Insitro To Drive Drug Discovery With Machine Learning

Insitro, an early-stage company based in South San Fracisco, CA, is a data-driven drug discovery and development company using machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients.

The company is applying state-of-the-art technologies from bioengineering 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. The resulting predictive models are used to accelerate target selection, to design and develop effective therapeutics, and to inform clinical strategy.

The Problem

72 cancer therapies approved between 2002 and 2014 only bought patients an extra 2.1 months of life compared with older drugs, researchers have found. And there’s no evidence that two-thirds of the drugs approved in the recent years improve survival at all. The life extension property of these drugs has to be further qualified by the quality-of-life question that results when side effects tend to be toxic. Yet the system continues to spin out new drugs that are billions of dollars in making and a decade in development with a 5% success rate. The name for this condition is Eroom’s law (Moore’s law spelled backwards). It is the concept that drug discovery is becoming slower and more expensive, despite improvements in technology, a trend first observed in the 1980s.

The Solution

Insitro’s approach to rethinking drug discovery and development is fueled by three strategic pillars:

  • machine learning-enabled statistical genetics on deeply phenotyped human cohorts to discover targets and patient segments with potential to inform clinical strategy,
  • predictive cell-based disease models to discover targets, patient segments and drugs;
  • and machine learning-enabled therapeutics design.

According to the company, the application of these pillars has built the foundation of the company’s pipeline, which includes efforts in neuroscience and liver diseases that are being advanced both internally and through strategic partnerships.

The Founder

Daphne Koller is an Israeli-American computer scientist and has been a Professor in the Department of Computer Science at Stanford University and a MacArthur Fellowship recipient. She is one of the founders of Coursera, an online education platform. Koller was featured in a 2004 article by MIT Technology Review titled “10 Emerging Technologies That Will Change Your World” concerning the topic of Bayesian machine learning. In 2020, Fast Company magazine listed her as one of the most creative people in business.

Insitro To Drive Drug Discovery With Machine Learning was last modified: March 15th, 2021 by Simons Chase