Predicting human hepatic clearance from in vitro drug metabolism and transport data: a scientific and pharmaceutical perspective for assessing drug-drug interactions

被引:60
|
作者
Camenisch, Gian [1 ]
Umehara, Ken-ichi [1 ]
机构
[1] Novartis Inst Biomed Res, Drug Drug Interact Sect DDI, Drug Metab & Pharmacokinet DMPK, CH-4002 Basel, Switzerland
关键词
clearance prediction; drug-drug interactions; metabolism; transporter; compound classification; INTESTINAL 1ST-PASS METABOLISM; CLINICAL PHARMACOKINETICS; VIVO EXTRAPOLATION; ORGAN CLEARANCE; DISPOSITION; KETOCONAZOLE; ATORVASTATIN; MODELS; LIVER; BIOTRANSFORMATION;
D O I
10.1002/bdd.1784
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Objectives Membrane transporters and metabolism are major determinants of the hepatobiliary elimination of drugs. This work investigates several key questions for drug development. Such questions include which drugs demonstrate transporter-based clearance in the clinic, and which in vitro methods are most suitable for drug classification, i.e. transporter- vs metabolism-dependent compound class categories. Additional questions posed are: what is the expected quantitative change in exposure in the presence of a transporter- and/or metabolism-inhibiting drug, and which criteria should trigger follow-up clinical drugdrug interaction studies. Methods A well-established method for (human) liver clearance prediction that considers all four physiological processes driving hepatic drug elimination (namely sinusoidal uptake and efflux, metabolism and biliary secretion) was applied. Suspended hepatocytes, liver microsomes and sandwich-cultured hepatocytes were used as in vitro models to determine the individual intrinsic clearance for 13 selected compounds with various physicochemical and pharmacokinetic properties. Results Using this in vitroin vivo extrapolation method a good linear correlation was observed between predicted and reported human hepatic clearances. Linear regression analysis revealed much improved correlations compared with other prediction methods. Conclusions The presented approach serves as a basis for accurate compound categorization within the Biopharmaceutics Drug Disposition Classification System (BDDCS) and was applied to anticipate metabolism- and transporter-based drugdrug interactions using different static prediction methods. A decision tree proposal is provided and helps to guide clinical studies on active processes influencing hepatic elimination. All recommendations in this paper are generally intended to support early pre-clinical and clinical drug development and the filing of a new drug application. Copyright (c) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:179 / 194
页数:16
相关论文
共 50 条
  • [1] Predicting drug-drug interactions from in vitro drug metabolism data: challenges and recent advances
    Obach, R. Scott
    CURRENT OPINION IN DRUG DISCOVERY & DEVELOPMENT, 2009, 12 (01) : 81 - 89
  • [2] Prediction of pharmacokinetics and drug-drug interactions from in vitro metabolism data
    Shou, MG
    CURRENT OPINION IN DRUG DISCOVERY & DEVELOPMENT, 2005, 8 (01) : 66 - 77
  • [3] Predicting Drug-Drug Interactions: An FDA Perspective
    Zhang, Lei
    Zhang, Yuanchao
    Zhao, Ping
    Huang, Shiew-Mei
    AAPS JOURNAL, 2009, 11 (02): : 300 - 306
  • [4] Prediction of drug-drug interactions of zonisamide metabolism in humans from in vitro data
    H. Nakasa
    H. Nakamura
    S. Ono
    M. Tsutsui
    M. Kiuchi
    S. Ohmori
    M. Kitada
    European Journal of Clinical Pharmacology, 1998, 54 : 177 - 183
  • [5] Prediction of drug-drug interactions of zonisamide metabolism in humans from in vitro data
    Nakasa, H
    Nakamura, H
    Ono, S
    Tsutsui, M
    Kiuchi, M
    Ohmori, S
    Kitada, M
    EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY, 1998, 54 (02) : 177 - 183
  • [6] Predicting drug-drug interactions:: In vitro veritas?
    Tucker, GT
    EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2004, 23 : S13 - S13
  • [7] Metabolism, Transport and Drug-Drug Interactions of Silymarin
    Xie, Ying
    Zhang, Dingqi
    Zhang, Jin
    Yuan, Jialu
    MOLECULES, 2019, 24 (20):
  • [8] Transporter-enzyme interactions:: Implications for predicting drug-drug interactions from in vitro data
    Benet, LZ
    Cummins, CL
    Wu, CY
    CURRENT DRUG METABOLISM, 2003, 4 (05) : 393 - 398
  • [9] UTILITY OF POOLED CRYOPRESERVED HUMAN ENTEROCYTES AS AN IN VITRO MODEL FOR ASSESSING INTESTINAL CLEARANCE AND DRUG-DRUG INTERACTIONS
    Wong, Susan
    Doshi, Utkarsh
    Vuong, Peter
    Liu, Ning
    Tay, Suzanne
    Le, Hoa
    Kenny, Jane
    Li, Albert P.
    Yan, Zhengyin
    DRUG METABOLISM AND PHARMACOKINETICS, 2018, 33 (01) : S78 - S78
  • [10] Quantitative prediction of in vivo drug clearance and drug interactions from in vitro data on metabolism, together with binding and transport
    Ito, K
    Iwatsubo, T
    Kanamitsu, S
    Nakajima, Y
    Sugiyama, Y
    ANNUAL REVIEW OF PHARMACOLOGY AND TOXICOLOGY, 1998, 38 : 461 - 499