Logic-Gated Killing Selectivity in Multispecific Multivalent T-Cell Engagers via Machine Learning (ML) & High-Throughput Functional Screening
- LabGenius Therapeutics has pioneered the development of EVA™, an ML-driven, closed-loop antibody discovery engine. EVA™ generates large volumes of biologically rich experimental data, which are used to train computational models. These models are used to co-optimise molecules across multiple therapeutic parameters, including potency, efficacy, selectivity and developability
- By integrating high-throughput experimentation and computational learning in this way, EVA™ identifies novel, high-performing antibody molecules, often with nonintuitive designs
- The company’s lead programme, LGTX-101, is a selectivity-enhanced Nectin-4 x CD3 T-cell engager featuring a novel 3+1 molecular architecture. In preclinical studies, LGTX-101 has demonstrated robust tumour-killing activity with minimal activity against Nectin-4–expressing healthy cells