TRANSLATIONAL MEDICINE POWERED BY COMPUTATIONAL DISCOVERY

Overview

Compugen discovers novel drug targets through a unique, predictive, computational process that combines human biology derived from genome analysis with disease information derived from analysis of vast amount of proprietary and publicly available data. This process, which is generally applicable to many fields of medical interest, usually results in multiple drug target candidates. Our comprehensive data analysis therefore enables us to often identify first-in-class drug target candidates, which are difficult to identify using traditional screening approaches.

Built on the understanding and mathematical modeling of biological phenomena, our discovery process is flexible enough to be applicable to a wide range of indications and diseases. Our computational tools were tested and optimized for over a decade and have been successfully applied to many biological phenomena, resulting in findings which were published in dozens of first-tier peer reviewed scientific journals. The applicability of the infrastructure was demonstrated internally in multiple therapeutic and diagnostic areas and, in contrast to traditional discovery methodologies, demonstrated significant advantages in terms of cost, time and most importantly, probability of successful validation.

Our in silico discovery process is followed by a therapeutically focused validation phase, in which the novel candidates undergo an extensive set of experiments to confirm the in silico prediction and provide additional detailed data as to their relevance and potential as drug targets for therapeutic development.

OUR PROCESS

Predictive Discovery

Our process for in silico discovery of novel drug targets
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Target Discovery

An overview of our process for the discovery of B7/CD28-like and other immunomodulators
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Target Validation

Therapeutically focused drug target validation pipeline
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PUBLICATIONS

Development and Functional Characterization of COM902, a Novel Therapeutic Antibody Targeting the Immune Checkpoint TIGIT

Sandeep Kumar, Radhika Desai, Hsin-Yuan Cheng, Kyle Hansen, Andy Drake, Patrick Wall, Kathryn Logronio, Gady Cojocaru, John Hunter, Mark White, Spencer Liang and Maya Kotturi
Nov 2017

Analysis of the TIGIT/PVRIG Axis in Human Cancers to Support Indication Selection and Biomarkers for COM701 and COM902

Sarah Whelan, Ling Leung, David Bernados, Sudipto Ganguly, Abha Soni, Janis Taube, John Hunter, Mark White, Drew Pardoll and Spencer Liang
Nov 2017

Computational Discovery and Experimental Validation of Cgen-15032 as a Novel Target for Cancer Immunotherapy

Ofer Levy, Sudipto Ganguly, Ilan Vaknin, Eran Ophir, Einav Safion, Inbal Barbiro, Yosef Diken, Liat Dassa, Tal Friedman, Zoya Alteber, Gady Cojocaro, Nir Rainy, Yair Benita, Benjamin Murter, Xiaoyu Pan, Debebe Theodros, Rupashree Sen, Ayelet Chajut, Vered Daniel Carmi, Zurit Levine, Yona Geffen, Drew Pardoll and Arthur Machlenkin
Sep 2017

Computational Discovery of Novel Immune Checkpoints

Amit Novik, Itamar Borukhov, Yair Benita, Gady Cojocaru, Assaf Wool, Yossef Kliger, Tomer Zekharya, Zurit Levine, Sergey Nemzer, Eran Ophir, Meir Azulay, Maya Kotturi, Sudipto Ganguly, Drew M Pardol, Ofer Levy, Amir Toporik
Jul 2017