In the last 10 years, genomic and proteomic technologies have been applied to identify and develop a new generation of diabetes treatments. While these technologies have become increasingly automated, producing a deluge of potential therapeutic targets and biological insights, projections estimate that individual drug development time and cost will continue to rise and soon exceed 1 billion USD. A significant contributor to this rising cost is the large number of compounds that fail in the clinic following years of pre-clinical development. A biological context is necessary to integrate the dynamic interactions of the regulatory mechanisms that distinguish health from disease and subsequently predict therapeutic outcomes. This is missing in today's data-intensive approach. Biosimulation, also termed computer modelling or in silico biology, is a systems-biology solution to this problem – using the abundance of diverse data to build a dynamic model of human physiology.
Biosimulation, Computer modelling, Insulin, Entelos