The future of drug discovery.

"Whether scientist or artist or mystic, we are stunned by the beauty and the complexity of what we see. But whether we look with the eyes of science or religion, we see order and lawfulness underlying superficial complexity."

. . . J.S. Lewis


COTI has developed a proprietary process, CHEMSASŪ, based upon a hybrid of artificial intelligence software and proprietary algorithms that allow accurate prediction of biological activity from molecular structure. The CHEMSAS system is based upon breaking complex molecular structures down into descriptive critical elements that can be used to model specific in vitro and in vivo biological activities in a two stage process. First, the prediction model is developed with information about molecules with known activities for the therapeutic target. Then, molecules with unknown activities are entered in to the prediction model system and their activity profiles for the same therapeutic target(s) are determined.

The CHEMSAS process can be used to model and optimize specific desirable biological activities of molecules. By profiling molecules for (i) efficacy against specific targets, (ii) pharmacokinetic properties (e.g., absorption, distribution, metabolism, excretion ("ADME")), (iii) Cytochrome P450 metabolic interactions, (iv) acute in vivo (animal) intra-peritoneal and oral toxicity, (v) P-glycoprotein transport interactions, (vi) potential mutagenicity (i.e., in silico AMES test), and (vii) potential cardiac toxicity (i.e. hERG/K+ channel interaction), COTI's technology provides a detailed in silico profile of potential drug candidates at the earliest stage of development.

To ensure that CHEMSAS continues to be a cutting edge technology new and/or updated prediction models are constantly updated and refined. New molecules are continuously added to the database and new in silico versions of tests and assays are also developed in order to

  • (1) make CHEMSAS' predictive capability as comprehensive as possible
  • (2) allow COTI to find molecules for new and important therapeutic targets
  • (3) find new molecule libraries that can be developed and sold.