Mechanistic understanding of complex biological phenomena is needed at a system level to identify novel biomarkers that can be used for better diagnostics of a disease as well as determine the efficacy of therapeutics. Current in vitro and in vivo methods of biomarker identification take a reductionist approaches that slow the process of biomarker identification. PancreaSolve’s platform offers a revolutionary and proven integrative information-centric in silico platform that can accurately model complex molecular mechanisms and can be used for discovery of novel biomarkers.
In a recent, multi-institutional project conducted at MIT, Brighman and Women’s Hospital, Harvard Medical School and Kings College, London, PancreaSolve’s platform was used to model the shear stress induced nitric oxide production by computationally modeling and integrating all the mechanistic pathways involved in nitric oxide production in the endothelial cells. Model predicted results matched very closely to those measured in the in vitro experiments indicating that the models were able to simulate the mechanistic behavior of nitric oxide production in the endothelial cells. These results are a significant milestone in the field of computational systems biology.