This report is published by Patsnap.

This case study explores Chai-2, a generative diffusion model developed with OpenAI support, which represents a leap forward in de novo antibody design. Unlike conventional methods, Chai-2 generates protein sequences with stable 3D structures in under two weeks—a 100-fold improvement in efficiency. Leveraging Patsnap’s Lao Tzu Dataset, the model enhances antibody design accuracy, reduces reliance on costly experimental methods, and enables large-scale exploration of novel sequences. Despite current limitations, such as validation challenges and dataset biases, diffusion models are set to revolutionize antibody development and broader protein engineering.

Explore how AI-driven models like Chai-2 can redefine your drug discovery pipeline with Patsnap’s datasets.

Patsnap empowers global IP and R&D leaders with AI-augmented intelligence solutions, so they can make high-impact innovation decisions.

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