Prellis Biologics has announced a multi-target drug discovery collaboration with Eli Lilly (Lilly).
In this strategic collaboration, the unique capabilities of Prellis' EXIS and AntiGen AI platforms will accelerate the discovery of highly diverse and fully human antibodies for multiple disease targets.
Under the terms of the agreement, Prellis and Lilly will jointly discover and develop human antibody therapeutics for selected targets.
The partnership combines Prellis' lymph node organoid technology, which replicates human immune response in vitro, with AI-driven optimisation to accelerate therapeutic efficacy, safety and manufacturability.
Prellis will receive an up-front payment, development and sales milestones and royalties for the licenced antibodies.
"With industry-leading speed, the EXIS platform generates diverse, high-affinity antibodies, derived from fully human artificial lymph node organoids against a wide array of targets that include classes such as GPCRs."
"These hits are then matured by artificial intelligence into drug candidates," said Mike Nohaile, CEO of Prellis.
"Moreover, by coupling organoid-derived biology with AI, we solve one of AI's biggest limitations in drug development: access to vast quantities of high-quality, fully human training data for novel targets."
"Ultimately, the future of drug development will be determined by the best data and that is exactly what we're delivering."
Whilst there have been previous commercial biological AI systems that use techniques such as imaging to detect tumours, Prellis' platform is the first to design drugs by combining a living biological system with generative AI refinements.
This has the advantage of using real-world, fully human biology with feedback loops and AI training systems that continuously improve drug candidates.
Prellis' vision is to replace previous biological drug discovery efforts with a more versatile and scalable bio-AI hybrid.
Les Miranda, Chief Scientific Officer of Prellis, added, "Our mission is to transform how antibody-based therapies are developed to create more precise, effective and accessible candidates."
"We believe this agile approach represents the future of medicine, where biology and artificial intelligence synergistically converge to address complex diseases faster than ever before."