Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2002 Sep;91(9):1923-35.
doi: 10.1002/jps.10179.

Inhibition-based metabolic drug-drug interactions: predictions from in vitro data

Affiliations
Review

Inhibition-based metabolic drug-drug interactions: predictions from in vitro data

Caiping Yao et al. J Pharm Sci. 2002 Sep.

Abstract

There has been a growing interest in predicting in vivo metabolic drug-drug interactions from in vitro systems. High-throughput screening methods aimed at assessing the potential of drug candidates for drug interactions are widely used in industry. However, at present, there is no consensus on methodologies that would yield reliable quantitative predictions, because a number of issues remain unsolved, such as estimations of inhibition constants in vitro and inhibitor concentration around the enzyme site in vivo. In the present review, different approaches to estimation of inhibitor concentration around the enzyme site are summarized; also, the problems associated with estimation of in vitro K(i) values due to incubation conditions and environment differences between in vitro and in vivo are presented. A new approach based on comparisons of in vitro and in vivo inhibition potencies by calculation of in vivo inhibition constants is discussed. Examples of predictions of in vivo drug interactions based on mechanism-based inactivation are described. Unresolved issues that would allow further refinement of existing prediction models are also evaluated.

PubMed Disclaimer

Publication types

Substances

LinkOut - more resources