We believe David, Ashwin, and the team are laying the groundwork for a new era of diagnostics and therapeutics, and we’re thrilled to partner with them on this journey.” An expanding client base: 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.
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 realized they could snowball a cheaper and more effective RNAseq operation into a one-stop shop for precision medicine. Unlocking the power of RNAseq through GenAICurrently, few molecular biology labs make the most of existing RNA datasets—or the power of machine learning to analyze them. That’s because conventional RNAseq suffers from three key limitations: It’s expensive, pricing most labs out of scaling their biotech research ambitions.
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. AI bridges molecular data and patient interventions: 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.
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