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Computational models

In silico prediction of drug toxicity based on effective plasma concentration

A logistic regression model based on effective plasma concentration (Ceff) of a compound could provide an in silico measure for predicting toxicity. In silico analysis compared the physicochemical and pharmacological characteristics of 56 compounds that had advanced to preclinical exploratory toxicology studies (ETS) and were classified as 'pass' or 'fail' for toxicity based on therapeutic index ratios from in vivo studies. ETS pass outcomes correlated significantly with Ceff values lower than 250 nM
for total drug (p<0.0001) and 40 nM for free drug (p=0.0532). In logistic regression analysis, a Ceff of 1 nM for total drug yielded over 80% probability of success for an ETS pass outcome, whereas a Ceff of 1 mm yielded 20% probability of success. Next steps could include expanding the model to incorporate in vitro cell-based assay data and other less expensive in vivo screening data endpoints.

SciBX 7(1); doi:10.1038/scibx.2014.33
Published online Jan. 9, 2014

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Wager, T.T. et al. J. Med. Chem.; published online Nov. 12, 2013;
Contact: Travis T. Wager, Pfizer Worldwide Research and Development, Cambridge, Mass.