Chapter 3.1 - Towards Translational Systems Biology of Inflammation

Abstract

Having introduced the historical, methodological, procedural, and societal antecedents that have contributed to the Translational Dilemma, in this chapter we propose our strategy to overcoming the challenges associated with the Dilemma, a research program we call Translational Systems Biology. This investigative strategy is predicated on the use of dynamic computational modeling and associated computational methods of data analysis and aggregation to accelerate the Scientific Cycle with an explicit target of generating clinically actionable knowledge. Translational Systems Biology is firmly grounded in the fundamental scientific principles discussed in earlier chapters, with its computational component specifically designed to overcome the numerous factors previously identified as contributing to the Translational Dilemma. These factors include the challenge of integrating and synthesizing mechanistic knowledge in systems with known nonlinear dynamics, utilizing and analyzing high-throughput data in a manner that facilitates the construction and use of dynamic computational models, the use of computational models as means of dynamic knowledge representation to test and falsify mechanistic hypotheses, and the use of computational modeling to bridge experimental biology to clinical application through the execution of in silico clinical trials.