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 Huang put it this way: “For the very first time in human history, biology has the opportunity to be engineering, not science.”
Leading 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. “The future of medicine lies at the intersection of AI and biology,” Micha Breakstone, co-founder and CEO of Somite.ai told me recently. Allon Klein, another Somite.ai co-founder, called the process of turning a cell into a specific treatment for a specific ailment, “the most sophisticated therapy that has ever been invented,” highlighting the complex engineering challenge of taking a cell, step-by-step, through the process of development.
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. 85% of patients with diabetes over the age of 40 could develop diabetic retinopathy, the leading cause of blindness in the working age population. Now they can benefit from an affordable early diagnostic screening solution, applied without dilation at a clinic, the pharmacy or even at home. There are approximately 40 million people with diabetes in the U.S. and over 500 million worldwide, all of whom are at risk of diabetic retinopathy, and early diagnosis and intervention are key for sight-loss prevention.
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,” says the FDA.
Since 2012, the number of FDA-approved AI-related medical devices has increased by more than 45-fold, according to the 2024 AI Index. In 2022, the FDA approved 139 AI-related medical devices, a 12.1% increase from 2021, and the FDA expected that the number of approved AI/ML-enabled devices will grow 30+% year-over-year in 2023. A significant majority of approved devices were related to radiology.
These AI/ML-enabled medical devices, focused on narrow healthcare challenges, herald a new era of digital biology, where the very complex processes of life with its myriad elements can be engineered to yield robust and repeatable healthcare treatments and interventions. Aviv Regev, the co-recipient with Allon Klein of the 2021 James Prize in Science and Technology Integration, for “forging new ways to unite the disciplines of biology, computational science, and engineering,” explained in a recent interview why AI is so important to advancing biomedicine: “Many of the problems that we try to solve in biomedicine, [are] bigger than we would ever be able to perform experiments or collect data.”
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.”
Joshua March and Kasia Gora, co-founders of SCiFi Foods, concur: “We are now at a critical inflection point in our ability to predict and engineer complex biological systems—transforming biology from a wet and messy science into an engineering discipline… it is clear that the combination of AI technology and advancements in automation with easy genetic editing means that we are already at the point where we can engineer biology to an extent never before possible.”
Investors also agree. The first quarter of 2024, says CB Insights, “was a brighter spot for the digital health market, which has struggled amid the broader venture slowdown. Digital health funding grew 48% quarter-over-quarter in Q1’24. This growth was supported by an increase in $100M+ mega-rounds, which were largely directed at biotech startups and other players leveraging AI.”
