About insitro
insitro uses machine learning and data at scale to decode the complexities of biology and unlock transformative new medicines.
Mission & Story
Mission
At insitro, we are building a different kind of drug company to bring better drugs faster to the patients who can benefit most. Through the power of machine learning (ML) and data at scale, we decode the complexities of biology to unlock transformative new medicines.
Founding Story
Founded by Daphne Koller (CEO & Founder) who set out to create a unique culture that unites individuals from diverse backgrounds in a single team, bringing together life scientists, data scientists, engineers, and drug hunters.
Clinical Focus
Medical conditions and clinical areas addressed by insitro.
Who It Serves
Milestones & Awards
Recent Milestones
Acquired CombinAbleAI to complete full-stack modality-agnostic AI platform (TherML). Received $25M milestone payments from Bristol Myers Squibb for ALS target discovery. Completed first AI-enabled human genetics study of brown adipose tissue. Extended collaborations with Bristol Myers Squibb and Eli Lilly. Nominated new ALS targets. Presented MASH data at ADA 2026.
Awards & Recognition
Poster of Distinction at The Liver Meeting 2025 for work on IRS1 and MASLD genetic architecture
Key Partnerships
Social & Media
Follow on
Latest Updates

insitro to Acquire CombinAbleAI to Complete its Full Stack, Modality-Agnostic AI Platform for Drug Discovery and Design

Introducing insitro’s TherML™: Rapidly engineering the right therapeutic for the right target

insitro and Bristol Myers Squibb Collaboration Expanded with Nomination of New Targets

Rewriting the Playbook for ALS Drug Development

insitro Validates AI-Enabled POSH Platform in Nature Communications, Bridging Critical Gap in Drug Discovery
Company Details
- Founded
- 2018
- Headquarters
- South San Francisco, CA, USA
- Employees
- 350
- Stage
- series c
Work here?
Claim this listing to update company information and connect with our audience.
Claim This ListingOfficial Sources
Similar Companies in this Market
View all 64 →A2A Pharmaceuticals
AI-driven pharmaceutical company focused on discovering and developing novel drug candidates using computational biology and machine learning.
AbCellera
AbCellera uses AI and machine learning to discover and develop antibody-based therapeutics and vaccines.
Absci
Absci uses AI-powered computational biology and machine learning to accelerate drug discovery and optimize therapeutic proteins and antibodies.
Adaptyv Bio
11-50 employees
Adaptyv Bio operates the world's fastest protein validation lab, providing automated experimental testing services for AI-designed proteins. The company enables protein engineers to validate binding, expression, and thermostability of novel protein designs through a fully automated platform with 3-week turnaround times.
Aitia
Aitia is a drug discovery and development company leveraging AI and computational biology to identify novel therapeutic targets and accelerate drug development.
Anagenex
Anagenex is a biotechnology company focused on drug discovery and development. The company appears to operate in the pharmaceutical research space, though specific details about their technology platform, therapeutic areas, and target markets are not available from the provided content.
Aqemia
Aqemia is a drug discovery company advancing next-generation medicines using generative AI and deep physics. The company combines AI-augmented discovery with computational chemistry to develop novel therapeutics at scale.
Arctoris
51-200 employees
Arctoris is a Partnership Research Organisation (PRO) providing automated wet lab biology R&D and data generation services for biotech, techbio, and pharma companies through its Ulysses® robotic platform.
Data Accuracy Notice: Company information on HealthAI Central is compiled from public sources and updated regularly. While we strive for accuracy, details such as funding figures, employee counts, and product offerings may change. We recommend verifying critical information directly with the company before making business decisions.
