Data Mining for Rational Drug Design

Abstract

Currently, there are a large number of drugs available that promote greater efficiency in health systems and are an asset to the health of the population. Its importance is indisputable to human life and consequently translates into greater competence at the professional level, bringing many benefits to society. In addition, the conscious use of medicines also leads to a decreasing need for other, longer and more expensive health care. The process of drug design consists of several steps until reaching the final phase that corresponds to the clinical tests. One of the process steps consists on testing five important properties of a drug, known as ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) tests. The work of this dissertation consists in the study of Data Mining techniques and evaluation of its potentialities to improve the process of development of new drugs, in particular to contribute to the improvement and reduction of the costs of ADMET tests