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BigHat Biosciences, a protein therapeutics startup and developer of an AI-guided antibody design platform, today announced it has closed a $19 million series A round led by Andreessen Horowitz. A spokesperson told VentureBeat the funding will be used to invest in R&D as BigHat further refines its antibody engineering processes.

The use of biologics —  medications made of components like sugars, proteins, DNA, whole cells, and tissues — is on the rise in drug development. Two years ago, seven of the top 10 drugs were biologics. Today, more than 200 biotherapeutics are in use. They are estimated to generate over $100 billion in annual revenue for drug companies, but they’re difficult to design, particularly those that leverage antibodies. While existing technologies can screen for antibody molecules, traditional lab workflows can take weeks to produce an antibody variant and characterize its behavior.

BigHat, which was founded in 2019 by Mark DePristo and Peyton Greenside, with advisor Theresa Tribble, aims to combine a high-speed antibody characterization lab with AI to engineer disease-fighting molecules. DePristo was formerly the head of genomics for Google AI and codirector of medical genetics at the Broad Institute of MIT and Harvard. Greenside, also a computational biologist at the Broad Institute, earned her Ph.D. in biomedical informatics from Stanford.

BigHat claims its wet lab can go from designs to hundreds of “expressed, purified, and characterized” antibodies in days, as opposed to weeks. That’s in part thanks to AI and machine learning technologies that guide the process and improve with each development cycle on the platform. The technologies also learn how mutations affect an antibody’s expression yield, affinity, stability, solubility, downstream function, and other molecular properties, charting a course to rare molecules that might otherwise remain undiscovered.

The BigHat platform can be used to build proteins like monoclonal antibodies, short chains of amino acids called peptides, and more. These proteins can bind to multiple targets on hostile cells and offer better tissue penetration, as well as providing access to sites other antibodies can’t reach and improving safety while lowering production costs. For example, CAR-T therapies use bioengineered antibodies and receptors to stimulate or suppress the immune system and help the body fight cancer.

BigHat claims its wet lab was actively producing and characterizing 100 antibodies per week as early as summer 2020. At the onset of the COVID-19 pandemic, BigHat began a SARS-CoV-2 retargeting program that ultimately led to a viral neutralizing molecule in the lab. More recently, BigHat was awarded Amgen’s Golden Ticket to MBC BioLabs, which entitles the company to lab bench space and access to Amgen’s scientific and business leaders. BigHat was also awarded a Small Business Innovation Research grant from the U.S. National Institute of Standards and Technology (NIST).

According to Greenside, BigHat is collaborating with unnamed strategic partners to leverage its platform and codevelop antibodies and other biotherapeutics. Over the next three years, BigHat plans to triple its headcount for clinical trials in therapeutic programs.

“There are very few biologic applications in which you can pose a hypothesis and have real, lab-produced answers in days. Our wet lab can synthesize and characterize hundreds of antibodies every few days. Coupled with active learning techniques, BigHat molecular engineering platform can optimize antibodies for affinity, stability, solubility, and even performance in a functional assay,” Greenside said. “We’ve just started to explore the potential for novel antibody and protein therapeutics enabled by BigHat’s approach to antibody discovery.”

8VC, AME Cloud Ventures, and Innovation Endeavors also participated in San Carlos, California-based BigHat’s latest round. The startup has raised around $25 million in venture capital.

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