Cheminformatics podcasts

Tim Wahlberg of CAS speaks with Rafael Rosengarten about the role of curated chemical knowledge in AI-assisted drug discovery. They examine scientific data quality, harmonisation and expert curation, and consider how reliable information can help researchers formulate questions and evaluate answers from large language models.

Hosted by Rafael Rosengarten

Alex Wiltschko explains efforts to predict smell from molecular structure and to give computers a useful representation of odors. He discusses graph neural networks, the difficulty of collecting olfactory data, and how learned embeddings connect chemistry to perception and potential practical applications.

Hosted by Sam Charrington

Surya Ganguli and Bowen Liu join Vijay Pande to examine how machine learning can support biological discovery and drug development. They compare physics-based modelling, learned molecular representations and self-supervised foundation models; discuss protein structures, target identification and generative molecule design; and explain why experimental validation and generalisation beyond training data remain difficult. The conversation also considers interpretable cellular representations and the potential role of AI in clinical-trial recruitment and prediction. The publisher provides an accompanying transcript.

Hosted by Vijay Pande