In order to overcome the challenge associated with the screening of Anabolic‐Androgenic Steroids abuses in animal competitions, a non‐targeted liquid chromatography coupled to high resolution mass spectrometry based metabolomics approach was implemented on equine urine samples to highlight potential biomarkers associated with the administration of such compounds, using testosterone esters as model steroids. A statistical model relying on four potential biomarkers intensity could be defined to predict the status of the samples. With a routine application perspective, the monitoring of the highlighted potential biomarkers was first transferred into high‐throughput liquid chromatography‐selected reaction monitoring (LC‐SRM). The model's performances and robustness of the approach were preserved and providing a first demonstration of metabolomics‐based biomarkers integration within a targeted workflow using common benchtop MS instrumentation. In addition, with a view to the widespread implementation of such biomarker‐based tools, we have transferred the method to a second laboratory with similar instrumentation. This proof of concept allows the development and application of biomarker‐based strategies to meet current doping control needs.

Despite their ban, Anabolic Androgenic Steroids (AAS) are considered as the most important threat for equine doping purposes. In the context of controlling such practices in horse racing, metabolomics has emerged as a promising alternative strategy to study the effect of a substance on metabolism and to discover new relevant biomarkers of effect. Based on the monitoring of 4 metabolomics derived candidate biomarkers in urine, a prediction model to screen for testosterone esters abuse was previously developed. The present work now focuses on assessing the robustness of the associated method and de ne its scope of application. Several hundred urine samples were selected from 16 different horses of ethically approved animal experiments involving various doping agents' applications (AAS, SARMS, β-agonists, SAID, NSAID) (n = 349). In addition, 342 urine samples from untreated animals of general equine populations were included in the study. Samples were characterized with the previously described LC-HRMS/MS developed method, with the objective of assessing both its biological and analytical robustness's. The study concluded that the measurement of the 4 biomarkers involved in the model was t for purpose. Further, the classi cation model con rmed its effectiveness in screening for testosterone esters use; and it demonstrated its ability to screen for the administration of other anabolic agents, allowing the development of a global screening tool dedicated to this class of substances. Finally, the results were compared to a direct screening method targeting anabolic agent's residues, demonstrating complementarity performances of traditional and omics approaches in the screening of anabolic agents in horses.