TY - JOUR T1 - A Pharmacokinetic Modeling Approach to Predict the Contribution of Active Metabolites to Human Efficacious Dose JF - Drug Metabolism and Disposition JO - Drug Metab Dispos SP - 1435 LP - 1440 DO - 10.1124/dmd.116.070391 VL - 44 IS - 8 AU - Iain J. Martin AU - Susan E. Hill AU - James A. Baker AU - Sujal V. Deshmukh AU - Erin F. Mulrooney Y1 - 2016/08/01 UR - http://dmd.aspetjournals.org/content/44/8/1435.abstract N2 - A preclinical drug candidate, MRK-1 (Merck candidate drug parent compound), was found to elicit tumor regression in a mouse xenograft model. Analysis of samples from these studies revealed significant levels of two circulating metabolites, whose identities were confirmed by comparison with authentic standards using liquid chromatography-tandem mass spectrometry. These metabolites were found to have an in vitro potency similar to that of MRK-1 against the pharmacological target and were therefore thought to contribute to the observed efficacy. To predict this contribution in humans, a pharmacokinetic (PK) modeling approach was developed. At the mouse efficacious dose, the areas under the plasma concentration time curves (AUCs) of the active metabolites were normalized by their in vitro potency compared with MRK-1. These normalized metabolite AUCs were added to that of MRK-1 to yield a composite efficacious unbound AUC, expressed as “parent drug equivalents,” which was used as the target AUC for predictions of the human efficacious dose. In vitro and preclinical PK studies afforded predictions of the PK of MRK-1 and the two active metabolites in human as well as the relative pathway flux to each metabolite. These were used to construct a PK model (Berkeley Madonna, version 8.3.18; Berkeley Madonna Inc., University of California, Berkeley, CA) and to predict the human dose required to achieve the target parent equivalent exposure. These predictions were used to inform on the feasibility of the human dose in terms of size, frequency, formulation, and likely safety margins, as well as to aid in the design of preclinical safety studies. ER -