The marriage of data, new algorithms, and biology is leading to innovative engineering of biological processes and the development of new healthcare treatments and diagnostic products and services. At Nvidia’s GTC conference last month, Jensen HuangLeading the company at the center of the new AI infrastructure, Huang is intimately familiar with the burgeoning entrepreneurial and investment activity in the emerging field of digital biology and its implications for healthcare.
While Somite.ai is aiming to bring, within the next two years, its first therapeutic asset to phase-1 clinical trials, other startups are already demonstrating proven solutions, primarily with AI-driven diagnostic devices. For example, the FDA just granted the first ever clearance for a fully autonomous AI for portable diabetic retinopathy screening, developed by AEYE Health.
AEYE Health’s solution is one of 171 artificial intelligence and machine learning-enabled medical devices approved so far by the FDA. “Digital health technologies are playing an increasingly significant role in many facets of our health and daily lives, and AI/ML is powering important advancements in this field,”. In 2022, the FDA approved 139 AI-related medical devices, a 12.
AI is a great tool, said Regev, for search and discovery in “universes that appear extremely big… but in fact have a lot of structure and constraint in them.” When you apply AI to biology, “you can actually go after these problems that appear too big that are so important to understanding the causes of disease or devising the next drug.