Winston is the VP Computational Sciences and Engineering at LabGenius, where he leads a team of experts in data science, machine learning, and software development to expand LabGenius’ ML-driven discovery platform capabilities. He has extensive experience leading the development and application of computational tools to advance both antibody therapeutics (BigHat Biosciences) and diagnostics (Serimmune). Winston holds a PhD in Biomedical Informatics from Stanford University, where he was a NSF GRFP fellow.
T-cell engagers (TCEs) promise breakthroughs in the treatment of solid tumors, but their progression in the clinic is limited by on-target, off-tumor toxicity. In this talk, I describe how our platform integrates active learning, automation, and high-throughput functional assays to efficiently identify highly selective and potent TCEs. I highlight our utilization of the design-build-test-learn ecosystem to generate high-quality data that powers our machine learning models and therapeutic assets.
· Exploring the current state of antibody modalities and emerging therapeutics
· Advances in established formats: next generation bispecifics and ADCs
· The potential of AI in antibody engineering – what place does this technology hold in antibody development?