Literature DB >> 11304892

Use of in vitro drug metabolism data to evaluate metabolic drug-drug interactions in man: the need for quantitative databases.

A D Rodrigues1, G A Winchell, M R Dobrinska.   

Abstract

It has become widely accepted that metabolic drug-drug interactions can be forecast using in vitro cytochrome P450 (CYP) data. For any CYP form-inhibitor pair, the magnitude of the interaction will depend on the potency of the inhibitor (inhibition constant, Ki) the concentration of the inhibitor available for inhibition ([I]), the fraction of the substrate dose metabolized by CYP (fm), and the fraction of the CYP-dependent metabolism catalyzed by the inhibited CYP form (e.g., fm,CYP3A4). While progress is being made toward our understanding of the factors necessary for predictions of [I]/Ki in vivo, it is evident that there is a need for quantitative databases that contain in vitro (e.g., Ki, fm,CYP3A4) and in vivo pharmacokinetic/absorption-distribution-metabolism-excretion (PK/ADME) data (e.g., fm) for a large number of marketed drugs. Ultimately, such databases would allow one to integrate all of the data necessary for the prediction of drug-drug interactions and permit the rational evaluation of new drug entities.

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Year:  2001        PMID: 11304892     DOI: 10.1177/00912700122010212

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  3 in total

Review 1.  Database analyses for the prediction of in vivo drug-drug interactions from in vitro data.

Authors:  Kiyomi Ito; Hayley S Brown; J Brian Houston
Journal:  Br J Clin Pharmacol       Date:  2004-04       Impact factor: 4.335

2.  Identification of intestinal loss of a drug through physiologically based pharmacokinetic simulation of plasma concentration-time profiles.

Authors:  Sheila Annie Peters
Journal:  Clin Pharmacokinet       Date:  2008       Impact factor: 6.447

3.  The Cancer Drug Fraction of Metabolism Database.

Authors:  Liyan Hua; Chien-Wei Chiang; Wang Cong; Jin Li; Xueying Wang; Lijun Cheng; Weixing Feng; Sara K Quinney; Lei Wang; Lang Li
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-06-17
  3 in total

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