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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AI and GenAI Applications to Help Optimize Purification and Yield of Antibodies From Plasma
October 31st 2024Deriving antibodies from plasma products involves several steps, typically starting from the collection of plasma and ending with the purification of the desired antibodies. These are: plasma collection; plasma pooling; fractionation; antibody purification; concentration and formulation; quality control; and packaging and storage. This process results in a purified antibody product that can be used for therapeutic purposes, diagnostic tests, or research. Each step is critical to ensure the safety, efficacy, and quality of the final product. Applications of AI/GenAI in many of these steps can significantly help in the optimization of purification and yield of the desired antibodies. Some specific use-cases are: selecting and optimizing plasma units for optimized plasma pooling; GenAI solution for enterprise search on internal knowledge portal; analysing and optimizing production batch profitability, inventory, yields; monitoring production batch key performance indicators for outlier identification; monitoring production equipment to predict maintenance events; and reducing quality control laboratory testing turnaround time.
