Artificial intelligence for method development in liquid chromatography

doi:10.1016/j.trac.2025.118320

Artificial intelligence for method development in liquid chromatography

2025-06-01

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DOI：10.1016/j.trac.2025.118320

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Abstract

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• Method development in chromatography is complex, time-consuming, and expensive. • Artificial intelligence facilitates and speeds up the method development process. • Richer molecular representations significantly improve QSRR performance. • Self-optimization methods allow for completely autonomous method development. • Deep learning based signal processing is a crucial building block of automation.

Artificial intelligence for method development in liquid chromatography

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