BigHat Biosciences Raises $19 Million in Series A Funding to Advance Antibody Design and Development for Safer, More Effective Treatments

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Andreessen Horowitz-led investment fuels hiring and R&D for AI-enabled experimental platform that speeds the antibody engineering process

SAN CARLOS, CA, February 10, 2021BigHat Biosciences, a novel protein therapeutics company and developer of an AI-guided antibody design platform, today announced it has raised $19 million in an oversubscribed Series A funding round, led by Andreessen Horowitz, with participation from prior investors 8VC, AME Cloud Ventures, and Innovation Endeavors. As part of the investment, Andreessen Horowitz General Partner, Vineeta Agarwala, MD, PhD joins BigHat’s Board of Directors.

Biologics represent a rapidly growing therapeutic category.  As of 2019, seven of the top ten drugs were biologics and there are currently more than 200 biotherapeutics in use, generating more than $100 billion in annual revenue for drug companies developing treatments for indications ranging from oncology to auto-immunity to infectious disease.  

“Our mission is to improve human health by making it far easier to create advanced, next-generation antibody and protein therapeutics.  BigHat is transforming antibody design from bulk screening to data-driven engineering to give precise control over the antibodies’ molecular properties.  Leveraging recent advances in synthetic biology and machine learning, our platform measures and optimizes antibodies for the biophysical and functional properties needed for cutting-edge therapeutic applications,” said BigHat Co-founder and CEO Mark DePristo, PhD.

BigHat integrates a wet lab for high-speed characterization with machine learning technologies to guide the search for better antibodies. This approach dramatically speeds up design and discovery data acquisition cycles to days rather than weeks or months. It also provides greater optionality, eliminating the need for premature candidate selection and enabling the simultaneous measurement of a vast array of key biophysical properties of many molecules.  

“There are very few biologic applications in which you can pose a hypothesis and have real, experimentally validated answers in days.  BigHat’s molecular engineering methods allow us to optimize antibodies for affinity, stability, solubility, and even performance in a functional assay,” added BigHat Co-founder and Chief Scientific Officer (CSO) Peyton Greenside, PhD. “We’ve just started to explore the potential for novel antibody and protein therapeutics enabled by BigHat’s approach to discovery.”

Supercharged Antibody Development

Existing technologies only solve a sliver of the full design problem and traditional lab workflows take weeks-to-months to produce a protein variant and characterize its behavior. BigHat’s experimental platform reduces the time to enter clinical development by accelerating candidate discovery and validation.

“The relevant search space for protein therapeutics is orders of magnitude larger than a purely experimental approach anchored in naturally-occurring sequences can efficiently traverse,” said Vineeta Agarwala, General Partner at Andreessen Horowitz.  “This is why we believe BigHat’s platform, which combines machine learning, synthetic biology, and high-throughput experimentation, holds tremendous promise.”

AI-Accelerated Momentum

Founded in late 2019, BigHat has experienced rapid growth during its proof-of-concept stage, reaching significant corporate and scientific milestones in its first 15 months.  BigHat’s wet lab is actively producing and characterizing antibodies at scale.  The cloud-based AI/ML platform improves designs each round by combining active learning with assay modeling of critical biophysical properties leading to the highest quality sequences.  At the onset of the COVID-19 pandemic, BigHat validated this platform by engineering a potent neutralizing SARS-CoV-2 bispecific antibody in the lab.  

Following this platform demonstration, in late 2020, BigHat was awarded Amgen’s Golden Ticket to MBC BioLabs, which entitles them to lab bench space as well as access to the life sciences incubator community and Amgen’s scientific and business leaders.  The company was also awarded a Small Business Innovation Research (SBIR) grant for improving protein production from the National Institute of Standards and Technology (NIST).  BigHat is collaborating with multiple strategic partners to leverage the platform to co-develop antibodies and other biotherapeutics.

The new capital will be used to expand the BigHat scientific and technical teams; the company is actively hiring exceptional antibody and protein engineers, AI/ML engineers, and computational biologists.  Additionally, the funding will support further platform development, scaling capacity and advancement of BigHat’s own internal therapeutic programs towards human clinical trials.

“BigHat is applying AI in a dramatically different way than most life sciences startups.  AI is by its nature iterative and so is drug development, but in a traditional lab you have long wait times between generations of data as discovery is done and redone.  In BigHat’s wet lab, the platform increases throughput, speeds the feedback loop and really eliminates some of the cost and time barriers standing in the way of optimizing protein therapeutics,” said Francisco Gimenez, Partner at 8VC.

Founding Team and Advisory Board

The company was founded by CEO Mark DePristo, PhD, University of Cambridge, and CSO Peyton Greenside, PhD, Stanford, along with founding advisor Theresa Tribble, a Harvard University MBA and former Chief Business Officer (CBO) for Everlywell. Liz Schwarzbach, PhD, University of Pennsylvania, recently joined as CBO.  

BigHat has assembled a world-class group of technical and business advisors.  Scientific and business leaders advising the company span chemistry luminaries (Brian Kobilka, Nobel Laureate), AI and deep learning experts (Jake Gardner and Andrew Gordon Wilson), life sciences entrepreneurs (Stan Lapidus) and biologics drug discovery leaders (Greg Landes), among others.