At the convergence of human biology and machine learning lies a healthier you.

Daphne Koller

Problem Tech Solves


Tech Brief

Despite the amazing advances made across medicine, biology and genomics over the last several decades, there is still a challenge in finding treatments for patients across many diseases. The cost of drug development has also grown exponentially, while the industry continues to be hit with many more failures and abandonment of candidates than successes in drug development. Enter insitro. Launched in 2018, they are working to tackle these issues head on, applying state-of-the-art technologies to create massive data sets that enable the power of modern machine learning methods to be brought to bear on key bottlenecks in pharmaceutical R&D. Their data-driven drug discovery and development uses machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients.

Tech Differentiators

The idea of incorporating artificial intelligence and machine learning into drug development has catapulted into the biotechnology industry in the last several years, but insitro is doing it differently. Today, low success rates in drug development are driven by a limited ability to make predictions at key steps throughout. insitro is using machine learning to build models that improve predictions on which paths to take during the drug development process. To do this, insitro deploys 3 core pillars 1) machine learning-enabled statistical genetics on phenotypically rich, multimodal datasets to uncover novel targets, patient segments, and clinical biomarkers; 2) develop predictive cell-based disease models empowered by state-of-the-art bioengineering technologies and automation at scale; and 3) advance machine learning-enabled therapeutics design driven by data generation at scale with a proprietary platform for DNA-encoded small molecule screening, all of which, when integrated are designed to enable more efficient and streamlined drug discovery.


In April 2019, insitro executed its first major collaboration with Gilead Sciences focused on discovering novel targets for patients with nonalcoholic steatohepatitis (NASH). The deal involved up to $50M in operational milestones, and up to $1B in downstream milestones. Since executing that deal, insitro has built out and demonstrated the capabilities of its target discovery platform, leading to the first milestone payment from Gilead. More recently, in October 2020, insitro and Bristol Myers Squibb entered a five-year strategic collaboration focused on the discovery and development of novel therapies for the treatment of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, insitro is going beyond target discovery into designing novel molecules and creating data packages that enable those molecules to move into clinical trials.

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