Small- and large-scale biosimulation applied to drug discovery and development

Biosimulation uses mathematics to quantitatively represent the dynamics of biological systems and thereby analyze and predict system behavior. Biosimulations can be classified into two general categories: small-scale models designed to address a specific problem, and large-scale models of detailed regulatory mechanisms used to address a broad scope of questions. Both classes of biosimulations have been applied to problems important for drug discovery and development. Small-scale biosimulations have been particularly useful for interpreting clinical data and developing novel biomarkers. Large-scale biosimulations typically integrate a wide variety of data and can provide insights into how complex biological systems are regulated in both health and disease. Because large-scale biosimulations represent detailed regulatory mechanisms and their interactions, they can predict the overall clinical effect of modulating individual pathways or targets. In this mini-review, we describe several examples of how small- and large-scale biosimulations have been applied to problems important for drug development in diabetes, HIV, heart disease and asthma.