Daiichi Sankyo Partners With Meddenovo to Use AI for Designing Cyclic Peptide Drug Candidates

Daiichi Sankyo, one of Japan's largest pharmaceutical companies, has entered a collaboration with Meddenovo Drug Design to apply AI-powered computational approaches to the discovery of novel cyclic peptide-based drug candidates. The partnership pairs Daiichi Sankyo's drug development expertise with Meddenovo's Mexa platform, which combines artificial intelligence and physics-based computational chemistry to design cyclic peptides targeting difficult-to-drug biological targets.

Cyclic peptides are short chains of amino acids whose ends are chemically bonded to form a ring structure. Unlike linear peptides, which are quickly broken down by enzymes in the body, cyclic peptides are more metabolically stable and can bind to protein surfaces that conventional small-molecule drugs cannot effectively target. This makes them a particularly promising modality for oncology, infectious disease, and autoimmune conditions — areas where "undruggable" targets have long frustrated drug developers.

AI meets peptide chemistry

Meddenovo, a European startup, has built what it describes as the largest database of cyclic peptide-like medicines, integrated with AI models that can predict molecular properties, binding affinity, and drug-like characteristics before a single compound is synthesized. The Mexa platform uses a hybrid approach: machine learning models trained on existing peptide data, combined with physics-based simulations that model molecular interactions at the atomic level.

The collaboration reflects a broader industry trend. Among peptide-drug conjugates entering clinical trials since 2022, an estimated 78% have utilized AI-optimized components. Companies like Pepticom and ProteinQure are building entire businesses around AI-driven peptide design, and the third annual Peptide-Based Therapeutics Summit in Boston this month features AI drug design as a major theme.

Beyond GLP-1: the cyclic peptide opportunity

While public attention has focused overwhelmingly on GLP-1 receptor agonists for obesity — drugs like semaglutide, a GLP-1 receptor agonist, and tirzepatide, a dual GIP/GLP-1 receptor agonist — the therapeutic potential of peptides extends far beyond metabolic disease. Cyclic peptides in particular are being investigated as targeted cancer therapeutics, antimicrobial agents to combat antibiotic resistance, and modulators of protein-protein interactions in neurodegenerative disease.

For Daiichi Sankyo, the partnership extends its modality portfolio beyond the antibody-drug conjugates (ADCs) that have driven its recent oncology success — including the blockbuster Enhertu (trastuzumab deruxtecan). Cyclic peptide-drug conjugates could offer similar targeted delivery with potentially different pharmacokinetic profiles.

The financial terms of the deal were not disclosed. Both companies indicated that initial programs will focus on oncology targets, with the potential to expand into other therapeutic areas.