Literature DB >> 15886285

Predicting inhibitory drug-drug interactions and evaluating drug interaction reports using inhibition constants.

Kenneth A Bachmann1, Jeffrey D Lewis.   

Abstract

OBJECTIVE: To review the use of inhibitory constants (Ki) determined from in vitro experiments in the prediction of the significance of inhibitory drug-drug interactions (DDIs). DATA SOURCES: Searches of MEDLINE (1966-August 2004) and manual review of journals, conference proceedings, reference textbooks, and Web sites were performed using the key search terms cytochrome P450, drug-drug interaction, inhibition constant, and Ki. STUDY SELECTION AND DATA EXTRACTION: All articles identified from the data sources were evaluated, and information deemed relevant was included for this review. DATA SYNTHESIS: The cytochrome P450 isoenzymes factor prominently in the explanation of numerous DDIs. Although the regulation of these enzymes by one drug can affect the pharmacokinetics of other drugs, the consequences may not necessarily be significant either in terms of pharmacokinetic or clinical outcomes. Yet, many DDI monographs originate as unconfirmed case reports that implicate the influence of one drug on the CYP-mediated metabolism of another, and these often uncorroborated mechanisms can eventually become regarded as dogma. One consequence of this process is the over-prediction of potentially important DDIs. The pharmaceutical industry, Food and Drug Administration, and pharmaceutical scientists have developed a strategy for predicting the significance of inhibitory DDIs at the earliest possible stages of drug development based on a new chemical entity's Ki value, determined in vitro.
CONCLUSIONS: We suggest that the use of Ki values of drugs purported to behave as CYP inhibitors be incorporated in the assessment of case reports that ascribe DDIs to inhibition of metabolism of one drug by another.

Mesh:

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Year:  2005        PMID: 15886285     DOI: 10.1345/aph.1E508

Source DB:  PubMed          Journal:  Ann Pharmacother        ISSN: 1060-0280            Impact factor:   3.154


  15 in total

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Authors:  Y H Choi; S J Chung; M G Lee
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