This autumn, I had a pleasure of giving an invited talk at the British Mass Spectrometry Society (BMSS) annual meeting in Leeds and a plenary lecture in the opening ceremony of RAFA (Recent Advances in Food Analysis).
RAFA is a very special conference that takes place every two years in Prague, Czech Republic. It is jointly organized by the University of Chemistry and Technology Prague (UCT Prague) and Wageningen Food Safety Research, part of Wageningen University & Research. I very much enjoyed the conference, which brings together mass spectrometry, toxicology, and data analysis in the context of food safety and quality. Since my own PhD research revolved around matrix effects in pesticide analysis, food is a matrix particularly close to my heart!
This year, the conference also featured a dedicated AI session and a poster sessi
on with several contributions exploring the use of modeling and machine learning in mass spectrometry. I was particularly happy to see some exciting developments coming out of Wageningen, including work on the deconvolution of data-dependent acquisition (DDA) data by Nick de Jonge and the prediction of endocrine-disrupting activity by Leonieke van den Bulk.
I was also delighted to see the growing interest in quantifying food contaminants using predicted ionization efficiencies and response factors. It is exciting to see these approaches gaining traction in food analysis, where the complexity of the matrices and the diversity of potential contaminants make reliable quantification particularly challenging.