Biostate AI: Making Biology Predictable with AI

Company & Team Introduction

Biostate AI, founded in late 2024, is dedicated to making biology and healthcare predictable by harnessing the power of AI. The company is tackling the challenges in genomic science by building what is rapidly becoming the world's largest RNA sequencing database. By dramatically reducing sequencing costs through their proprietary technologies, Biostate makes RNA sequencing and other omics accessible at an unprecedented scale. Their AI then extracts meaning from this massive influx of data, using foundation models trained on diverse RNA expression profiles. This approach captures the dynamic nature of biology in a way that traditional genomics cannot, enabling the design of new drug molecules and therapies.

Leadership Team

• David Zhang (Co-founder & CEO): David brings a visionary perspective to Biostate AI, driving the company's mission to transform drug development and patient care.

• Ashwin Gopinath (Co-founder & CTO): Ashwin is a biotech entrepreneur and AI innovator who leads the technology and development of Biostate's AI systems and proprietary sequencing technologies.

Product Overview

Biostate AI's core technology is a vertically integrated system that combines proprietary RNA sequencing with advanced AI models to make biology predictable. The company has developed innovative solutions to address the high cost and complexity of traditional gene expression data acquisition from RNA sequencing workflows.

Revolutionary RNA Sequencing Technology

Biostate AI's approach is built on two patent-pending technologies:

• BIRT (Barcode-Integrated Reverse Transcription): This technology integrates sample barcoding directly into the reverse transcription step of RNA sequencing. Using proprietary hairpin primers and random polyN priming, BIRT allows for the pooling of up to 16 samples immediately after reverse transcription. This multiplexing dramatically reduces costs, hands-on time, and reagent use for downstream library preparation. BIRT is also effective with challenging and degraded samples, such as those from formalin-fixed paraffin-embedded (FFPE) tissues, and avoids the 3'-end bias of traditional methods.

• PERD (Probes for Excess RNA Depletion): An enzyme-free method that removes ribosomal RNA (rRNA), which provides little useful information and can make up to 90% of cellular RNA. By using specially designed probes instead of expensive enzymes, PERD further reduces costs while maintaining high data quality.

Together, BIRT and PERD deliver significant advantages: up to a 16x increase in sample throughput and up to a 90% reduction in cost, while also enabling the measurement of long non-coding RNAs (lncRNAs) and accommodating low-yield, degraded samples.

AI Platform

Biostate AI's AI platform transforms the vast amount of data generated by their RNA sequencing technology into actionable insights. Unlike many precision medicine companies that focus on medical images or electronic health records, Biostate analyzes the entire transcriptome. This comprehensive approach captures complex, non-linear relationships between genes and outcomes, allowing for the discovery of novel patterns beyond current biological understanding. This enables the company to:

• Make Biology Predictable: By building what is rapidly becoming the world's largest RNA sequencing database, Biostate's foundation models, trained on diverse RNA expression profiles, capture the dynamic nature of biology.

• Support N-of-1 Approaches: The platform prioritizes individual patient outcomes by analyzing a comprehensive view of a patient’s biological state, helping to minimize toxicity and side effects.

• Enhance Drug Development: The AI models can be used to design new drug molecules and optimize therapy design itself, representing a fundamental transformation in clinical decision-making and patient care.

Market Opportunity

Biostate AI is poised to capture a significant share of the rapidly growing RNA sequencing and precision medicine markets by addressing the key bottlenecks of cost and data accessibility.

• Explosive Market Growth: The global RNA sequencing market is valued at approximately $3.74 billion in 2024 and is projected to reach $23.52 billion by 2034, growing at a CAGR of 20.1%. Similarly, the AI in precision medicine market is expected to grow from $3.15 billion in 2025 to nearly $50 billion by 2034, with a CAGR of over 35%. This growth is fueled by the rising demand for personalized treatments and increased investment in R&D.

• Solving the Cost Barrier to Scale: A major restraint in the RNA sequencing market is the high cost of technology and data generation. Biostate AI's proprietary BIRT and PERD technologies directly solve this problem, reducing per-sample costs significantly and allowing researchers to run 2-3 times more samples on the same budget. This democratizes access to large-scale transcriptomic data, which is essential for training sophisticated AI models.

• Building a Vertically Integrated Data Moat: By offering its low-cost sequencing services, Biostate AI creates a self-reinforcing competitive advantage. The company can collect and standardize a massive, high-quality dataset of RNA expression profiles from its collaborations with institutions like MD Anderson, Cornell Weill, and Stanford Medicine. This proprietary data is the "fuel" for its AI models, which in turn deliver more accurate and robust insights than competitors relying solely on public datasets.

• Shifting to Predictive Healthcare: While traditional biomarker approaches are limited to a small number of genes, Biostate's AI platform analyzes the entire transcriptome. This enables the company to predict disease progression and treatment response weeks or months before symptoms appear, with an initial proof of concept in predicting leukemia recurrence. This capability positions Biostate to not only improve clinical decision-making but also to accelerate drug development and improve the success rates of clinical trials.

Business Model & Traction
Biostate AI's business model is a "self-sustaining" one, likened by the company to a "Netflix for RNA." It is built on a two-pronged approach that leverages its proprietary sequencing technology to fuel its AI platform.

Business Model:

• Affordable RNA Sequencing as a Service: Biostate AI offers its RNA sequencing services to academic, biotech, and biopharma clients at a significantly reduced cost compared to traditional providers. This is the primary revenue stream and serves a dual purpose: it generates immediate income while simultaneously enabling the company to collect vast amounts of high-quality RNA sequencing data.

• AI-Driven Insights and Platform: The company's AI platform, including tools like OmicsWeb Copilot and Quantaquill, is offered to clients to help them analyze their data. While some tools are provided for free to academic and non-profit researchers to encourage adoption and data collection, the ultimate goal is to offer specialized, high-value AI models and services for clinical and drug development applications. This allows Biostate to monetize the insights generated from its growing proprietary dataset.

Traction:

• Significant Customer and Partner Growth: Since commercializing its offering just a few quarters ago, Biostate AI has rapidly gained traction. The company has processed over 10,000 samples for more than 150 collaborating institutions and customers. It has also secured agreements to process several hundred thousand unlabeled samples annually, which will further expand its dataset.

• Proof-of-Concept and Clinical Collaborations: Biostate AI has demonstrated initial proof-of-concept success, including an internal study that predicted disease recurrence in human leukemia patients. The company has established a network of over 100 pilot projects across various disease indications. Key partnerships include collaborations with:

  • Cornell University for leukemia research.

  • The Accelerated Cure Project for multiple sclerosis.

  • Mass General Brigham to develop AI models for melanoma immunotherapy.

  • Kindstar Global Gene Technology in a joint venture to adapt its platform for the Chinese population, focusing on diseases like autoimmune disorders and oncology.

• Global Expansion: Following its Series A funding, Biostate AI has expanded its global reach with strategic partnerships and operations in the U.S., India, and China, demonstrating its commitment to building a diverse, global dataset for its AI models. The company has a subsidiary in India, Bayosthiti, and a joint venture in China, further solidifying its global presence.

Competitors

Biostate AI competes against established players in the sequencing and bioinformatics spaces, as well as emerging AI-driven biotech companies. Its primary differentiator is a vertically integrated platform that combines proprietary, low-cost RNA sequencing with an advanced AI platform, creating a self-reinforcing competitive advantage. Biostate AI operates in a market with several distinct types of competitors:

• Traditional Sequencing Providers: Companies like Illumina, 10x Genomics, and PacBio are major players in the sequencing technology space. While they offer high-quality sequencing, their platforms can be expensive and may not be optimized for the large-scale, low-cost data generation that Biostate AI enables. Biostate's BIRT and PERD technologies directly challenge the high cost and complexity of traditional sequencing workflows by making RNA sequencing more accessible for large studies.

• AI-First Precision Medicine Companies: Firms such as Tempus and Recursion Pharmaceuticals use AI to analyze biological data for drug discovery and patient treatment. While these companies also use AI, many rely on publicly available data or expensive third-party sequencing. Biostate AI differentiates itself by generating its own proprietary, high-quality, and cost-effective dataset, which allows for more robust and less-biased AI models. Other competitors like Cellworks and Immuneering Corporation also focus on AI-driven diagnostics and therapeutics.

• Specialized RNA and Bioinformatics Companies: There are companies that focus specifically on RNA analysis or bioinformatics, such as Alithea Genomics and CellCarta, that offer various RNA sequencing services. Biostate AI's competitive edge comes from its deep integration of both the sequencing technology and the AI platform. This eliminates the "vendor siloing" that often plagues research, where labs must use one company for sequencing and another for data analysis, which can introduce inconsistencies and higher costs.

• Manual Processes: The most fundamental competitor remains the traditional, manual methods of scientific research. For example, labs still frequently rely on expensive and labor-intensive manual processes for RNA extraction and library preparation. By automating and streamlining these steps with technologies like BIRT and PERD, Biostate AI offers a more efficient, scalable, and reproducible alternative.

Funding

Biostate AI has secured a total of $16 million in funding over two rounds. The company's seed round, which closed in July 2024, raised $4 million with Matter Venture Partners as a key investor. This was followed by a $12 million Series A round in May 2025, which was led by Accel and saw participation from other investors including Gaingels, Mana Ventures, Info Edge ventures, and Caltech.