AI/ML in Practice: Machine-learning Prediction of Chromatographic Retention Times for Small Molecules in Pharmaceutical Applications
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Daniel Vik from Amgen Research Copenhagen, Denmark discusses the motivation behind applying machine learning to chromatographic retention time prediction and its growing importance in modern pharmaceutical research. He shares insights into the challenges of developing robust predictive models, their role in supporting high-throughput drug discovery workflows, and the potential of artificial intelligence to make analytical chemistry more efficient and scalable.