BMS and insitro Expand AI-Driven Collaboration to Develop Novel ALS Therapies with Potential Deal Value Exceeding $2 Billion

On October 14, south of San Francisco, California, insitro, a pioneer in machine learning-driven drug discovery and development, and Bristol-Myers Squibb (NYSE:BMY) announced the next phase of their collaboration aimed at discovering new molecules that could become potential new therapies for Amyotrophic Lateral Sclerosis (ALS).To date, insitro has raised more than $700 million and is building a "platform pipeline" focused on metabolic diseases and neuroscience.

The extension of this collaboration will leverage insitro’s artificial intelligence ChemML™ platform to design novel drugs targeting newly identified ALS targets in the first biological evaluation phase, potentially providing up to $20 million in new funding over the one-year extension period. Successful delivery of a new therapeutic through this partnership could result in payments to insitro of over $2 billion in total value across discovery, development, regulatory, and commercial milestones, in addition to royalties.

Daphne Koller, Ph.D., Founder and CEO of insitro, stated:"Our collaboration with Bristol-Myers Squibb has uncovered new targets that have the potential to address the underlying biology of ALS. We are now moving into the next phase — translating these discoveries into drugs. With our end-to-end drug design platform ChemML, we can rapidly advance new targets into sophisticated small-molecule leads, leveraging a differentiated set of capabilities spanning AI-driven modeling, medicinal chemistry, and structural biology. As we progress these initial candidates, we will continue to work on identifying additional novel targets with the potential to change the course of the disease. Our goal remains steadfast: to deliver truly transformative treatments that enable ALS patients to live longer."

Discovering and Advancing Novel ALS Drugs Using insitro's ChemML™ Platform

insitro's proprietary ChemML™ platform enables end-to-end small molecule discovery and optimization through internal development and the acquisition of Haystack Sciences. Despite significant efforts to apply artificial intelligence/machine learning to various aspects of drug discovery, advancing new therapies for complex and challenging targets remains a slow and costly iterative process. ChemML™ seamlessly integrates multiple computational and laboratory functions to rapidly design and optimize new small molecule therapies across diverse disease areas. These measures include:

Large-Scale Data Generation: The proprietary Quantitative Adaptive Library (QAL) can generate hundreds of millions of drug-target binding and selectivity data points, informing machine learning models and supporting rapid, machine learning-driven data generation.

Predictive Pharmacology Property Modeling: Advanced ML models for Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET, including in vivo PK), supported by a large high-quality dataset in collaboration with Eli Lilly and Company.

AI-Driven Design Cycle: A proprietary iterative engine that becomes smarter at every turn while driving the "Design-Make-Test" cycle, enabling the platform to combine computational predictions with physical experimental data to intelligently guide each round of synthesis.

Powerful Computing Infrastructure: A large computing cluster consisting of 192 H100 GPUs, providing the necessary capabilities for high-end machine learning modeling and physics-based simulations.

Philip Tagari, Chief Scientific Officer of insitro, stated:"insitro's proprietary machine learning discovery engine uncovers new biology, enabling us to identify multiple differentiated, high-confidence novel ALS drug targets at record speed. These targets are supported by strong evidence, including functional data demonstrating motor neuron survival and the reversal of multiple downstream markers of ALS pathology. Our integrated ChemML platform has generated new compounds that can be optimized using insitro's ML-powered medicinal chemistry to address technically challenging targets."

ALS is a devastating, progressive neurodegenerative disease characterized by the selective loss of upper and lower motor neurons. The disease causes muscle weakness, respiratory failure, and eventually death, with a median survival of 3 to 5 years after diagnosis.

Since nearly 90% of ALS cases are sporadic, the initial phase of the collaboration focuses on identifying cross-disciplinary biology—the common underlying pathology of the disease—to develop therapies that can help as many patients as possible with both familial and sporadic ALS. Both insitro and Bristol-Myers Squibb are firmly committed to accelerating the pace to bring new treatments to patients and families awaiting transformative therapeutic options.