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§ Private Profile · San Mateo, CA, USA
Biotechnology company developing AI/ML platforms to design therapeutic antibodies and proteins for pharmaceutical partners.
Based in San Mateo, California, BigHat Biosciences operates an artificial intelligence and machine learning platform integrated with an automated wet lab to rapidly design and develop next-generation therapeutic antibodies. The biotechnology company currently employs approximately 80 people and manages an active internal pipeline of 10 therapeutic candidates targeting various complex human diseases. To support its clinical advancement, the enterprise has secured over $100 million in total venture funding, which includes a $75 million Series B financing round led by Section 32 alongside Andreessen Horowitz. Its primary business model relies on strategic drug discovery collaborations, generating revenue through upfront payments, royalty structures, and milestone agreements with major global pharmaceutical corporations such as Merck, Amgen, and AbbVie. The corporation known as BigHat Biosciences was officially established in 2019 by co-founders Mark DePristo and Peyton Greenside.
BigHat Biosciences has raised $94.0M across 2 funding rounds.
BigHat Biosciences has raised $94.0M in total across 2 funding rounds.
BigHat Biosciences has raised $94.0M across 2 funding rounds. Most recently, it raised $75.0M Series B in July 2022.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jul 1, 2022 | $75M Series B | Section 32 | 7wire Ventures, AlleyCorp, Amoon Fund, Andreessen Horowitz, B Capital Group, Curie.bio, Define Ventures, General Catalyst, Highbury Group, Kleiner Perkins, Operator Partners, Polaris Partners, Thirty Five Ventures, Transformation Capital, UP.Partners, 8VC, AME Cloud Ventures, Philip Tagari, A16z Scout Fund, Bristol Myers Squibb, Gaingels, GRIDS Capital, Quadrille Capital | Announced |
| Feb 1, 2021 | $19M Series A | Vineeta Agarwala | AlleyCorp, Andreessen Horowitz, B Capital Group, Curie.bio, General Catalyst, Operator Partners, Thirty Five Ventures, Transformation Capital, UP.Partners, Francisco Gimenez, AME Cloud Ventures, Innovation Endeavors | Announced |
BigHat Biosciences has raised $94.0M in total across 2 funding rounds.
BigHat Biosciences's investors include Section 32, 7wire Ventures, AlleyCorp, aMoon Fund, Andreessen Horowitz, B Capital Group, Curie.Bio, Define Ventures, General Catalyst, Highbury Group, Kleiner Perkins, Operator Partners.
BigHat Biosciences is a Series B biotechnology company headquartered in San Mateo, California, that develops safer, more effective antibody therapies using an integrated platform combining machine learning (ML), synthetic biology, and high-throughput wet-lab automation.[2][3][4] The company builds the Milliner™ platform, a full-stack antibody discovery and engineering system that designs, synthesizes, tests, and optimizes hundreds of antibody variants weekly through iterative design-build-test cycles, targeting challenging diseases in oncology, inflammation, and immunology.[1][2][5] It serves biopharma partners and maintains an internal pipeline of wholly-owned programs, solving the problem of slow, inefficient traditional antibody discovery by enabling rapid multi-parameter optimization for next-generation formats like multispecifics, VHH nanobodies, scFvs, and antibody-drug conjugates (ADCs).[1][5][8] With over $100M raised from top investors and scaling from 32 to 800 molecules tested per week, BigHat demonstrates strong growth momentum toward clinical candidates.[2][5]
BigHat Biosciences was founded in September 2019 by Mark DePristo (CEO & Co-Founder) and Peyton Greenside, who identified antibody discovery as a key biomedicine challenge ripe for AI/ML integration with fast, small-scale wet-lab experiments using advances in DNA writing and cell-free protein expression.[4][5] DePristo, with prior experience in protein modeling and deep learning, and Greenside converged on this after ideation on commercially vital problems, closing their first funding round just eight weeks later.[4] Early traction came from building the Milliner platform from scratch, starting with 32 antibody variants tested weekly in 2020 and rapidly scaling via automated labs and ML models, supported by investors like Andreessen Horowitz who backed the shift from screening to iterative engineering.[5][6] Pivotal moments include developing Reccy, their custom LIMS operating system, and focusing on partnerships for high-value programs.[1][7]
BigHat stands out through its end-to-end, AI-driven platform that outperforms traditional methods in speed, precision, and versatility:
BigHat rides the AI-biotech convergence trend, applying deep learning to the vast protein sequence space of biologics—one of the fastest-growing therapeutic categories including monoclonal antibodies and ADCs—shifting from blind screening to predictive engineering.[2][6] Timing is ideal amid advances in protein structure prediction (e.g., AlphaFold-era tools) and synthetic biology, enabling exploration of "green field" molecular spaces inaccessible traditionally, especially for hard targets in oncology and immunology.[4][5][6] Market forces like rising demand for next-gen antibodies (amid patent cliffs on blockbusters) and biopharma's need for speed favor BigHat, as its platform accelerates from design to candidates while reducing costs.[1][2] It influences the ecosystem by partnering with domain experts, augmenting pipelines, and demonstrating scalable ML-wet lab fusion, potentially expanding to novel assays and therapeutic areas.[5][8]
BigHat is poised to double wet-lab capacity multiple times, advancing its internal pipeline toward clinical milestones in oncology and inflammation while deepening strategic biopharma partnerships.[2][5] Trends like AI-accelerated drug discovery, multimodal biologics, and automated labs will propel it, enabling novel targets and formats amid a biologics market projected for sustained growth.[1][6] Its influence may evolve from platform innovator to full therapeutic developer, unlocking unprecedented efficiency in protein therapeutics and redefining antibody design standards—echoing its founding vision of making advanced therapies far easier to create.[3][4]