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3rd Global Pharma R&D Informatics and AI Congress w/ Mark Davies

Meet Mark Davies, VP Biomedical informatics at BenevolentAI, who will be speaking about how AI enables an enhanced data-driven approach to drug discovery and development.

Despite the huge growth of knowledge and information the process of biomedical discovery has not changed for 50 years. In the modern world, it is impossible for humans alone to process all the complex information potentially available to them for the advancement of scientific research. For example, a new scientific paper is published every 30 seconds, consequently only a small fraction of globally generated scientific information can form ‘useable’ knowledge. This talk will present on how AI can offer a solution to this problem and how machine learning technologies are changing how new medicines are discovered and developed. The talk will also focus on how AI, as an augmentation tool to human intelligence, is essential in providing experienced scientists with the analytical tools they need to design better compounds faster


Mark’s biography

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Mark is the VP Biomedical Informatics at BenevolentAI. He has a background in molecular genetics, bioinformatics (BSc University of Sussex) and computer science (MSc Birkbeck College) and has over 15 years of experience working on biomedical data representation, data analysis and application development. In 2001, he joined the London based biotechnology company Inpharmatica, where he was initially working on mining the output of the Human Genome Projects and eventually moved on to building Chemogenomics systems used by pharmaceutical companies, such as Bayer. Mark moved to the European Bioinformatics Institute (EMBL-EBI) as one of the founding members and technical lead for the ChEMBL resource - the largest open-source SAR database. Mark was also responsible for the successful transition of the SureChEMBL chemical patent system from Digital Science to the EMBL-EBI. Throughout his career Mark has published on how the use of biomedical data and technologies can improve the drug discovery process and enjoys identifying new opportunities this research space.

 

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