Literature DB >> 17268485

Simulation and prediction of in vivo drug metabolism in human populations from in vitro data.

Amin Rostami-Hodjegan1, Geoffrey T Tucker.   

Abstract

The perceived failure of new drug development has been blamed on deficiencies in in vivo studies of drug efficacy and safety. Prior simulation of the potential exposure of different individuals to a given dose might help to improve the design of such studies. This should also help researchers to focus on the characteristics of individuals who present with extreme reactions to therapy. An effort to build virtual populations using extensive demographic, physiological, genomic and in vitro biochemical data to simulate and predict drug disposition from routinely collected in vitro data is outlined.

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Year:  2007        PMID: 17268485     DOI: 10.1038/nrd2173

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN: 1474-1776            Impact factor:   84.694


  124 in total

1.  A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs.

Authors:  Karthik Venkatakrishnan; Michael D Pickard; Lisa L von Moltke
Journal:  Clin Pharmacokinet       Date:  2010-11       Impact factor: 6.447

2.  Incorporating human dosimetry and exposure into high-throughput in vitro toxicity screening.

Authors:  Daniel M Rotroff; Barbara A Wetmore; David J Dix; Stephen S Ferguson; Harvey J Clewell; Keith A Houck; Edward L Lecluyse; Melvin E Andersen; Richard S Judson; Cornelia M Smith; Mark A Sochaski; Robert J Kavlock; Frank Boellmann; Matthew T Martin; David M Reif; John F Wambaugh; Russell S Thomas
Journal:  Toxicol Sci       Date:  2010-07-16       Impact factor: 4.849

Review 3.  Quantitative clinical pharmacology is transforming drug regulation.

Authors:  Carl C Peck
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-10-27       Impact factor: 2.745

4.  Assessment of algorithms for predicting drug-drug interactions via inhibition mechanisms: comparison of dynamic and static models.

Authors:  Eleanor J Guest; Karen Rowland-Yeo; Amin Rostami-Hodjegan; Geoffrey T Tucker; J Brian Houston; Aleksandra Galetin
Journal:  Br J Clin Pharmacol       Date:  2011-01       Impact factor: 4.335

5.  An improved nonlinear model describing the hepatic pharmacokinetics of digoxin: evidence for two functionally different uptake systems and saturable binding.

Authors:  Michael Weiss; Peng Li; Michael S Roberts
Journal:  Pharm Res       Date:  2010-07-13       Impact factor: 4.200

6.  A pregnancy physiologically based pharmacokinetic (p-PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4.

Authors:  Lu Gaohua; Khaled Abduljalil; Masoud Jamei; Trevor N Johnson; Amin Rostami-Hodjegan
Journal:  Br J Clin Pharmacol       Date:  2012-11       Impact factor: 4.335

Review 7.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

8.  A semi-mechanistic model to predict the effects of liver cirrhosis on drug clearance.

Authors:  Trevor N Johnson; Koen Boussery; Karen Rowland-Yeo; Geoffrey T Tucker; Amin Rostami-Hodjegan
Journal:  Clin Pharmacokinet       Date:  2010-03       Impact factor: 6.447

9.  Structure-based prediction of the nonspecific binding of drugs to hepatic microsomes.

Authors:  Haiyan Li; Jin Sun; Xiaofan Sui; Zhongtian Yan; Yinghua Sun; Xiaohong Liu; Yongjun Wang; Zhonggui He
Journal:  AAPS J       Date:  2009-05-14       Impact factor: 4.009

Review 10.  The role of CYP26 enzymes in retinoic acid clearance.

Authors:  Jayne E Thatcher; Nina Isoherranen
Journal:  Expert Opin Drug Metab Toxicol       Date:  2009-08       Impact factor: 4.481

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