Computer-aided drug discovery for pathway and genetic diseases

Selecting drug targets in pathway and genetic diseases (e.g., cancer) is a difficult problem facing the medical field and pharmaceutical industry. Because of the complex interconnections and feedback found in biological pathways, it is difficult to understand the potential effects of targeting certain portions of the network. The pharmaceutical industry has avoided novel targets for drugs, largely because of the increased risk in developing such treatments. This necessitates the need for systems biology methods which can help mitigate some of the risks of identifying novel targets and also suggest further experiments to validate them. The primary goal of this paper is to introduce a mathematical framework for solving such problems, that is amenable to computational or mathematical study. The secondary goal is to suggest methods for solving problems posed in this framework. One of these methods is a heuristic which is designed to allow its computations to scale up to much bigger examples and pathways than presented here.