Agilent Thought Leader Award to Support Web-Based Tools for Cancer and Drug-Safety Research
Emmanuel Barillot, Director of Bioinformatics and Systems IT at the Institut Curie (Paris, France), has received an Agilent Thought Leader Award. Agilent will contribute financial support, products, and expertise to the work by Barillot to develop a database of cellular signalling pathways and a visualization tool to help the pharmaceutical industry develop more effective cancer treatments. The web-based tool will enable the identification of off-pathway effects of new drugs.
Emmanuel Barillot, Director of Bioinformatics and Systems IT at the Institut Curie (Paris, France), has received an Agilent Thought Leader Award. Agilent will contribute financial support, products, and expertise to the work by Barillot to develop a database of cellular signalling pathways and a visualization tool to help the pharmaceutical industry develop more effective cancer treatments. The web-based tool will enable the identification of off-pathway effects of new drugs.
Tony Owen, Agilent’s Senior Director of life science marketing and market development, said: “Pharmaceutical companies can spend many years and billions of dollars only to find that a once-promising preclinical therapeutic compound is actually harmful to patients in clinical tests.” He added: “It is incumbent upon drug developers to find ways to assess drug toxicity much earlier in the process to reduce R&D time, minimize costs, and maximize patient benefits.”
Barillot said: “The Agilent Thought Leader Award will accelerate the further development of the Curie Atlas of Cancer Signalling Networks, a comprehensive and freely available cancer pathway database, and NaviCell network visualization tool.” He added: “These tools will enable earlier identification and visualization of toxic interactions between signalling pathways during the discovery and development of therapeutics for the treatment of cancer, thus enabling better informed drug-candidate selection and prioritization. They will also be useful for interpreting high-throughput biological data, like next-generation sequencing profiles of tumours or other samples.”
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