BigHat Biosciences Raises $75 Million in Series B Funding to Design Safer, More Effective Antibodies

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Capital will advance BigHat’s internal pipeline of therapeutics to patients, expand platform capacity 10-fold, and accelerate strategic partnerships

SAN MATEO, CA, July 20, 2022 — 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.”

The company was founded in 2019 by CEO Mark DePristo, a University of Cambridge biochemistry Ph.D., former Head of Genomics for Google.AI, and Co-director of Medical Genetics at Broad Institute, with CSO Peyton Greenside, a Stanford biomedical informatics Ph.D. and 2018 Schmidt Science Fellow.  Since that time, BigHat has reached significant business and scientific milestones, including:

“The scale and flexibility of the BigHat platform allows us to partner with companies anywhere along the therapeutic discovery continuum as well as pursue internal therapeutics programs to address major unmet needs across a variety of diseases,” said BigHat co-founder and CEO Mark DePristo. “Combining internal programs and partnerships enables us to bring as many assets to market as quickly as possible. All while capturing a wealth of data to continuously improve our AI/ML models and wet lab techniques, making future campaigns faster and better. The BigHat team is excited and ready to put this Series B funding to excellent use.”