chicago, IL, USA
| | - Jaydeep Yadav
- Department of Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics, Merck & Co., Inc, Boston, MA, USA
| | - Benjamin J Maldonato
- Department of Nonclinical Development and Clinical Pharmacology, Revolution Medicines, Inc, Redwood City, CA, USA
| | - Huan-Chieh Chien
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Ling Zou
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Ana G Vergara
- Department of Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics, Merck & Co., Inc, Rahway, NJ, USA
| | - Erick G Villavicencio
- Department of Biology-Discovery, Imaging and Functional Genomics, Merck & Co., Inc, Rahway, NJ, USA
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Jeong YS, Jusko WJ. A Complete Extension of Classical Hepatic Clearance Models Using Fractional Distribution Parameter f d in Physiologically Based Pharmacokinetics. J Pharm Sci 2024; 113:95-117. [PMID: 37279835 PMCID: PMC10902797 DOI: 10.1016/j.xphs.2023.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/30/2023] [Accepted: 05/30/2023] [Indexed: 06/08/2023]
Abstract
The classical organ clearance models have been proposed to relate the plasma clearance CLp to probable mechanism(s) of hepatic clearance. However, the classical models assume the intrinsic capability of drug elimination (CLu,int) that is physically segregated from the vascular blood but directly acts upon the unbound drug concentration in the blood (fubCavg), and do not handle the transit-time delay between the inlet/outlet concentrations in their closed-form clearance equations. Therefore, we propose unified model structures that can address the internal blood concentration patterns of clearance organs in a more mechanistic/physiological manner, based on the fractional distribution parameter fd operative in PBPK. The basic partial/ordinary differential equations for four classical models are revisited/modified to yield a more complete set of extended clearance models, i.e., the Rattle, Sieve, Tube, and Jar models, which are the counterparts of the dispersion, series-compartment, parallel-tube, and well-stirred models. We demonstrate the feasibility of applying the resulting extended models to isolated perfused rat liver data for 11 compounds and an example dataset for in vitro-in vivo extrapolation of the intrinsic to the systemic clearances. Based on their feasibilities to handle such real data, these models may serve as an improved basis for applying clearance models in the future.
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Affiliation(s)
- Yoo-Seong Jeong
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, 14214, USA
| | - William J Jusko
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, 14214, USA.
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Mitra P, Kasliwala R, Iboki L, Madari S, Williams Z, Takahashi R, Taub ME. Mechanistic Static Model based Prediction of Transporter Substrate Drug-Drug Interactions Utilizing Atorvastatin and Rifampicin. Pharm Res 2023; 40:3025-3042. [PMID: 37821766 DOI: 10.1007/s11095-023-03613-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVE An in vitro relative activity factor (RAF) technique combined with mechanistic static modeling was examined to predict drug-drug interaction (DDI) magnitude and analyze contributions of different clearance pathways in complex DDIs involving transporter substrates. Atorvastatin and rifampicin were used as a model substrate and inhibitor pair. METHODS In vitro studies were conducted with transfected HEK293 cells, hepatocytes and human liver microsomes. Prediction success was defined as predictions being within twofold of observations. RESULTS The RAF method successfully translated atorvastatin uptake from transfected cells to hepatocytes, demonstrating its ability to quantify transporter contributions to uptake. Successful translation of atorvastatin's in vivo intrinsic hepatic clearance (CLint,h,in vivo) from hepatocytes to liver was only achieved through consideration of albumin facilitated uptake or through application of empirical scaling factors to transporter-mediated clearances. Transporter protein expression differences between hepatocytes and liver did not affect CLint,h,in vivo predictions. By integrating cis and trans inhibition of OATP1B1/OATP1B3, atorvastatin-rifampicin (single dose) DDI magnitude could be accurately predicted (predictions within 0.77-1.0 fold of observations). Simulations indicated that concurrent inhibition of both OATP1B1 and OATP1B3 caused approximately 80% of atorvastatin exposure increases (AUCR) in the presence of rifampicin. Inhibiting biliary elimination, hepatic metabolism, OATP2B1, NTCP, and basolateral efflux are predicted to have minimal to no effect on AUCR. CONCLUSIONS This study demonstrates the effective application of a RAF-based translation method combined with mechanistic static modeling for transporter substrate DDI predictions and subsequent mechanistic interpretation.
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Affiliation(s)
- Pallabi Mitra
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals Inc., 900 Old Ridgebury Road, Ridgefield, CT, 06877, USA.
| | - Rumanah Kasliwala
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
| | - Laeticia Iboki
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
| | - Shilpa Madari
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
| | - Zachary Williams
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
| | - Ryo Takahashi
- Pharmacokinetics and Non-Clinical Safety Department, Nippon Boehringer Ingelheim Co., Ltd., Kobe, Hyogo, Japan
| | - Mitchell E Taub
- Department of Drug Metabolism and Pharmacokinetics, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA
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Tess D, Chang GC, Keefer C, Carlo A, Jones R, Di L. In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes. AAPS J 2023; 25:40. [PMID: 37052732 DOI: 10.1208/s12248-023-00800-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 03/03/2023] [Indexed: 04/14/2023] Open
Abstract
In vitro-in vivo extrapolation ((IVIVE) and empirical scaling factors (SF) of human intrinsic clearance (CLint) were developed using one of the largest dataset of 455 compounds with data from human liver microsomes (HLM) and human hepatocytes (HHEP). For extended clearance classification system (ECCS) class 2/4 compounds, linear SFs (SFlin) are approximately 1, suggesting enzyme activities in HLM and HHEP are similar to those in vivo under physiological conditions. For ECCS class 1A/1B compounds, a unified set of SFs was developed for CLint. These SFs contain both SFlin and an exponential SF (SFβ) of fraction unbound in plasma (fu,p). The unified SFs for class 1A/1B eliminate the need to identify the transporters involved prior to clearance prediction. The underlying mechanisms of these SFs are not entirely clear at this point, but they serve practical purposes to reduce biases and increase prediction accuracy. Similar SFs have also been developed for preclinical species. For HLM-HHEP disconnect (HLM > HHEP) ECCS class 2/4 compounds that are mainly metabolized by cytochrome P450s/FMO, HLM significantly overpredicted in vivo CLint, while HHEP slightly underpredicted and geometric mean of HLM and HHEP slightly overpredicted in vivo CLint. This observation is different than in rats, where rat liver microsomal CLint correlates well with in vivo CLint for compounds demonstrating permeability-limited metabolism. The good CLint IVIVE developed using HLM and HHEP helps build confidence for prospective predictions of human clearance and supports the continued utilization of these assays to guide structure-activity relationships to improve metabolic stability.
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Affiliation(s)
- David Tess
- Modeling and Simulation, Pfizer Worldwide Research and Development, Cambridge, MA, USA
| | - George C Chang
- Modeling and Simulation, Pfizer Worldwide Research and Development, Groton, CT, USA
| | - Christopher Keefer
- Modeling and Simulation, Pfizer Worldwide Research and Development, Groton, CT, USA
| | - Anthony Carlo
- Discovery Sciences, Pfizer Worldwide Research and Development, Groton, CT, USA
| | - Rhys Jones
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, La Jolla, CA, USA
| | - Li Di
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, 06340, USA.
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The next frontier in ADME science: Predicting transporter-based drug disposition, tissue concentrations and drug-drug interactions in humans. Pharmacol Ther 2022; 238:108271. [DOI: 10.1016/j.pharmthera.2022.108271] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 08/05/2022] [Accepted: 08/17/2022] [Indexed: 12/25/2022]
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Miyauchi S, Kim SJ, Lee W, Sugiyama Y. Consideration of albumin-mediated hepatic uptake for highly protein-bound anionic drugs: Bridging the gap of hepatic uptake clearance between in vitro and in vivo. Pharmacol Ther 2021; 229:107938. [PMID: 34171335 DOI: 10.1016/j.pharmthera.2021.107938] [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: 05/13/2020] [Accepted: 03/22/2021] [Indexed: 10/21/2022]
Abstract
The accuracy in predicting in vivo hepatic clearance of drugs from in vitro data (often termed as in vitro-to-in vivo extrapolation, IVIVE) has improved in part by applying the extended-clearance concept that considers the interplay between hepatic metabolism and uptake/efflux processes. However, the IVIVE-based prediction performs poorly in predicting the hepatic uptake clearance of highly albumin-bound anionic drugs. Their hepatic uptake clearances tend to be much higher than expected based on the free-drug theory. Such observation can be attributable to a phenomenon called albumin-mediated hepatic uptake, for which various models have been thus far proposed. Our group has been applying a facilitated-dissociation model, which assumes the enhanced dissociation of the drug-albumin complex upon interaction with the cell surface. By considering the albumin-mediated hepatic uptake (using the facilitated-dissociation model or alternative kinetic models), a number of investigations demonstrated the improvement in the prediction accuracy for the hepatic clearance of highly protein-bound anionic drugs that are substrates for hepatic uptake transporters. This review summarizes the reported kinetic analyses of the albumin-mediated hepatic uptake of highly albumin-bound drugs concerning the IVIVE and the clinical and physiological relevance.
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Affiliation(s)
- Seiji Miyauchi
- Faculty of Pharmaceutical Sciences, Toho University, 2-2-1 Miyama, Funabashi, Chiba, Japan
| | - Soo-Jin Kim
- Sugiyama Laboratory, RIKEN Baton Zone Program, RIKEN Cluster for Science, Technology and Innovation Hub, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Wooin Lee
- College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Republic of Korea
| | - Yuichi Sugiyama
- Sugiyama Laboratory, RIKEN Baton Zone Program, RIKEN Cluster for Science, Technology and Innovation Hub, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
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