In this week's episode, we’re exploring the role of AI in toxicology. From large language models supporting drug identification to machine learning tools navigating the vast datasets produced by high-resolution mass spectrometry, we look at how artificial intelligence could be integrated into toxicological workflows.

We also discuss the limitations — including bias in training data, challenges with messy or incomplete datasets, and the importance of expert oversight in clinical and forensic applications.

Join us as we unpack the promise and pitfalls of AI in the evolving world of toxicology.

Hope you enjoy!

Linked to the letter we discussed: https://academic.oup.com/jat/advance-article-abstract/doi/10.1093/jat/bkaf036/8123742?redirectedFrom=fulltext&login=false

Disclaimer: All opinions are our own.

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