CHEMSAS® is a multi-staged computational platform technology based upon a hybrid of machine learning technologies and proprietary algorithms that allow accurate prediction of biological activity from the molecular structure.
The series of proprietary algorithms are applied to complex 3D molecular structures to produce unique 2D data patterns composed of more than 250 descriptors. These unique 2D molecular data patterns are then used to develop hybrid predictive models relating molecular structure to specific target biological properties that traditionally require expensive and time consuming in vitro or in vivo tests. The final lead candidates are selected based on an optimal profile to probable physical chemical, biological, efficacy and ADMET properties.
To ensure that CHEMSAS remains a cutting edge technology, new and updated prediction models are being constantly added and refined. New molecules are continuously being added to the database and new in silico versions of tests and assays are also being developed in order to make CHEMSAS’ predictive capability as comprehensive as possible.
CHEMSAS helps create competitive advantage through accelerated identification of drug candidates. This faster time to market yields increased profits for each successful new drug by providing a longer revenue period through extended useful patent life. In addition to time savings, this rigorous scientific screening process allows customers to fill their pipelines with drug candidates that have a higher probability of clinical success.