TY - JOUR T1 - Drug Metabolites as Cytochrome P450 Inhibitors: A Retrospective Analysis and Proposed Algorithm for Evaluation of the Pharmacokinetic Interaction Potential of Metabolites in Drug Discovery and Development JF - Drug Metabolism and Disposition JO - Drug Metab Dispos SP - 2047 LP - 2055 DO - 10.1124/dmd.113.052241 VL - 41 IS - 12 AU - Ernesto Callegari AU - Amit S. Kalgutkar AU - Louis Leung AU - R. Scott Obach AU - David R. Plowchalk AU - Susanna Tse Y1 - 2013/12/01 UR - http://dmd.aspetjournals.org/content/41/12/2047.abstract N2 - Understanding drug-drug interactions (DDIs) is a key component of clinical practice ensuring patient safety and efficacy of medicines. The role of drug metabolites in DDIs is a developing area of science, and has been recently highlighted in a draft regulatory guidance. The guidance states that metabolites representing ≥25% of the parent drug’s area under the plasma concentration/time curve and/or >10% of exposure of total drug-related material should trigger in vitro characterization of metabolites for cytochrome P450 inhibition and propensity for DDIs. The relationship between in vitro cytochrome P450 inhibitory potency, systemic exposure, and DDI potential of drug metabolites was examined using the Pfizer development database to identify compounds with pre-existing in vivo biotransformation data, where circulating metabolites were identified in humans. The database yielded 33 structurally diverse compounds with collectively 115 distinct circulating metabolites. Of these, 52% (60/115) achieved exposures >25% of parent drug levels as judged from mass balance/metabolite identification studies. It was noted that 14 metabolite standards for 12 parent drugs had been synthesized, monitored in clinical studies, and examined for cytochrome P450 inhibition. For the 14 metabolite/parent drug pairs, no clinically relevant DDIs were expected to occur against the major human cytochrome P450 isoforms. A review of the literature for parent/metabolite DDI information was also conducted to examine trends using a larger data set. Leveraging the analysis of both internal and literature-based data sets, an algorithm was devised for use in drug discovery/early development to assess cytochrome P450 inhibitory potential of drug metabolites and the propensity to cause a clinically relevant DDI. ER -