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MetIDfyR, an Open-Source R Package to Decipher Small-Molecule Drugs Metabolism Through High Resolution Mass Spectrometry

submitted on 26.05.2020 and posted on 27.05.2020 by Vivian Delcourt, Agnès Barnabé, Benoit Loup, Patrice Garcia, François André, Benjamin Chabot, Stéphane Trévisiol, Yves Moulard, Marie-Agnès Popot, Ludovic Bailly-Chouriberry
After administration to humans or animals, small-molecule drugs most frequently undergo several biochemical transformations by the endogenous enzymatic machinery, called phase I and phase II metabolism. These molecular processes allow organisms to eliminate xenobiotics through modification of their chemical properties and generate metabolites. With recent advances in analytical chemistry, LC-HRMS/MS has become an essential tool for metabolite discovery and detection. Even if most common drug transformations have already been extensively described, manual search of drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology laboratories, disabling efficient metabolite discovery. Furthermore, the availability of free open-source software for metabolite discovery is still limited.

In this article, we present MetIDfyR, an open-source and cross-platform R package for in-silico drug phase I/II biotransformations prediction and mass-spectrometric data mining. MetIDfyR has proven efficacy for advanced metabolite identification in semi-complex and complex mixtures in in-vitro or in-vivo drug studies and is freely available at


Email Address of Submitting Author


GIE-LCH, Laboratoire des Courses Hippiques, Verrières-le-Buisson, France



ORCID For Submitting Author


Declaration of Conflict of Interest


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