Biostate AI closes $12m to bring ‘Netflix model’ to molecular diagnostics

AI and RNA sequencing company Biostate AI has announced the successful completion of a $12M Series A funding round, led by Accel.

The funds will support the company’s mission to unlock affordable and integrated precision medicine, starting with RNA sequencing (RNAseq) services for US-based molecular research.

The company’s immediate focus is revolutionising RNAseq accessibility and developing clinically relevant predictive models.

These technologies—and the requisite advances in data quality, integration of molecular data types, and rigorous clinical validation—serve as the foundations for Biostate’s long-term vision: truly personalised therapeutics.

Ashwin Gopinath is co-founder and CTO of Biostate AI and a former MIT assistant professor.

Gopinath said: “Just as ChatGPT transformed language understanding by learning from trillions of words, we’re learning the molecular language of human disease from billions of RNA expressions from millions of samples.

“We’re doing for molecular medicine what large language models did for text—scaling the raw data so the algorithms can finally shine.”

Biostate was founded on the principle that the entire RNA transcriptome (rather than just small groups of RNA transcripts) is an underutilised real-time biomarker for human health.

Until now, the comprehensive, simultaneous analysis of all RNA transcripts has been limited by cost and analytical barriers.

By eliminating such industry bottlenecks, the Biostate co-founders realised they could snowball a cheaper and more effective RNAseq operation into a one-stop shop for precision medicine.

Gopinath’s work is deeply influenced by his wife’s battle with leukemia.

His background in engineering led him to dig into how such devastating diseases can be predicted.

Paired with co-founder David Zhang’s background in DNA research, the two discovered that RNA was an untapped middle ground of human health insights.

Plus, they planned to build something that would last, hence the Netflix-inspired self-sustaining business model fueled by the company’s focus on home-grown AI.

While LLMs like ChatGPT learn patterns from text, Biostate’s AI models identify expression signatures across thousands of genes, which all correlate with specific disease states and treatment responses.

This enables its models to detect subtle molecular changes that precede clinical symptoms by weeks, months, or even years, enabling earlier intervention.

The firm has raised over $20 million to date and is growing its paying institutional customer base through a network of 100+ pilot projects across diverse disease indications, including leukemia (Cornell) and multiple sclerosis (Accelerated Cure Project).

As a result, since commercializing its offering just two quarters ago, Biostate has run RNAseq on over 10,000 samples from over 150 collaborators and customers from leading institutions.

The startup has also secured agreements to process several hundred thousand unlabeled samples annually, rapidly accelerating its dataset growth and powering AI development.