AI/ML for biotherapeutics is constrained by the scale and quality of training data. In this session, Twist Bioscience will present multiple workflows for strategies to bridge this gap using highfidelity synthetic DNA platforms and bespoke data outputs that integrates next-generation synthesis, production and characterisation directly into the Design-Make-Test-Learn cycle. Case studies will illustrate how LLMs are validated using Twist “off-the-shelf” data sets, how high-throughput iterations of make-test cycles can be used to compare and train new models, and when in silico (de novo) designed libraries coupled with wet-lab panning and screening can simultaneously generate lead therapeutic candidates while also validating and training generative models. Learn how scalable and innovative antibody services transform ML into a powerful engine for rapid biotherapeutic discovery.
Colby Souders, Chief Scientific Officer, Twist Bioscience
