Revolutionary blood test detects cannabis where urine screening fails

In forensic toxicology (FT), drug of abuse (DoA) screening is essential yet challenging. This study presents a vendor-based, high-resolution (HR) LC-MS/MS blood screening method implemented without in‑house optimization, in comparison to immunoassay-based and low-resolution (LR) urine screening approaches simultaneous to (semi)quantification. The HR-method allows detection of more than 3000 analytes, including DoAs, drugs, and suspected new psychoactive substances (NPS). Following protein precipitation, analytes qualitatively identified in 500 authentic whole-blood samples using the HR-method were qualitatively compared with results from immunoassay and LR urine screening. Additionally, 82 common DoAs and drugs were (semi)quantitatively validated according to ANSI and GTFCh guidelines, and quantitative performance was assessed against a fully-validated targeted LC-MS/MS method (MRM mode). In total, the HR-method detected 819 (83%) of the 994 analytes identified by LR urine screening. Substances not captured by the HR approach typically showed concentrations below the identification limit and/or were of negligible relevance in FT. The HR blood screening detected 66% of all cases positive for THC and/or its metabolites, whereas the LR urine screening failed to detect these compounds entirely. Incorporation of the HighResNPS® database enabled the tentative identification of 14 NPS. Seventy-four (90%) of the 82 DoAs demonstrated accuracy within ±30%, precision (CV) ≤30%, and quantitative results of 100 authentic cases were consistent with those from the targeted LC-MS/MS method which is generally considered the gold standard for quantification. Overall, the HR blood screening can replace LR urine screening enabling simultaneous detection of DoAs, their metabolites, and NPS. The (semi)quantitative validation of 74 drugs and the quantitative comparison confirmed the method's reliability in distinguishing between subtherapeutic, therapeutic, and toxic concentrations without the need for drug class-specific optimization, thereby saving time, effort, and costs. This untargeted approach combines screening with (semi)quantification while supporting routine workflows, research applications, and retrospective analysis of new emerging substances.