The characterization of pharmaceutical drugs and their transformation products have become an important analytical research field because its presence in the environment could induce bacterial resistance. Despite all efforts made by the scientific community, detection and structure identification of unknown chemicals still remains the most challenging task in non-targeted analytics. Given that, the objective of the present study was to develop an untargeted workflow to detect, quantify, identify and characterize ofloxacin and its transformation products (OFX TPs) after photocatalytic treatments based on TiO2 nanoparticles and TiO2 nanofibers. For the characterization and chemical structure assignment of OFX TPs, mass defect filters, mass accurate measurements (HRMS), tandem mass spectrometry in a q-Orbitrap (MS/HRMS) and the photocatalysis of the isotopically labelled ofloxacin (OFX-d3) were used. Since a large set of data was obtained in each run, data treatment based on statistical analysis and mass defect filtering was used to reduce the number of potential TP candidates from 2497 m/z peaks to 70. Moreover, ions generated by in-source CID and by redox reactions in the electrospray source (ESI) were also detected and discarded from the TP candidate list. Moreover, the whole kinetics evolution of the generated TPs provided a deeper insight into the degradation mechanism and was used to propose a degradation pathway for the OFX in the aqueous phase. The time evolution of the TPs generated during the photocatalytic process using both types of catalysts (NPs and NFs) and different set-ups (suspended and supported conditions) indicated that OFX was completely removed from the aqueous solution in less than 4h. Among the condition tested TiO2 nanoparticles in suspended conditions showed the fastest kinetics (k: 0.161 min(-1)).
Keywords: Data mining techniques; Fluoroquinolones; LC-HRMS(MS/HRMS); Photocatalysis.
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