Translated from our German original by AI. The German text was researched, written, and edited by the Psychedelia Foundation team and remains the authoritative version.
Artificial intelligence (AI), and machine learning methods in particular, supports analytical toxicology in evaluating data and identifying new psychoactive substances (NPS). That is the conclusion of the review Artificial intelligence in new psychoactive substances analysis: state-of-art and future perspectives.
For the paper, the authors evaluated publications describing the use of AI models in analytical toxicology. The most common areas of application are the identification of substances, the prediction of molecular structures, and the prediction of retention times in chromatographic analyzes.
In the authors’ assessment, AI is a valuable tool for analytical toxicology above all because it can process the large volumes of data produced by untargeted analytical methods. The review summarizes the current state of research and outlines future prospects for the use of AI in this area.
