On the use of machine learning methods for modern drug discovery

Abstract

Machine learning techniques provide a strong basis for enhancing the process of drug discovery within the pharmaceutical industry. During the last decade, chemoinformatics – briefly defined as informatics applied on chemical data – has gained much importance due to the economical benefits obtained from the application of in silico (i.e., computer-based) models. Prediction of candidate compounds for medicinal use is a hard task due to the complex and usually unknown relationships between structure and biological properties. This short article aims at summarizing the main contributions of a PhD thesis [PhD thesis, Universidad Nacional del Sur, Argentina, 2010] and, at the same time, at encouraging research on this challenging area.