In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes

Smith DA, Beaumont K, Maurer TS, Di L. Clearance in drug design. J Med Chem. 2019;62(5):2245–55. https://doi.org/10.1021/acs.jmedchem.8b01263.

Article  CAS  PubMed  Google Scholar 

Smith DA, Beaumont K, Maurer TS, Di L. Relevance of half-life in drug design. J Med Chem. 2018;61(10):4273–82. https://doi.org/10.1021/acs.jmedchem.7b00969.

Article  CAS  PubMed  Google Scholar 

Smith DA, Beaumont K, Maurer TS, Di L. Volume of distribution in drug design. J Med Chem. 2015;58(15):5691–8. https://doi.org/10.1021/acs.jmedchem.5b00201.

Article  CAS  PubMed  Google Scholar 

Benet LZ, Zia-Amirhosseini P. Basic principles of pharmacokinetics. Toxicol Pathol. 1995;23(2):115. https://doi.org/10.1177/019262339502300203.

Article  CAS  PubMed  Google Scholar 

van de Waterbeemd H, Smith DA, Beaumont K, Walker DK. Property-based design: optimization of drug absorption and pharmacokinetics. J Med Chem. 2001;44(9):1313–33. https://doi.org/10.1021/jm000407e.

Article  CAS  PubMed  Google Scholar 

Caldwell GW, Masucci JA, Yan Z, Hageman W. Allometric scaling of pharmacokinetic parameters in drug discovery: can human CL, Vss and t1/2 be predicted from in-vivo rat data? Eur J Drug Metab Pharmacokinet. 2004;29(2):133–43. https://doi.org/10.1007/bf03190588.

Article  CAS  PubMed  Google Scholar 

Huang Q, Riviere JE. The application of allometric scaling principles to predict pharmacokinetic parameters across species. Expert Opin Drug Metab Toxicol. 2014;10(9):1241–53. https://doi.org/10.1517/17425255.2014.934671.

Article  CAS  PubMed  Google Scholar 

Lin JH. Applications and limitations of interspecies scaling and in vitro extrapolation in pharmacokinetics. Drug Metab Dispos. 1998;26(12):1202–12.

CAS  PubMed  Google Scholar 

Riede J, Poller B, Umehara K-i, Huwyler J, Camenisch G. New IVIVE method for the prediction of total human clearance and relative elimination pathway contributions from in vitro hepatocyte and microsome data. Eur J Pharm Sci. 2016;86:96–102. https://doi.org/10.1016/j.ejps.2016.02.022.

Article  CAS  PubMed  Google Scholar 

Obach RS. Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes. Drug Metab Dispos. 1999;27(11):1350–9.

CAS  PubMed  Google Scholar 

Hallifax D, Foster JA, Houston JB. Prediction of human metabolic clearance from in vitro systems: retrospective analysis and prospective view. Pharm Res. 2010;27(10):2150–61. https://doi.org/10.1007/s11095-010-0218-3.

Article  CAS  PubMed  Google Scholar 

Hosea NA, Collard WT, Cole S, Maurer TS, Fang RX, Jones H, et al. Prediction of human pharmacokinetics from preclinical information: comparative accuracy of quantitative prediction approaches. J Clin Pharmacol. 2009;49(5):513–33.

Article  CAS  PubMed  Google Scholar 

Chen Y, Jin JY, Mukadam S, Malhi V, Kenny JR. Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies PROSPECTIVE Simcyp SIMULATION OF CLINICAL PK DATAY. CHEN ET AL. Biopharm Drug Dispos. 2012;33(2):85-98. https://doi.org/10.1002/bdd.1769.

Jones HM, Gardner IB, Watson KJ. Modelling and PBPK simulation in drug discovery. AAPS J. 2009;11(1):155–66. https://doi.org/10.1208/s12248-009-9088-1.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Davies M, Jones RDO, Grime K, Jansson-Lofmark R, Fretland AJ, Winiwarter S, et al. Improving the accuracy of predicted human pharmacokinetics: lessons learned from the AstraZeneca drug pipeline over two decades. Trends Pharmacol Sci. 2020;41(6):390–408. https://doi.org/10.1016/j.tips.2020.03.004.

Article  CAS  PubMed  Google Scholar 

Di L. The role of drug metabolizing enzymes in clearance. Expert Opin Drug Metab Toxicol. 2014;10(3):379–93. https://doi.org/10.1517/17425255.2014.876006.

Article  CAS  PubMed  Google Scholar 

Keefer C, Chang G, Carlo A, Novak JJ, Banker M, Carey J, et al. Mechanistic insights on clearance and inhibition discordance between liver microsomes and hepatocytes when clearance in liver microsomes is higher than in hepatocytes. Eur J Pharm Sci. 2020;155:105541. https://doi.org/10.1016/j.ejps.2020.105541.

Article  CAS  PubMed  Google Scholar 

Di L, Keefer C, Scott DO, Strelevitz TJ, Chang G, Bi Y-A, et al. Mechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design. Eur J Med Chem. 2012;57:441–8. https://doi.org/10.1016/j.ejmech.2012.06.043.

Article  CAS  PubMed  Google Scholar 

Di L, Trapa P, Obach RS, Atkinson K, Bi Y-A, Wolford AC, et al. A novel relay method for determining low-clearance values. Drug Metab Dispos. 2012;40(9):1860–5. https://doi.org/10.1124/dmd.112.046425.

Article  CAS  PubMed  Google Scholar 

Jones RS, Leung C, Chang JH, Brown S, Liu N, Yan Z, et al. Application of empirical scalars to enable early prediction of human hepatic clearance using in vitro-in vivo extrapolation in drug discovery: an evaluation of 173 drugs. Drug Metab Dispos. 2022;50(8):1053–63. https://doi.org/10.1124/dmd.121.000784.

Article  CAS  Google Scholar 

Chan TS, Yu H, Moore A, Khetani SR, Tweedie D. Meeting the challenge of predicting hepatic clearance of compounds slowly metabolized by cytochrome P450 using a novel hepatocyte model. HepatoPac Drug Metab Dispos. 2013;41(12):2024–32. https://doi.org/10.1124/dmd.113.053397.

Article  PubMed  Google Scholar 

Francis LJ, Houston JB, Hallifax D. Impact of plasma protein binding in drug clearance prediction: a database analysis of published studies and implications for in vitro-in vivo extrapolation. Drug Metab Dispos. 2021;49(3):188–201. https://doi.org/10.1124/dmd.120.000294.

Article  CAS  PubMed  Google Scholar 

Poulin P, Hop CECA, Ho Q, Halladay JS, Haddad S, Kenny JR. Comparative assessment of in vitro-in vivo extrapolation methods used for predicting hepatic metabolic clearance of drugs. J Pharm Sci. 2012;101(11):4308–26. https://doi.org/10.1002/jps.23288.

Article  CAS  PubMed  Google Scholar 

Poulin P, Haddad S. Toward a new paradigm for the efficient in vitro-in vivo extrapolation of metabolic clearance in humans from hepatocyte data. J Pharm Sci. 2013;102(9):3239–51. https://doi.org/10.1002/jps.23502.

Article  CAS  PubMed  Google Scholar 

Saravanakumar A, Sadighi A, Ryu R, Akhlaghi F. Physicochemical properties, biotransformation, and transport pathways of established and newly approved medications: a systematic review of the top 200 most prescribed drugs vs. the FDA-approved drugs between 2005 and 2016. Clin Pharmacokinet. 2019;58(10):1281–94. https://doi.org/10.1007/s40262-019-00750-8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Martignoni M, Groothuis GMM, de Kanter R. Species differences between mouse, rat, dog, monkey and human CYP-mediated drug metabolism, inhibition and induction. Expert Opin Drug Metab Toxicol. 2006;2(6):875–94. https://doi.org/10.1517/17425255.2.6.875.

Article  CAS  PubMed  Google Scholar 

Di L, Feng B, Goosen TC, Lai Y, Steyn SJ, Varma MV, et al. A perspective on the prediction of drug pharmacokinetics and disposition in drug research and development. Drug Metab Dispos. 2013;41(12):1975–93. https://doi.org/10.1124/dmd.113.054031.

Article  CAS  PubMed  Google Scholar 

Mathew S, Tess D, Burchett W, Chang G, Woody N, Keefer C, et al. Evaluation of prediction accuracy for volume of distribution in rat and human using in vitro, in vivo, PBPK and QSAR methods. J Pharm Sci (Philadelphia, PA, U S). 2021;110(4):1799–823. https://doi.org/10.1016/j.xphs.2020.12.005.

Article  CAS  Google Scholar 

Di L, Artursson P, Lennernas H, Avdeef A, Benet L, Houston B, et al. The critical role of passive permeability in designing successful drugs. ChemMedChem. 2020;15(20):1862–74. https://doi.org/10.1002/cmdc.202000419.

Article  CAS  PubMed  Google Scholar 

Di L, Rong H, Feng B. Demystifying brain penetration in central nervous system drug discovery. J Med Chem. 2013;56(1):2–12. https://doi.org/10.1021/jm301297f.

Article  CAS  PubMed  Google Scholar 

Nigade PB, Gundu J, Pai KS, Nemmani KVS, Talwar R. Prediction of volume of distribution in preclinical species and humans: application of simplified physiologically based algorithms. Xenobiotica. 2019;49(5):528–39. https://doi.org/10.1080/00498254.2018.1474399.

Article  CAS  PubMed  Google Scholar 

Jones RD, Jones HM, Rowland M, Gibson CR, Yates JWT, Chien JY, et al. PhRMA CPCDC initiative on predictive models of human pharmacokinetics, Part 2: Comparative assessment of prediction methods of human volume of distribution. J Pharm Sci. 2011;100(10):4074–89. https://doi.org/10.1002/jps.22553.

Article  CAS  PubMed  Google Scholar 

Price E, Kalvass JC, DeGoey D, Hosmane B, Doktor S, Desino K. Global analysis of models for predicting human absorption: QSAR, in vitro, and preclinical models. J Med Chem. 2021;64(13):9389–403. https://doi.org/10.1021/acs.jmedchem.1c00669.

Article  CAS  PubMed  Google Scholar 

Paine SW, Menochet K, Denton R, McGinnity DF, Riley RJ. Prediction of human renal clearance from preclinical species for a diverse set of drugs that exhibit both active secretion and net reabsorption. Drug Metab Dispos. 2011;39(6):1008–13. https://doi.org/10.1124/dmd.110.037267.

Article  CAS  PubMed  Google Scholar 

Mahmood I. Interspecies scaling of renally secreted drugs. Life Sci. 1998;63(26):2365–71. https://doi.org/10.1016/s0024-3205(98)00525-6.

Article  CAS  PubMed 

留言 (0)

沒有登入
gif