CytoSolve is based on computational biology. This is a field in rapid transition from diagrammatic representation of pathways to quantitative and predictive mathematical models that span time-scales, knowledge domains and spatial-scales. This transition is being accelerated by high-throughput experimentation which isolates reactions and their corresponding rate constants.
Biomolecular pathways are building blocks of cellular biochemical function. CytoSolve offers a new system for integrating an ensemble of such distributed biochemical network models. Rapid growth in the number of biochemical network models, created in different formats, across different computing systems, with minimal input and output information, necessitates the need for such a system in order to build large scale models in a flexible and scalable manner.
Using CytoSolve, complex molecular pathway models have been tested and built for EGFR, nitric oxide and Interferon (IFN) pathways. Without CytoSolve, the integration of complex molecular pathway models is largely manual, time-consuming and in many cases, not possible.
The platform uses in-silico modeling to bridge in-vitro testing with human clinical trials with the goal of eliminating animal experimentation. It can be used for drug development in the fields of vaccines, liver cancer and heart disease. It also provides opportunities for commercial companies such as biotech and pharmaceutical companies to work to use the CytoSolve platform for supporting their internal drug development process.
