The Impact of Computational Drug Discovery on Society

Abstract

Network pharmacology and deep learning-based approaches have significantly advanced the field of drug discovery. With the improved prediction accuracy on drug targets, a logical next step would be the modeling of the complexity of human biology to understand the heterogeneity of drug response across individual patients and suggest novel treatment options for non responders. To ensure the successful translation of the computer-aided models into drug development and treatment decision-making, it is imperative to refine our models to predict drug-target interactions within specific disease contexts and ultimately to personalize these predictions for each patient.