Turning Multi Specific Antibody Design into an Engineering Discipline with AI

Multi-specific antibodies promise to unlock complex biology that conventional monoclonals can’t touch, but their added mechanisms of action also introduce safety and developability risks. These antibodies—especially T‑cell engagers—behave differently from traditional monospecific antibodies, and seemingly minor architectural tweaks can cause disproportionate shifts in potency, selectivity, and cytokine release. LabGenius is trying to turn multi-specific design from an intuition-driven art into a genuine engineering discipline by generating proprietary data at scale and feeding them back into machine learning models. Angus Sinclair, chief scientific officer of LabGenius, discusses why many safety failures in early solid-tumor T‑cell engagers were effectively locked in at design, how the company’s AI platform engineers multi-specific T‑cell engagers that are both potent and selective in solid tumors, and where AI is actually adding value in multi-specific design today.