Commentary & Perspectives

When AI Meets Physics: A Microcosmic Revolution in Liquid Chromatography

How physics-informed machine learning can more accurately predict retention times in LC and speed up drug development

Share

  • 1

    AI and ML have vast potential in analytical chemistry.

  • 2

    Improvement of retention time predictions can streamline drug development.

  • 3

    Traditional models face challenges addressing LC complexities.

  • 4

    Integration of physics-based methods with ML may enhance prediction accuracy.

  • 5

    Waters supports research in MDS for chromatography solutions.

Original Source(s)

When AI Meets Physics: A Microcosmic Revolution in Liquid Chromatography

  • by Fabrice Gritti

  • March 18, 2026