Systems biology in disease modeling and control, analysis and perspectives

Abstract

Omics and drug molecules become increasingly influential in identifying disease mechanisms and drug response. Because diseases and drug responses are co-expressed and regulated in the relevant omics interactions, the traditional way that grabbing molecular data from single isolated layers cannot always obtain valuable inference. Also, adverse effects exist in drugs that impair patients, and launching new medicines for diseases is costly. To resolve the above difficulties, systems biology is then applied to predict potential molecular interaction elements by integrating omics data from genomic, proteomic, transcriptional, and metabolic layers. Combined with known drug reactions, the resulting models improve medicines’ therapeutical performance by re-purposing the existing drugs and combining drug molecules without off-target effects. Based on the identified computational models, drug administration control laws are designed to balance toxicity and efficacy. This review introduces biomedical applications and analyses of interactions among omics and drug molecules for modeling disease mechanism and drug response. The therapeutical performance can be improved by combining the predictive and computational models with drug administration designed by control laws. The challenges are discussed for its clinic uses.