insitro uses machine learning and data generation at scale to transform drug discovery and development. Its core platform develops predictive machine learning models applied to target identification, lead discovery, and therapeutic design, supported by predictive cell-based disease models and statistical genetics on deeply phenotyped human cohorts. The company has enabling collaborations with Gilead in NASH and Bristol Myers Squibb in ALS and acquired Haystack Sciences to add a high-throughput chemistry platform for ML-driven molecular design. insitro was founded in 2018 and is located in South San Francisco, CA. Its pipeline includes efforts in neuroscience and liver diseases advanced internally and through strategic partnerships. The company plans to use new financing to expand platform capabilities and pipeline, access enabling datasets and complementary technologies, and potentially in-license de-risked assets. insitro applies machine learning and high-throughput biology to transform drug discovery and development, building large, disease-relevant biological datasets and predictive models. The company has assembled a multidisciplinary team of computational scientists, engineers, biologists, translational scientists, and drug developers. insitro has developed a platform for producing biological data at scale and reports scientific progress on ML-driven disease models that aim to predict human clinical outcomes. The company is focusing initial therapeutic work in liver and CNS disease and cites a strategic partnership with Gilead as a milestone. Proceeds from financing will be used to expand technology and automation, scale data generation, pursue genetically validated targets, identify patient-segmentation biomarkers, and advance therapeutics in genetically defined populations. insitro is located in South San Francisco, CA.

Total raised

$543M

Funding rounds

2

Latest round

Series C

Latest activity

Mar 2021