Juvena Therapeutics, a clinical-stage biotechnology company specializing in tissue restorative biologics, has announced a strategic partnership with pharmaceutical giant Eli Lilly and Company to accelerate the discovery of treatments targeting muscle health and body composition. The collaboration represents a significant convergence of artificial intelligence-driven drug discovery with established pharmaceutical development expertise.
AI-Powered Platform Drives Discovery
The partnership centers on Juvena's proprietary JuvNET platform, described as the world's first fully integrated, AI-enabled screening system for mapping the therapeutic potential of stem cell-secreted proteins. This platform combines a comprehensive database linking secreted proteins to specific disease phenotypes with advanced in silico and in vitro human cell screening capabilities, pharmacology, and protein engineering technologies.
"We are thrilled to demonstrate the power of our fully integrated AI-enabled platform to accelerate the discovery and development of therapeutics with transformative potential that promote healthspan in individuals facing chronic conditions like obesity and frailty," said Dr. Hanadie Yousef, co-founder and CEO of Juvena Therapeutics.
The collaboration will specifically identify muscle-targeting drug candidates from Juvena's proprietary library of human stem-cell secreted proteins, focusing on applications for improved body composition and muscle health.
Addressing Global Health Challenges
The partnership targets a significant global health burden, with obesity affecting one in eight people worldwide according to the companies. Dr. Jeremy O'Connell, co-founder and Chief Science Officer of Juvena Therapeutics, emphasized the clinical rationale behind the collaboration.
"Bringing together Lilly's decades-long experience in metabolic diseases with Juvena's AI expertise and deep understanding of human stem-cell secreted proteins with therapeutic potential, we aim to accelerate innovation that advances the standard of care in obesity management and helps people live their best lives," O'Connell stated.
The scientific foundation for the partnership rests on established connections between muscle health and broader metabolic outcomes, including enhanced metabolism, mobility, and long-term disease prevention.
Financial Structure and Development Pathway
Under the collaboration terms, Juvena will receive an upfront payment, equity investment, and potential development and commercialization milestone payments. The company will grant Lilly exclusive licenses to identified lead candidates, with Lilly assuming responsibility for subsequent research, development, and commercialization activities.
This structure allows Juvena to leverage its discovery platform while benefiting from Lilly's extensive development and commercialization capabilities in metabolic diseases.
Current Pipeline and Platform Capabilities
Juvena's existing pipeline demonstrates the platform's potential, with the company recently announcing the first clinical trial for its lead program, JUV-161, an engineered biologic derived from a natural secreted protein that enhances muscle regeneration and health.
The company is also developing JUV-112, a preclinical candidate for obesity and metabolic diseases that induces lipolysis without appetite suppression while sparing muscle mass. This candidate operates through an energy expenditure mechanism based on a secreted protein that functions independently of incretin pathways.
Beyond muscle and metabolic applications, Juvena's platform has generated multiple therapeutic candidates with tissue restorative benefits spanning pulmonary and hepatic fibrosis and osteoarthritis, demonstrating the broader potential of their stem cell-secreted protein approach.
The collaboration represents a significant validation of AI-driven drug discovery platforms in addressing complex metabolic and muscle health challenges, potentially accelerating the development of novel therapeutic approaches for conditions affecting millions of patients globally.
