Prediction of Drug Half-life Values of Antihistamines Based on the CODES/Neural Network Model

Abstract

The CODES/neural network model has been successfully applied to the prediction of pharmacokinetic properties of therapeutical compounds. The output of CODES, a graphical module based on the Gestalt isomorphism, is proved to be a valuable tool in the design of a neural network model able to predict the half-life values of antihistamines. Additionally, the generated models are able to classify these drugs in their corresponding therapeutic category (H1 or H2 receptor antagonists).