Business Overview






Series B



3.8 years

insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients. At insitro, we are rethinking the entire drug discovery process, from the perspective of machine learning, human genetics, and high-throughput, quantitative biology. Over the past five decades, we have seen the development of new medicines becoming increasingly more difficult and expensive, leaving many patients with significant unmet need. We’re embarking on a new approach to drug development – one that leverages machine learning and unique in vitro strategies for modeling disease state and designing new therapeutic interventions. We aim to eliminate key bottlenecks in traditional drug discovery, so we can help more people sooner and at a much lower cost to the patient and the healthcare industry. We believe that by harnessing the power of technology to interrogate and measure human biology, we can have a major impact on many diseases. We invest heavily in cutting edge bioengineering technologies to enable the construction of large-scale, high-quality data sets that are designed specifically to drive machine learning methods. Our first application is to use human genetics, functional genomics, and machine learning to build a new generation of in vitro human cell-derived disease models whose response to perturbation is designed to be predictive of human clinical outcomes. This cannot be done without great people. We are bringing together an outstanding team of people whose expertise spans multiple disciplines – life sciences, machine learning, human genetics, engineering, and drug discovery – and building a unique culture where people from diverse backgrounds work as a single team towards a common goal. We offer opportunities to collaborative people with expertise in life science and computational science. Join us to help bring better health to more people, faster and cheaper.

Employee Count





Employee counts updated on a monthly basis.


Stock Chart

Founders (1)

hiddenDaphne Koller
CEO and Board MemberAI Expert, Serial Entrepreneur

AI Team (0)

Board and Advisors (1)

hiddenVijay Pande
Board Member

Revenues (0)

Funding Rounds (2)


RoundDateCapital RaisedValuationInvestors
May 2020
May 2018

M&A Events (0)

Investors (11)

InvestorInvestor TypeLocation
hiddenAndreessen Horowitz
Venture CapitalUnited States
hiddenArch Venture Partners
Venture CapitalUnited States
hiddenTwo Sigma Ventures
Venture CapitalUnited States
hiddenForesite Capital
Venture CapitalUnited States
hiddenThird Rock Ventures
Venture CapitalUnited States
hiddenCanada Pension Plan Investment Board
Corporate Venture CapitalUnited States
hiddenAlexandria Venture Investments
Corporate Venture CapitalUnited States
hiddenBezos Expeditions
hiddenMubadala Investment Company

Patents (0)

Research Publications (0)

Certifications (0)

AI Technology Stack


Powerful machine learning requires powerful data. Our data pipelines and automation infrastructure allow us to go beyond artisanal chemistry and biology, and rapidly generate massive amounts of high-quality data. This scale allows us to span much more of the diversity of human disease and potential therapies. With massive amounts of high quality data, we then develop and deploy a variety of leading-edge machine learning methods. As witnessed in other industries, machine learning can make sense of vast amounts of high-dimensional data that are beyond human ability to interpret. Our machine learning models allow us to differentiate between cell states at much finer granularity and predict disease-relevant clinical traits.

Jobs (0)

NameStatusFoundedStageFundingValuationEmployees1YR Headcount GrowthFounder UnitsFounder Classification

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