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    NOV 2017
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Profilling potential drug-induced hepatotoxicity thorugh modelling molecular initiating events (MIEs)

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Drug-induced liver injury is reported as a major cause of serious adverse effects, and has led to the withdrawal of a significant number of marketed drugs. During drug development, considerable effort is made to identify chemicals with hepatotoxic potential. Current testing strategies involve screening for possible undesirable interactions of drug candidates with multiple relevant subcellular targets. The initial interaction of the chemical with a subcellular target triggering the chain of events, leading to an adverse effect, is referred to as the molecular initiating event (MIE).

During this research a number of MIEs relevant for hepatotoxicity were identified and include such targets as hepatic transporters, nuclear receptors and mitochondrial elements. Datasets reflective of each MIE were compiled from various public sources. Several approaches were investigated for the modelling of MIEs including machine-leaning methods (k-nearest neighbours, random forest, decision tree) and expert analysis of chemical structure. A selection of these models were incorporated into a hepatotoxicity profiler, where the overall hepatotoxic potential of a compound is derived from the predictions of individual MIE models. This profiler was evaluated using an in vivo human hepatotoxicity dataset assembled from multiple sources.

This talk, presented at the 2017 IVTS meeting, will touch on the details of data compilation, its modelability and vision for the applicability of the profiler in drug discovery settings.


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