A Machine Learning Model to Predict Drug Transfer Across the Human Placenta Barrier.

ABSTRACT: The development of computational models for assessing the transfer of chemicals across the placental membrane would be of the utmost importance in drug discovery campaigns, in order to develop safe therapeutic options. We have developed a low-dimensional machine learning model capable of classifying compounds according to whether they can cross or not the placental barrier. To this aim, we compiled a database of 248 compounds with experimental information about their placental transfer, characterizing each compound with a set of ∼5.4 thousand descriptors, including physicochemical properties and structural features. We evaluated different machine learning classifiers and implemented a genetic algorithm, in a five cross validation scheme, to perform feature selection. The optimization was g

SUBMITTER: Di Filippo JI 

PROVIDER: S-EPMC8329444 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature