Biostate AI Secures $12 Million in Series A Funding Led by Accel
•Biostate AI secured $12 million in Accel-led Series A funding.
•The company plans to expand access to RNA sequencing for precision medicine.
•Founders highlight the incorporation of AI to forecast disease progression and drug response.
Biostate AI, a startup focused on AI and RNA sequencing, said on Tuesday that it has raised $12 million in a Series A round led by Accel. The investment round also saw Gaingels, Mana Ventures, InfoEdge Ventures, and repeat investors Matter Venture Partners, Vision Plus Capital, and Catapult Ventures. The new capital will go toward increasing access to precision medicine integration, starting with RNA sequencing (RNAseq) services for molecular research in the US.
Biostate AI was established in 2023 by Ashwin Gopinath and David Zhang. Biostate AI is building predictive generative models of disease progression and drug response using RNA sequence data. "Rather than working on diagnostics and therapeutics as individual, isolated problems for each disease, we think that contemporary AI can be leveraged to see and solve every disease in its entirety. Each diagnostic I have built has been designed to bring answers closer to the patient.". Biostate is a huge leap because it makes the whole transcriptome accessible," said Zhang, Co-founder and CEO at Biostate AI.
The company is now focused on bringing RNA sequencing within everyone's reach and developing predictive models to support clinical decision-making. Houston, Texas-based Biostate AI is striving to overcome challenges in RNA sequencing by combining biochemical approaches with generative AI.
By reducing the expense related to RNAseq and streamlining workflows, the firm is facilitating researchers to amplify their work and generate trustworthy data. "Just as ChatGPT transformed language comprehension by learning from trillions of words, we are deciphering human disease's molecular language from billions of RNA expressions in millions of samples.". We’re achieving for molecular medicine what large language models accomplished for text, optimizing raw data so that algorithms can truly excel,” remarked Gopinath, Co-founder and CTO of Biostate AI and a former assistant professor at MIT.
•The company plans to expand access to RNA sequencing for precision medicine.
•Founders highlight the incorporation of AI to forecast disease progression and drug response.
Biostate AI, a startup focused on AI and RNA sequencing, said on Tuesday that it has raised $12 million in a Series A round led by Accel. The investment round also saw Gaingels, Mana Ventures, InfoEdge Ventures, and repeat investors Matter Venture Partners, Vision Plus Capital, and Catapult Ventures. The new capital will go toward increasing access to precision medicine integration, starting with RNA sequencing (RNAseq) services for molecular research in the US.
Biostate AI was established in 2023 by Ashwin Gopinath and David Zhang. Biostate AI is building predictive generative models of disease progression and drug response using RNA sequence data. "Rather than working on diagnostics and therapeutics as individual, isolated problems for each disease, we think that contemporary AI can be leveraged to see and solve every disease in its entirety. Each diagnostic I have built has been designed to bring answers closer to the patient.". Biostate is a huge leap because it makes the whole transcriptome accessible," said Zhang, Co-founder and CEO at Biostate AI.
The company is now focused on bringing RNA sequencing within everyone's reach and developing predictive models to support clinical decision-making. Houston, Texas-based Biostate AI is striving to overcome challenges in RNA sequencing by combining biochemical approaches with generative AI.
By reducing the expense related to RNAseq and streamlining workflows, the firm is facilitating researchers to amplify their work and generate trustworthy data. "Just as ChatGPT transformed language comprehension by learning from trillions of words, we are deciphering human disease's molecular language from billions of RNA expressions in millions of samples.". We’re achieving for molecular medicine what large language models accomplished for text, optimizing raw data so that algorithms can truly excel,” remarked Gopinath, Co-founder and CTO of Biostate AI and a former assistant professor at MIT.
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