Episode: 62 - AI/ML in Antibody Discovery and Engineering: Reality, Hope, Future, and Hype
The Chain: Protein Engineering Podcast
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Challenges and Opportunities in Applying Machine Learning to Protein Design
The chapter explores the complexities and challenges in applying machine learning to proteins and biologics, emphasizing the uniqueness of each molecule and the difficulties in developing consistent models across diverse proteins. It discusses the necessity of unique datasets for individual antibodies and debates whether transfer learning can be effective in this context. The chapter also highlights the potential applications of machine learning in antibody discovery, engineering, and design, emphasizing the role of AI as an assistant to project teams and the importance of combining human expertise with algorithmic approaches for optimal results.
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