Systematic forensic toxicological analysis by GC-MS in serum using automated mass spectral deconvolution and identification system

Non-targeted screening of body fluids for psychoactive agents is an essential task for forensic toxicology. The challenge is the identification of xenobiotics of interest from background noise and endogenous matrix components. The aim of the present work was to evaluate the use of an Automated Mass Spectral Deconvolution and Identification System (AMDIS) for gas chromatography-mass spectrometry (GC-MS) based toxicological serum screening. One hundred fifty serum samples submitted to the authors´ laboratory for systematic forensic toxicological analysis underwent GC-MS screening after neutral and basic liquid-liquid extraction. Recorded datasets were routinely evaluated both by experienced personnel and automatically using the AMDIS software combined with the Maurer/Pfleger/Weber GC-MS library MPW_2011. The results from manual and automated data evaluation were then systematically compared. AMDIS parameters for data deconvolution and substance identification had been successfully adapted to the GC-MS screening procedure in serum. The number of false positive hits could substantially be reduced without increasing the risk of overlooking relevant compounds. With AMDIS-based data evaluation, additional drugs were identified in 25 samples (17%) that had not been detected by manual data evaluation. Importantly, among these drugs, there were frequently prescribed and toxicologically relevant antidepressants and antipsychotic drugs such as citalopram, mirtazapine, quetiapine, or venlafaxine. For most of the identified drugs, their serum concentrations were in the therapeutic or subtherapeutic range. Thus, our study indicated that automated data evaluation by AMDIS provided reliable screening results. Copyright © 2015 John Wiley & Sons, Ltd.