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The development of a LC-MS/MS general unknown screening procedure for toxicologically relevant substances in blood samples by means of information-dependent acquisition on a Q-TOF is reported. IDA is an artificial intelligence-based product ion scan mode providing automatic "on-the-fly" MS to MS/MS switching. By performing information-dependent scanning at two different fragmentation energies, two collision-induced dissociation product ion spectra for each of the detected compounds are generated. As such, information-rich MS/MS spectra are obtained from precursor ions not known beforehand. In addition, limitation of the MS/MS acquisition time to an acceptable minimum resulted in an almost instantaneous switch back to the MS mode. As such, this approach provided MS chromatograms that still could be of use for semiquantitative purposes. Since the switching intensity threshold, unequivocally related to the background noise, proved a critical parameter, the solid-phase extraction procedure, the liquid chromatographic conditions, and the mass spectrometric parameters all were optimized to the advantage of information-dependent acquisition. Finally, the screening procedure we developed was benchmarked, on one hand, qualitatively against the results obtained from traditional GUS approaches in a number of routine toxicological laboratories (20 samples) and, on the other hand, quantitatively with respect to its potential against established LC-MS/MS methods (7 samples). The procedure performed very well from a qualitative point of view; almost all of the drugs detected by the conventional techniques were identified, as well as additional drugs that were not previously reported. The procedure proved well-suited for an initial semiquantitative assessment, as is customary in, for example, forensic toxicology before accurate intoxication levels are determined using targeted analytical analyses.
Decaestecker et al. (Sat,) studied this question.