QUANTITATIVE MEDICINE

Quantitative Medicine's Computational Research Engine™ (CoRE™) is a dynamic and comprehensive in silico predictive modeling platform for constructing, assessing, validating and deploying exceedingly accurate predictive models to efficiently guide the testing process and solve complex drug discovery optimization problems. CoRE™ applies cutting edge machine learning techniques from three complementary informatics technologies: Supervised Learning, Transfer Learning and Active Learning, to ef... ficiently solve multi-parameter optimization problems in a series of discrete discovery cycles. CoRE’s unique capability to effect simultaneous co-optimization of the entire efficacy, safety and off-target effects property profile is vastly more efficient than the standard approach and greatly accelerates discovery. Based on over 20 industry collaborations, it is very realistic to expect, at a minimum, CoRE™ can reduce preclinical attrition 5%, preclinical costs 20% and lead optimization costs 40%. When these three parameters were adjusted in a recent assessment of pharmaceutical R&D productivity (Paul et al. 2010 ) to capture the effects of using CoRE™, this translated to capitalized costs savings of $238 million and out-of-pocket cost reductions of $88 million. Additionally, CoRE™ can quickly yield significant reductions in time which may be instrumental in gaining first mover IP advantage, particularly with novel targets. The Revolutionary CoRE™ Platform Changes How Predictive In Silico Models Are Generated and Deployed, and How Highly Accurate Predictive Models Enable and Accelerate Efficient Drug Discovery. The net result is a game changing competitive advantage.More