insitro, a machine learning-enabled drug discovery and development company, entered three strategic agreements with Lilly focused on advancing potential new medicines for metabolic diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD), based on targets identified using insitro’s AI/ML-based platform.
 
Current therapies for metabolic diseases primarily manage symptoms without addressing root causes. This collaboration aims to shift this paradigm by combining insitro’s machine learning platforms, particularly directed at early biology discovery, with Lilly’s expertise in drug delivery and metabolic disease biology.
 
Under the first two agreements, insitro has an option to in-license clinical stage, ternary N-acetylgalactosamine (GalNAc) delivery technology from Lilly that it will combine with two different small interfering ribonucleic acid (siRNA) molecules discovered and developed by insitro, each specifically directed toward a different target in the liver.
 
Under the third agreement, insitro and Lilly will collaborate to discover and develop an antibody for a third novel target for metabolic disease. As part of the collaboration, the companies will work together on the early preclinical development activities until development candidate nomination, when insitro will be responsible for all remaining development and commercialization.
 
Under these agreements, insitro will partner with Lilly Catalyze360-ExploR&D, to help accelerate partner science. Across all agreements, insitro retains full global rights to its programs, with Lilly being eligible to receive potential milestones and royalties.
 
“We are innovating not only in our biology discovery, but also how we partner with industry leaders like Lilly to accelerate our therapeutic programs toward the clinic,” said Daphne Koller, Ph.D., founder and CEO of insitro. “Our proprietary AI/ML platform, leveraging multimodal data at scale, computational power, and genetics, has identified several high-value targets with extensive support in human genetics and translatable models. These could help provide transformative impact for patients with metabolic disease by addressing it at its root, and bringing together the best of biotech and pharma skill sets accelerates our impact.”