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Use of In Vitro Drug Metabolism Data to Evaluate Metabolic Drug‐Drug Interactions in Man: The Need for Quantitative Databases
Author(s) -
Rodrigues A. David,
Winchell Gregory A.,
Dobrinska Michael R.
Publication year - 2001
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1177/00912700122010212
Subject(s) - adme , drug , in vivo , pharmacology , pharmacokinetics , cyp3a4 , drug metabolism , cytochrome p450 , chemistry , database , drug interaction , cyp2d6 , distribution (mathematics) , metabolism , potency , drug discovery , in vitro , biology , biochemistry , computer science , mathematical analysis , microbiology and biotechnology , mathematics
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, K i ), the concentration of the inhibitor available for inhibition ([I]), the fraction of the substrate dose metabolized by CYP (f m ), and the fraction of the CYP‐dependent metabolism catalyzed by the inhibited CYP form (e.g., f m,CYP3A4 ). While progress is being made toward our understanding of the factors necessary for predictions of [I]/K i in vivo, it is evident that there is a need for quantitative databases that contain in vitro (e.g., K i , f m,CYP3A4 ) and in vivo pharmacokinetic/absorption‐distribution‐metabolism‐excretion (PK/ADME) data (e.g., f m ) 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.