SAN MATEO, Calif.– BigHat Biosciences, a biotechnology company developing safer, more effective antibody therapies for patients using machine learning and synthetic biology, today announced it has raised a $75 million Series B funding round, led by Section 32, with participation from new investors Amgen Ventures, Bristol Myers Squibb, Quadrille Capital, Gaingels, GRIDS Capital, among others. The investment brings BigHat’s total funding to date to $100 million. Prior investors Andreessen Horowitz, 8VC, and AME Cloud Ventures also contributed to this round, which will be used to scale the capacity of MillinerTM, an integrated AI/ML- wet lab platform, advance therapeutic programs toward human clinical trials, aggressively hire drug discovery and development talent and to accelerate strategic collaborations with flagship partners.
More than 200 antibodies and other biotherapeutics are approved today as part of a global biologics market expected to grow to $421 billion by 2025. Next-generation antibody therapies promise improved safety and efficacy for patients. Developing these advanced molecules can be difficult, costly, and slow with conventional techniques. BigHat’s AI-enabled antibody design platform, Milliner, offers the essential technologies to quickly and reliably create these breakthrough therapies.
BigHat is using MillinerTM to design safer, more effective antibody therapies to treat some of the world’s most intractable conditions, from chronic illnesses to life-threatening diseases. At BigHat, every therapeutic program starts with a design blueprint and antibodies generated in our discovery engine or supplied by a partner. These initial molecules are then iteratively transformed into best-in-class next-generation therapies on the Milliner platform through sequential design-build-test cycles. BigHat’s machine learning models design hundreds of variants that are built and tested in our lab using the latest synthetic biology technologies in each cycle. These measurements include biophysical properties and impact on disease activity for every variant using cell-based or other functional assays that replicate in vivo disease processes. This new data is used to update the AI/ML models so that over multiple cycles, these models learn to create antibodies that match our design blueprint.
“BigHat is ushering the next wave of personalized medicines with a sophisticated AI platform integrated with a next-generation lab that addresses the complexities and inefficiencies associated with biologics discovery,” said Steve Kafka, PhD, Managing Partner of Section 32 and newly-appointed BigHat Board Member. “Section 32 is delighted to support BigHat’s mission and their quest to rapidly deliver safer and more effective antibody therapies for people suffering from today’s most challenging diseases.” Longtime Alphabet executive and Section 32 Managing Partner, Andy Harrison, co-led this Series B financing and will join as a Board Observer.
”Completion of the first stage of Amgen’s research collaboration with BigHat demonstrated the ability of their platform to quickly and significantly optimize next-generation single-domain antibodies, validating the platform as a path to generating target binders with improved properties compared with the original repertoire identified by traditional technologies,” said Philip Tagari, VP of Research at Amgen. “We’re excited to participate in the funding round to assist in the continued development and deployment of BigHat’s approach.”
