Introduction General unknown screening (GUS) is the procedure used by toxicologists in order to unambiguously identify the xenobiotics involved in an intoxication case. Due to its high specificity, GC-MS was long considered the gold standard for GUS in clinical and forensic toxicology. Still, GC-MS is poorly suited for the detection of several xenobiotics and their more hydrophilic metabolites. Here we describe the optimization and implementation of a comprehensive high-resolution drug screen in biological matrices using a Waters UPLC XEVO G2 QToF MS system. We also examined the transferability of the high-resolution spectral lists established on mirror systems by comparing our data against two other instruments of the same model and manufacturer using the same chromatographic separation (Humbert et al., 2012; Rosano et al., 2013). Methods Drugs and metabolites were extracted from spiked matrices using SPE cartridges or liquid-liquid extraction. Extracts were sequentially injected into a UPLC coupled to a hybrid quadrupole- time of flight system (MSe) in positive and negative ESI mode. Data was collected using MSe acquisition which performs two sets of acquisition simultaneously and compared to a list containing the exact mass, the retention time and the exact mass fragments as previously described (Humbert et al., 2012; Rosano et al., 2013). In order to optimize the extraction procedure, we modeled different approaches (reverse phase SPE, mixed-mode cation exchange SPE and liquid-liquid extraction) using 18 different xenobiotics frequently encountered in toxicological investigations. Results The most efficient extraction process was chosen using the following criteria: ion suppression, recovery and the limit of detection. Based on our data, mixed-mode cation exchange SPE demonstrated the best overall performance and was selected to be compared to our reference GC-MS screening method. We then evaluated the recoveries, ion suppression and the limits of detections for 225 xenobiotics which are part of our GC-MS screen. Overall our transferability study showed few discrepancies in mass or fragments generated. Retention time reproducibility was 99% using a retention time tolerance of 0.4min and 96% using a 0.3 window. Finally, we performed a comparison between the test LC-QToF method and our reference GC-MS method on real samples to evaluate its performance; several cases will be presented. In summary, these cases demonstrated that the LC-QTOF method was able to identify more xenobiotics in the following categories: benzodiazepine and stimulant metabolites (7-amino-clonazepam, 4-methylamphetamine and desmethyl-diphenhydramine), anti hypertensive drugs metabolite (OH-propranolol), antiretroviral drugs (such as ritonavir and darunavir) and hydrophilic anticonvulsant pregabalin. Conclusion Overall, the LC-QToF method demonstrates increased sensitivity compared to GC-MS and should be more specific. Our evaluation of the transferability of lists between labs indicates that retention variability could be an issue for a small fraction of compounds. Also, in order to detect some families of xenobiotics, such as barbiturates and NSAIDS, the addition of a second injection (using negative ionization) was necessary.