SC3.1 Predicting Metabolism-Mediated Toxicities of Drug Candidates

Amit S. S Kalgutkar , Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Cambridge, MA

Reliably predicting the occurrence of idiosyncratic adverse drug reactions (IADRs) for new drug candidates continues to present a significant challenge in preclinical discovery. Many IADRs possess an immune component and occur in only a subset of patients either acutely or as a delayed response.  IADRs can manifest as a rare and sometimes life-threatening reaction in drug-treated patients that cannot be explained based on the primary pharmacology of the drug. Because the frequency of occurrence in patients is very low, these reactions are often not detected until the drug has gained broad exposure in a large patient population. Because of the inability to predict and quantify the risk of IADRs and because reactive metabolites (RMs) are thought to be responsible for the pathogenesis of some IADRs, the potential for RM formation within new chemical entities is routinely examined with the ultimate goal of eliminating or reducing the liability through iterative design. Likewise, avoidance of structural alerts is almost a standard practice in drug design. However, the perceived safety concerns associated with the use of structural alerts and/or RM screening tools as standalone predictors of toxicity risks may be overexaggerated. Numerous marketed drugs form RMs but do not cause idiosyncratic toxicity. A critical analysis of the structural alert/RM concept as applied in drug discovery and evaluation of the evidence linking structural alerts and RMs to IADRs will be presented. Pragmatic risk mitigation strategies to aid the advancement of drug candidates that carry a RM liability will also be discussed.