VERGE GENOMICS | MedPath

Eli Lilly and Alchemab Forge $415M Partnership for Novel ALS Antibody Therapy

18 days ago

• Eli Lilly has entered a $415 million licensing agreement with UK-based Alchemab Therapeutics for ATLX-1282, a first-in-class antibody therapy for amyotrophic lateral sclerosis (ALS). • The novel antibody was discovered using Alchemab's AI-powered platform that identified protective antibodies in individuals with genetic mutations for frontotemporal dementia (FTD) who remained healthy into old age. • Alchemab will conduct early Phase 1 trials before Lilly takes over further development and commercialization, leveraging its expertise in neurological conditions to advance the therapy.

Verge Genomics Launches First Clinical Trial of AI-Discovered ALS Drug VRG50635

4 months ago

• Verge Genomics has initiated Phase 1 clinical trials for VRG50635, a novel PIKfyve inhibitor discovered using their AI platform ConVERGE, marking a significant milestone in AI-driven drug development. • The drug candidate, developed in just four years, targets a novel mechanism involving lysosomal function in ALS, demonstrating promising neuron preservation effects in preclinical studies. • This achievement positions Verge Genomics among select companies successfully transitioning AI-discovered drugs to clinical trials, supported by major pharmaceutical investors including Eli Lilly and Merck & Co.

AI Accelerates Drug Discovery and Clinical Trials, Reducing Time and Costs

8 months ago

• AI is revolutionizing drug discovery by accelerating target identification, drug molecule design, and clinical development, potentially reducing costs and increasing the probability of success in Phase 2 trials. • Generative AI analyzes vast datasets to identify promising drug candidates and predict molecular interactions, while AI-focused biotechs are rapidly advancing drug candidates into clinical trials. • AI is enhancing clinical trial efficiency through automated data analysis, predictive modeling for site selection, improved patient engagement, and faster recruitment, leading to quicker trial completion and reduced participant numbers. • The integration of AI in drug discovery and development promises faster, cheaper, and better-value outcomes by minimizing experimental overhead, improving trial efficiency, and balancing drug properties.