Former Director, Lead Discovery and Profiling, Center for the Development of Therapeutics, The Broad Institute of MIT and Harvard
Dr. Holly Soutter is a visionary leader and driving force in the convergence of biotech, pharma, and artificial intelligence, leveraging over two decades of drug discovery expertise. Holly's innovation lies in her ability to strategically unify structural biology, biochemistry, and biophysics with cutting-edge high-throughput screening to generate the high-quality data essential for fueling next-generation machine learning models.
She possesses a clear-eyed vision: that the future of drug discovery is AI-powered, but that success hinges on a "biology-first," hypothesis-driven approach to ML integration. This deep commitment ensures that the technology serves the science, accelerating the path to novel therapies.
While at the Broad Institute, Holly built a legacy of collaboration, working directly with machine learning experts to seamlessly integrate AI tools into hit finding workflows. These pioneering, integrated systems have democratized small molecule discovery, making it accessible to academic researchers worldwide. As the founding co-chair of the Machine Learning in Drug Discovery Symposium, she acts as a crucial nexus, fostering vital connections between experimentalists and ML scientists and attracting luminaries who are defining the next era of medicine.
At AIDDD 25, Dirk Van Hyfte and Holly Soutter will share insights on reprogramming the entire drug discovery process, presenting the HYFT® breakthrough that enables biology to "compute itself"—making complex biological connections explainable, accessible, and actionable for the first time. This session will explore:
- Reprogramming Discovery: How AI-native platforms are reshaping how scientists interact with biological data and design new therapies.
- The HYFT® Breakthrough: Unveiling a novel computational approach that decodes universal biosphere patterns, unlocking unprecedented discovery potential.
- The Frontier of Explainable AI in Biology: Transcending black-box models to deliver clarity, transparency, and trust in AI-powered biological research.