Pipeline

Nectin-4 is a tumour-associated antigen (TAA) that is commonly overexpressed on numerous solid tumour types, including urothelial, head and neck, and triple-negative breast cancer. Nectin-4 is also expressed at low levels on normal, healthy tissues, which limits current ADC therapies due to high rates of dose-limiting, on-target, off-tumour toxicities. This highlights a need for alternative approaches for anti-cancer therapeutics that can selectively target Nectin-4 expressing solid tumours. 

Through the tight integration of high-throughput functional cell-based experimentation with machine learning (ML), LabGenius’ proprietary lead optimisation platform (EVA™) generated a highly selective and potent trivalent VHH-based Nectin-4 x CD3 T-cell engager (TCE), LGTX-101. By harnessing avidity-driven selectivity, LGTX-101 is able to differentiate between healthy and diseased cells based on differential TAA expression, demonstrating >70,000-fold killing selectivity in a T-cell-mediated tumour cell killing assay. LGTX-101 is highly efficacious in vivo with complete tumour regression observed in all tumour-bearing mice treated with our lead candidate.