CODES/Neural Network Model: a Useful Tool for in Silico Prediction of Oral Absorption and Blood‐Brain Barrier Permeability of Structurally Diverse Drugs

Two different neural network models able to predict both oral absorption (OA) and blood‐brain barrier (BBB) permeability of structurally diverse drugs in use clinically are presented here. Using the descriptors generated by CODES, a program which codifies molecules from a topological point of view, we avoid the uncertain choice of molecular conformation and physicochemical parameters. In this work, a method called Reduction of Dimensions, designed for compressing data, is applied for the first time in order to minimize the bias factor added to a QSAR study when the selection of descriptors are performed.