A Comprehensive HPLC-MS-MS Screening Method for 77 New Psychoactive Substances, 24 Classic Drugs and 18 Related Metabolites in Blood, Urine and Oral Fluid

To date, more than 800 molecules are classified as New Psychoactive Substances (NPS), and it is reported that this number increases every year. Whereas several cases of polydrug consumption that led to acute intoxication and death are reported, a lack of effective analytical screening method to detect NPS and classical drug of abuse in human matrices affects the prompt identification of the probable cause of intoxication in emergency department of hospitals. In this concern, a fast, simple and comprehensive high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS-MS) screening method to detect and quantify 77 NPS, 24 classic drugs and 18 related metabolites has been successfully developed and validated in blood, urine and oral fluid. A small volume (100 mu L) of whole blood samples spiked with internal standard deuterated mixture was added to 70 mu L of M3 (R) buffer, and after precipitation of blood proteins, the supernatant was evaporated to dryness and reconstituted in 1 mL of mobile phase. Same volume (100 mu L) of urine and oral fluid samples spiked with internal standard deuterated mix were only diluted with 500 mu L of M3 (R) reagent. One microliter of samples of each matrix was injected into HPLC-MS-MS equipment. The run time lasted 10 min with a gradient mobile phase. Mass spectrometric analysis was performed in positive ion multiple reaction monitoring mode. The method was linear for all analytes under investigation with a determination coefficient always better than 0.99. The calibration range for blood and oral fluid was from limits of quantification (LOQs) to 200 ng/mL, whereas that for urine was LOQs to 1000 ng/mL. Recovery and matrix effect were always higher than 80%, whereas intra-assay and inter-assay precision were always better than 19% and accuracy was always within 19% of target in every matrix. Applicability of the method was verified by analysis of samples from real cases.