Biostate AI, a deeptech startup working at the intersection of artificial intelligence and RNA sequencing, has raised $12 million in a Series A funding round led by venture capital firm Accel, with participation from Gaingels, Mana Ventures, InfoEdge Ventures, and existing backers Matter Venture Partners, Vision Plus Capital, and Catapult Ventures.
Founded by former professors and serial entrepreneurs David Zhang (ex-Rice University) and Ashwin Gopinath (ex-MIT), Biostate AI is aiming to build what it calls the “foundation model for molecular medicine.”
The company’s goal is to dramatically expand access to RNA sequencing (RNAseq)—a cornerstone of precision medicine—by cutting costs, improving data quality, and applying generative AI to glean actionable insights from the human transcriptome.
The startup’s platform is already being used in over 150 pilot projects, including collaborations with Cornell University (for leukemia) and the Accelerated Cure Project (for multiple sclerosis), and has processed over 10,000 RNA samples since going commercial just two quarters ago.
Precision medicine at scale
RNAseq has long been a powerful but costly and technically fragmented method to track real-time gene expression and health markers. Biostate AI claims it is eliminating these bottlenecks using a combination of proprietary wet-lab techniques and AI-based analysis that can scale like a modern software product.
Its proprietary technologies include:
1. BIRT (Biostate’s Integrated RNA Technology), which uses an innovative multiplexing process to process multiple tissue samples simultaneously, cutting sequencing costs significantly.
2. PERD, a signal-filtering method that removes analytical “noise” in RNA datasets caused by variability between labs and equipment.
These innovations, the company claims, allow customers to run 2-3x more samples within the same budget. With this data advantage, Biostate is building LLM-style generative models trained on RNA sequences to predict disease evolution, recurrence, and treatment responses.
“Just as ChatGPT learned from the internet’s text, we’re training our models on the grammar of biology from billions of RNA expressions,” said Ashwin Gopinath, co-founder and CTO.
The bigger play: From diagnostics to therapies
While Biostate’s initial focus is on RNAseq services for research labs and biotech companies in the U.S., its long-term ambition is to become an end-to-end platform for precision diagnostics and therapeutics. Its stack includes Quantaquill, a generative AI tool that drafts publication-ready manuscripts from clinical datasets—streamlining scientific writing alongside biological discovery.
The startup is also building a large, consented, de-identified dataset of RNA profiles, enabling the development of disease-specific predictive models. “We’re moving the entire diagnostics workflow closer to the patient,” said David Zhang, co-founder and CEO.
Zhang, who previously invented several DNA diagnostic tools at Rice, described Biostate as a natural progression: “Every diagnostic I’ve built was about bringing answers faster. Biostate takes the biggest leap yet—by making full-transcriptome sequencing affordable.”
Gopinath, whose work is personally motivated by his wife’s leukemia diagnosis, added: “We’re not just trying to predict disease. Eventually, we want to eliminate it.”
Accel backs Biostate’s AI-first thesis for medicine
“Biostate is doing for medicine what OpenAI did for text: scaling data collection so that AI can finally work,” said Shekhar Kirani, Partner at Accel. “By combining generative AI with next-gen wetlab innovation, they’re laying the foundation for truly personalised, scalable healthcare.”
So far, Biostate has raised $20 million+ in total, including a prior seed round backed by deep-tech angels like Dario Amodei (Anthropic), Emily Leproust (Twist Bioscience), and Mike Schnall-Levin (10X Genomics).
With offices in Houston, Palo Alto, Bengaluru, and Shanghai, Biostate is now positioning itself as a global player in molecular AI, with plans to expand collaborations in oncology, cardiovascular disease, and autoimmune disorders in FY26.
