Latent Bio resides at the intersection of geometric deep learning, chemistry, biology, and clinical data—reimagining how drugs are discovered and optimizing translation to and through the clinic.

With scientific roots in Yale's Krishnaswamy Lab, Latent Bio is implementing practical, business-focused, applications of GDL for drug discovery, biomarker discovery, and characterization of clinical populations to optimize assets for clinical development and partnerships.

The company has engaged with Krishnaswamy Lab’s deep expertise in geometric and manifold-based machine learning to build a platform that reads the true underlying shape and structure of biological and chemical data. This enables Latent Bio and its partners to navigate toward promising drug discoveries with far greater precision than traditional methods allow. Where conventional drug development relies on slow, iterative cycles of molecular tweaking and screening, Latent Bio's technology compresses that process, helping itself and R&D partners identify the right molecules and biomarkers faster and with greater confidence. For pharmaceutical partners and biotech researchers working across many indications, this is a platform built to make drug discovery and development smarter from the start.