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raised $19 million in an oversubscribed Series A funding round to integrate a wet lab with machine-learning technologies to guide the search for better antibodies, and as a result, better drug treatments, particularly in areas where no other treatments are available.

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led the round with participation from prior investors , 1 and . BigHat raised a total of $24.3 million in funding since it was founded in 2019. That includes a round in 2019, also led by 8VC, according to 附近上门 data.

Biologics is growing rapidly, BigHat co-founder and CEO , Ph.D., told 附近上门 News. Many of the medications on the market right now are considered biologics. They are typically made of tiny components like cells, tissues, sugars, proteins or DNA and can originate from living sources such as animals, plants and bacteria.

The is expected to be valued at $456 billion by 2027. As of 2019, seven of the top 10 drugs are biologics. More than 200 biotherapeutics are used today, generating more than $100 billion in annual revenue for drug companies developing treatments, for example in oncology to auto-immunity to infectious disease, DePristo said.

The San Carlos, California-based protein therapeutics company is developing an antibody design platform, guided by artificial intelligence, aimed at speeding up the design and discovery of potential antibodies to days rather than weeks or months, as well as enabling simultaneous measurement of many molecules at the same time, said , Ph.D., co-founder and chief scientific officer at BigHat.

鈥淭he result is that the platform can unlock antibody designs currently not possible,鈥� Greenside said. 鈥淭here is only so much time, but if you can drive it down to days, you can pursue difficult engineering platforms at the same time.鈥�

One of the company鈥檚 successful use cases so far is engineering a potent neutralizing SARS-CoV-2 bispecific antibody in the lab, she said.

BigHat intends to put the new capital to work by expanding its scientific and technical teams, including hiring antibody and protein engineers, AI/ML engineers and computational biologists, DePristo said. In addition, the company will continue developing its platform and internal therapeutic programs toward human clinical trials.

鈥淲e want to attract world-class talent that will help grow the company significantly to service the opportunity in front of us,鈥� he said. 鈥淭here are so many interesting applications and real opportunities for therapeutics, and we want to run all of them to the ground over the next two to three years 鈥� we don鈥檛 want to have to choose.鈥�

As part of the investment, Andreessen Horowitz General Partner M.D., Ph.D., joins BigHat鈥檚 board of directors.

Agarwala has known DePristo and his work on bioinformatics software for over a decade, and was one of the first founders she reached out to when joining Andreessen Horowitz. When learning about BigHat, she felt the vision for a machine learning-enabled biologics discovery platform was aligned with her team鈥檚 investing theses.

In an environment where most antibody companies experimentally screen a large number of protein sequences to nominate lead candidates, it typically represents only a tiny fraction of all possible sequences, Agarwala said via email. BigHat is taking an alternative approach.

鈥淏igHat鈥檚 platform brings together advanced computational models and a large, ever-growing experimental dataset that is generated within the company; in so doing, they can create tight learning loops which enable them to efficiently traverse the multi-parameter space of protein optimization,鈥� she said. 鈥淭his shift from screening to engineering will enable us to access therapeutically powerful, yet manufacturable, sequences that may not even exist in nature. We believe this could unlock a whole new wave of productivity in biologics drug development.鈥�

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