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Compugen Presents Prediction Based Discovery Strategy At “Targets And Strategies For Drug Discovery” Conference

Speaking today at the Targets and Strategies in Drug Discovery Summit in Las Vegas, Dr. Gady Cojocaru, Head of Target Discovery at Compugen Ltd. ( NASDAQ: CGEN), presented Compugen’s prediction based discovery strategy by focusing on two of the methodologies being utilized by the Company for the identification of novel targets for monoclonal antibody (mAb) cancer therapy. Also included in the presentation was the disclosure of CGEN-15022 and CGEN-15092, two of the B7/CD28-like proteins discovered by the Company that have shown potential in initial validation studies for this therapeutic use.

Dr. Cojocaru stated, “As with all of our discovery methodologies, or platforms, the two methodologies being presented today rely on our underlying and continuously growing predictive discovery infrastructure. The first discovery platform was created for the prediction of novel cancer targets, including drug resistant and advanced stage cancer. This methodology relies in large part on query algorithms focused on the integrated statistical analysis of both expression and clinical data within the infrastructure and has resulted to date in multiple discoveries, such as the previously disclosed CGEN-928 with potential use for late stage, aggressive and drug resistant multiple myeloma and Rituximab resistant non-Hodgkin’s lymphoma.”

Dr. Cojocaru continued, “The second platform was developed to predict targets specifically for the use of monoclonal antibodies in cancer immunotherapy, and is based on a more general Compugen platform for identifying novel members of protein families of high industry interest. Since most traditional approaches for identifying novel members of known protein families are largely based on sequence homology or function, the set of query algorithms for this platform was designed to first discover other types of characteristics shared between known members of the family of interest. Based on this, we select proteins from our discovery infrastructure that share these characteristics and therefore could potentially be unknown family members.”

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