Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches.

ABSTRACT: PURPOSE:Oral bioavailability (%F) is a key factor that determines the fate of a new drug in clinical trials. Traditionally, %F is measured using costly and time-consuming experimental tests. Developing computational models to evaluate the %F of new drugs before they are synthesized would be beneficial in the drug discovery process. METHODS:We employed Combinatorial Quantitative Structure-Activity Relationship approach to develop several computational %F models. We compiled a %F dataset of 995 drugs from public sources. After generating chemical descriptors for each compound, we used random forest, support vector machine, k nearest neighbor, and CASE Ultra to develop the relevant QSAR models. The resulting models were validated using five-fold cross-validation. RESULTS:The external predictivity of %F values was poor (R(2)?=?0.28, n?=?995, MAE?=?24), but was improved (R(2)?=?0.40, n?=?362, MAE?=?21) by filtering unreliable predictions that had a high probability of interacting with MDR1 and MRP2 transporters. Furthermore, classifying the compounds according to the %F values (%F?

SUBMITTER: Kim MT 

PROVIDER: S-EPMC3955412 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature