Quantitative Medicine is a biomedical analytics and computational biology company offering a novel drug discovery platform which dramatically reduces the time, cost and financial risk of discovering new therapeutic drugs by predicting: the main effects of drugs on target molecules that mediate disease; the effects of drugs on other molecules or pathways in the body that could mediate adverse effects; as well as the interaction of these with underlying genetic variations. The platform identifies similarities in relationships of drug candidates screened against a diverse matrix of pathogenic, cellular, molecular and/or systems biology targets. By iteratively adding new data from other existing research or additional experiments, the predictive model is improved. More accurate predictions can be made for previously unobserved effects of putative compounds on target molecules. “Because of the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug discovery and development. In particular …active learning methods to guide experimentation will be required to overcome dimensionality problem in drug development.” -- Robert F. Murphy, Department Head of the Computational Biology Department at Carnegie Mellon University and a Founder of Quantitative Medicine.