Iterative active learning for the rapid discovery of best-in-class multispecific antibody therapeutics
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The emergence of ML-enabled technology platforms that aim to enhance molecule performance have the potential to revolutionize the way we approach drug discovery. However, without a purpose-built tech stack that puts data quality at the heart, many are destined to fail. This talk will focus on the deep integration of predictive assays, data generation, data capturing, and data pre-processing needed to enable iterative active learning cycles for lead optimization.
Link to join virtually: https://cam-ac-uk.zoom.us/j/81322468305
This talk is being recorded.
This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series.
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