Predicting Adverse Drug Reactions: What Works and What Doesn’t
Dr Nigel Green, Pfizer, gave this presentation at the “Guiding Optimal Compound Design and Development Symposium” held in Cambridge, MA, USA on 19 March 2015.
The ability to predict the adverse safety effects of small molecules has long been an aspiration in the pharmaceutical industry as it offers the advantage of lowering costs associated with the identification of candidate drugs whilst increasing the speed of development. Numerous methods and approaches to predicting adverse events have been developed but computational models that utilize physicochemical properties, structural alerts, polypharmacology assessments and mechanistic in vitro assays offer the most promise. One such approach is now being used to help guide early medicinal chemistry efforts and can be built into product development strategies to mitigate unwanted health effects in drug candidates that ultimately go to commercialization. By combining these diverse data types in an optimized, holistic model, a prediction of the exposure at which a compound may demonstrate a threshold level of toxicity in an in vivo study can be made. By combining this prediction with assessments of projected efficacious concentrations some success has been achieved in predicting the likely therapeutic index of a novel molecule. The use of such approaches allows medicinal chemists to steer early design efforts away from unproductive space, potentially reducing the use of in vivo experimentation for compounds with no hope of success.
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