PhRMA CPCDC Initiative on Predictive Models of Human Pharmacokinetics, Part 1: Goals, Properties of the PhRMA Dataset, and Comparison with Literature Datasets

被引：44

作者：

Poulin, Patrick ^{[1
]}

Jones, Hannah M. ^{[2
]}

Do Jones, Rhys ^{[3
]}

Yates, James W. T. ^{[3
]}

Gibson, Christopher R. ^{[4
]}

Chien, Jenny Y. ^{[5
]}

Ring, Barbara J. ^{[6
]}

Adkison, Kimberly K. ^{[7
]}

He, Handan ^{[8
]}

Vuppugalla, Ragini ^{[9
]}

Marathe, Punit ^{[9
]}

Fischer, Volker ^{[10
]}

Dutta, Sandeep ^{[11
]}

Sinha, Vikash K. ^{[12
]}

Bjornsson, Thorir ^{[13
]}

Lave, Thierry ^{[14
]}

Ku, M. Sherry ^{[15
]}

机构：

[1] Leader Consultant, Quebec City, PQ G1X 0A6, Canada

[2] Pfizer Ltd, Dept Pharmacokinet Dynam & Metab, Sandwich CT13 9NJ, Kent, England

[3] AstraZeneca Ltd, DMPK, Modeling & Simulat, Macclesfield SK10 3JL, Cheshire, England

[4] Merck Res Labs, West Point, PA 19525 USA

[5] Eli Lilly & Co, Lilly Res Labs, Global PK PD & Pharmacometr, Indianapolis, IN 46285 USA

[6] Eli Lilly & Co, Lilly Res Labs, Drug Disposit BR, Indianapolis, IN 46285 USA

[7] GlaxoSmithKline, Clin Pharmacol Modeling & Simulat, Res Triangle Pk, NC 27709 USA

[8] Novartis Inst Biomed Res, DMPK Translat Sci, E Hanover, NJ 07936 USA

[9] Bristol Myers Squibb Co, Metabolism & Pharmacokinet, Princeton, NJ 08543 USA

[10] DMPK, Abbott Pk, IL 60064 USA

[11] Global Pharma Res & Dev, Clin Pharmacol & Pharmacometr, Clin Pharmacokinet & Pharmacodynam, Abbott Pk, IL 60064 USA

[12] Janssen Res & Dev, Clin Pharmacol, Beerse, Belgium

[13] Crit Path Inst, Tucson, AZ 85718 USA

[14] F Hoffmann La Roche Ltd, Non Clin Drug Safety, CH-4070 Basel, Switzerland

[15] Anchen Pharmaceut Inc, Irvine, CA 92618 USA

来源：

JOURNAL OF PHARMACEUTICAL SCIENCES | 2011年 / 100卷 / 10期

关键词：

allometry; bioavailability; clearance; computational ADME; first-in-human; pharmacokinetics; oral absorption; PhRMA; PBPK; volume of distribution; HUMAN DRUG CLEARANCE; ANIMAL DATA; CLASSIFICATION; PARAMETERS;

D O I：

10.1002/jps.22554

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

This study is part of the Pharmaceutical Research and Manufacturers of America (PhRMA) initiative on predictive models of efficacy, safety, and compound properties. The overall goal of this part was to assess the predictability of human pharmacokinetics (PK) from preclinical data and to provide comparisons of available prediction methods from the literature, as appropriate, using a representative blinded dataset of drug candidates. The key objectives were to (i) appropriately assemble and blind a diverse dataset of in vitro, preclinical in vivo, and clinical data for multiple drug candidates, (ii) evaluate the dataset with empirical and physiological methodologies from the literature used to predict human PK properties and plasma concentration-time profiles, (iii) compare the predicted properties with the observed clinical data to assess the prediction accuracy using routine statistical techniques and to evaluate prediction method(s) based on the degree of accuracy of each prediction method, and (iv) compile and summarize results for publication. Another objective was to provide a mechanistic understanding as to why one methodology provided better predictions than another, after analyzing the poor predictions. A total of 108 clinical lead compounds were collected from 12 PhRMA member companies. This dataset contains intravenous (n = 19) and oral pharmacokinetic data (n = 107) in humans as well as the corresponding preclinical in vitro, in vivo, and physicochemical data. All data were blinded to protect the anonymity of both the data and the company submitting the data. This manuscript, which is the first of a series of manuscripts, summarizes the PhRMA initiative and the 108 compound dataset. More details on the predictability of each method are reported in companion manuscripts. (C) 2011 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 100: 4050-4073, 2011

引用

页码：4050 / 4073

页数：24

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