NetTargets develops large-scale computational models of life systems based on integrated experimental evidences and provides the most promising drug targets and materials.
Finding paths in a black box
How a drug works in a human body is often described as a black box. Because no one has a clear holistic understanding of this black box, drug discovery processes were dependent on dispersed/fragmented knowledge about human body and heuristic judgements.
Our research platform powered by systems biology and machine learning compiles chemical, biological, experimental, and clinical data to create a large complex network model. Then, the network model is investigated on computer to discover novel therapeutic mechanisms.
Once a mathematical model has been developed that represents the biological phenomena of the disease, we can run various virtual experiments on a computer. We plug the mathematical model into our research platform and then perform various virtual perturbation experiments. After running a large computer simulation, we find out the most efficient paths to identify promising novel drug targets and materials.
With a mechanism-based white box approach, we clarify hidden mechanisms such as undesired feedbacks or crosstalks, and discover novel targets in the most cost-effective way.