Progress, Potential, and Possibilities Podcast / Show Andrea De Souza - Eli Lilly - Leveraging Big Data & Artificial Intelligence For Unmet Medical Needs
Andrea De Souza, is Associate Vice President, Research Data Sciences and Engineering, at Eli Lilly & Company (https://www.lilly.com/) where over the past three years her work has focused around empowering the Lilly Research Laboratories (LRL) organization with greater computational, analytics-intense experimentation to raise the innovation of their scientists. A former neuroscience researcher, Andrea’s portfolio career has included leadership assignments at the intersection of science, technology and business development. She has built and led informatics and scientific teams across the entire pharmaceutical value chain. Most recently, Andrea focused on building the Pharma Artificial Intelligence market at NVIDIA. Through this experience she has traveled the world advising bio-pharmaceutical clients, academics, research institutes, and startups in the potential of machine learning and artificial intelligence across every discipline of the industry. Prior to her role at NVIDIA, Andrea held leadership positions at the Broad Institute of Harvard and MIT, Amgen, and Roche. In her current role as Associate Vice President at Lilly, Andrea leads four organizations: the High-Performance Computing Team, the Data Engineering team, the AI/ML team and the Translational Informatics team for LRL. Additionally, Andrea serves as a strategic advisor for the U.S. National Institutes of Health (NIH) for The Human BioMolecular Atlas Program (HubMap) Advisory Team. Andrea has a B.S. in Animal Physiology from UC Davis, a Master’s in Health Administration from University of San Francisco, and an MBA from MIT Sloan. Through her broad research efforts, Andrea has publications in journals as diverse as the Journal of Computer-Aided Molecular Design, Bio-organic & Medicinal Chemistry Letters, and Neuropharmacology. Her leadership has gained her international recognition as a leader in Big Data, Artificial Intelligence and Data Sciences.