Our method of discovering novel product candidates involves first selecting – either on our own or with a partner company - an unmet therapeutic or diagnostic need where we believe our predictive capabilities would be relevant, or could be modified to be relevant. After selection of the unmet need we wish to address, we then focus all of our discovery platforms, algorithms and other computational biology capabilities to predict in silico (i.e. in computers) sequences for a typically large number of possible product candidates.Next we utilize proprietary algorithms and tools and other methodologies to select from this large number of possibilities, those novel molecules that we believe have the highest probability of being successful for such specified need. Selected molecules are then synthesized and undergo in vitro and/or in vivo validation testing.

Currently included in our computational biology capabilities are more than ten discovery platforms that have been created and validated, largely during the past several years, and continue to be enhanced with new scientific knowledge and findings from each discovery run.Each of these platforms incorporates the predictive modeling of various biological phenomena, with each such platform designed to identify novel biologic molecules of a specific type or for a specific purpose. Our therapeutic discovery platforms include identification of novel Protein Family Members, discovery of targets for mAb therapy, Protein-Protein Interaction Blockers (PPI Blockers), GPCR Peptide Ligand,Disease-Associated Conformation (DAC) Blockers, peptides for Intracellular Drug Delivery (IDD), viral peptides, Splice Variant Based Therapeutic Proteins, and more.

Over 70 publications in peer-reviewed journals have been published about our discovery capabilities and product candidates.