Drug discovery is an immensely challenging problem. There are currently more than 9,000 untreated diseases with over 300 million people suffering from rare diseases for which we are unlikely to develop treatments any time soon. The drug discovery process still costs an average of $2.6 billion per drug. Even then, 30 to 50% of top selling drugs don't work for the patients in which they are prescribed for. We build technology in the service of science, specifically using AI to tackle this huge unmet need and to transform the traditional drug discovery process. In this talk Mark will discuss how integration of data is the foundation of which everything else is based, and describe our approach to using AI and human expertise to deliver validated unprecedented targets, and to enhance chemical drug design and precision medicine.
Mark is the SVP Informatics and Data 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.