doi.bio/insitro

Insitro

Overview

Insitro is a data-driven drug discovery and development company that uses machine learning and high-throughput biology to transform the way drugs are discovered and delivered to patients. The company was founded in 2018 by Daphne Koller, Stanford's first machine learning professor, and is based in South San Francisco, California. Insitro aims to help pharmaceutical companies avoid costly failures in the drug development process by using predictive models to accelerate target selection, design, and development of effective therapeutics.

Financial Information

Insitro was last valued at $2.5 billion and has raised a total of $643 million in funding. The company's latest funding round, Series C, raised $400 million 3 years ago.

Investors

Insitro has 23 investors, including:

• SoftBank Investment Advisers
• Sovereign Wealth Fund
• Third Rock Ventures
• Alexandria Venture Investments
• Two Sigma Ventures
• Foresite Capital
• Google Ventures

Executive Officers and Board Members

Insitro has a total of 9 executive team members, including:

• Co-Founder, Chief Executive Officer & Board Member
• Chief Financial Officer & Chief Business Officer
• Chief Technology Officer & Chief Exploration Officer and Head of Neuroscience
• Chief People Officer
• Chief Technical Operations Officer

The company also has 12 board members, with 5 of them being disclosed:

• Co-Founder, Chief Executive Officer & Board Member
• [4 others not disclosed]

Products and Services

Insitro's main services involve the use of machine learning and high-throughput biology to predict successful paths for medicine creation. The company has filed 12 patents, with the 3 most popular patent topics being genetics, rare diseases, and molecular biology. Insitro also offers a robust machine learning platform that integrates in vitro cellular data with human clinical data to help redefine diseases and accelerate the development of new medicines.

Research and Development

Insitro is leveraging AI to enhance medical diagnostics for liver disease and is also researching various fields such as ALS, cancer, and neuroscience. The company aims to bring better drugs to patients faster by decoding the complexities of biology through machine learning and data.