Hepatotoxicity is a leading cause of drug withdrawal from the market; thus, the assessment of potential drug induced liver injury (DILI) in preclinical trials is necessary. More and more research has shown that the covalent modification of drug reactive metabolites (RMs) for cellular proteins is a possible reason for DILI. Unfortunately, so far no appropriate method can be employed to evaluate this kind of DILI due to the low abundance of RM-protein adducts in complex biological samples. In this study, we proposed a mechanism-based strategy to solve this problem using human liver microsomes (HLMs) and online 2D nano-LC-MS analysis. First, RM modification patterns and potential modified AA residues are determined using HLM and model amino acids (AAs) by UHPLC-Q-TOF-MS. Then, a new online 2D-nano-LC-Q-TOF-MS method is established and applied to separate the digested modified microsomal peptides from high abundance peptides followed by identification of RM-modified proteins using Mascot, in which RM modification patterns on specific AA residues are added. Finally, the functions and relationship with hepatotoxicity of the RM-modified proteins are investigated using ingenuity pathway analysis (IPA) to predict the possible DILI. Using this strategy, 21 proteins were found to be modified by RMs of toosendanin, a hepatotoxic drug with complex structure, and some of them have been reported to be associated with hepatotoxicity. This strategy emphasizes the identification of drug RM-modified proteins in complex biological samples, and no pretreatment is required for the drugs. Consequently, it may serve as a valuable method to predict potential DILI, especially for complex compounds.

Hair analysis is useful for documenting long‐term exposure to drugs. The potential of hair analysis for therapeutic drug monitoring within the forensic field has been studied, but reference values for some antidepressants and antipsychotics in the hair of individuals undergoing chronic therapy are still lacking. In the present study, a method was developed and validated for the determination of 23 analytes, including antidepressants, antipsychotics, and related metabolites, in human hair by liquid chromatography–tandem mass spectrometry (LC–MS/MS). Hair samples (10 mg) were extracted with a 25:25:50 (v/v/v) mixture of methanol/acetonitrile/2 mM ammonium formate (8% acetonitrile, pH 5.3) utilizing cryogenic grinding. The present method demonstrated sufficient selectivity, robustness, and accuracy. Sixteen analytes in hair were reported in 46 psychiatric patients receiving fixed drug dosages. To the best of our knowledge, the hair concentrations of perphenazine and norolanzapine, as well as the concentrations of amisulpride, aripiprazole and its metabolite dehydroaripiprazole, olanzapine, and sulpiride, in hair from individuals receiving fixed dosages is reported for the first time. A significant relationship between the administered dose and the concentration in the proximal hair segment was found only for clozapine, norclozapine, and chlorpromazine. The results confirmed that the idea of using hair concentrations to monitor a daily dose is inapplicable.

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A method using liquid chromatography–tandem mass spectrometry (LC–MS/MS) to simultaneously quantify amphetamines, opiates, ketamine, cocaine, and metabolites in human hair is described. Hair samples (50 mg) were extracted with methanol utilizing cryogenic grinding. Calibration curves for all the analytes were established in the concentration range 0.05–10 ng/mg. The recoveries were above 72%, except for AMP at the limit of quantification (LOQ), which was 48%. The accuracies were within ±20% at the LOQ (0.05 ng/mg) and between −11% and 13.3% at 0.3 and 9.5 ng/mg, respectively. The intraday and interday precisions were within 19.6% and 19.8%, respectively. A proficiency test was applied to the validated method with z‐scores within ±2, demonstrating the accuracy of the method for the determination of drugs of abuse in the hair of individuals suspected of abusing drugs. The hair concentration ranges, means, and medians are summarized for abused drugs in 158 authentic cases.