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Optimizing Classification of Drug-Drug Interaction Potential for CYP450 Isoenzyme Inhibition Assays in Early Drug Discovery

Freie Universität Berlin, Department of Mathematics and Computer Science, Berlin, and International Max-Planck Research School CBSC, Berlin, Germany

Philip Lienau

Andreas Reichel

Schering AG, Department of Research Pharmacokinetics, Berlin, Germany

Wilhelm Huisinga

Freie Universität Berlin, Department of Mathematics and Computer Science, Berlin, and DFG Research Center MATHEON, Berlin, Germany

In drug discovery, the potential of cytochrome P450 inhibition of new chemical entities is frequently quantified in terms of IC₅₀ values. In early drug discovery, a risk classification into low, medium, or high potential inhibitors is often sufficient for ranking and prioritizing of compounds. Although often 6 or more inhibitor concentrations are used to determine the IC₅₀ value, the question arises whether it is possible to predict the risk class based on fewer inhibitor concentrations with comparable reliability. In this article, the authors propose a new integrated 2-point method with inhibitor concentrations chosen in accordance with the risk classification. They analyze its predictive power and the feasibility of not only classifying the compounds into different risk classes but also ranking those compounds that have been binned into the middle risk class. The proposed integrated 2-point method is thus highly suitable for automation. Altogether, it maintains the quality of the prediction while considerably reducing time and cost. The proposed method is applicable to other IC₅₀ assays and risk classifications.

Key Words: drug-drug interaction • cytochrome P450 • drug discovery • high throughput • IC50

This version was published on February 1, 2007

Journal of Biomolecular Screening, Vol. 12, No. 1, 92-99 (2007)
DOI: 10.1177/1087057106295897


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