Next-Generation Wastewater-Based Epidemiology: Green Automation for Detecting 69 Multiclass Pharmaceutical and Personal Care Products in Wastewater Using 96-Well Plate Solid-Phase Extraction by LC-MS/MS

摘要

Conventional methods for detecting pharmaceutical and personal care products (PPCPs) in environmental samples are complex, resource-intensive, and not sustainable. Therefore, this study aimed to evaluate an automated sample preparation approach using the Biomek i7 Workstation to analyze 69 PPCPs in wastewater, with the objective to improve monitoring of public health and environmental protection. The method underwent extensive development, including optimization of UPLC-MS/MS parameters, preparation of wastewater matrix blank sample and assessment of extraction efficiency using three types of SPE cartridges. Extraction efficiency trials revealed that the order of suitability for SPE cartridges is Mixed-Mode Anion Exchange (MAX) > Mixed-Mode Cation Exchange (MCX) > Hydrophilic–Lipophilic Balance (HLB). The method demonstrated specificity for all targeted PPCPs, with the max interfering peak for 1, 7 Dimethylxanthine reaching 14.79% of the response at the target limit of quantification (LOQ). The method met ±20% matrix effect tolerance for 63 PPCPs, while 6 PPCPs showed signal enhancement. The 8-point procedural calibration curve prepared using automated robotic extraction has demonstrated linearity across the tested range. A spiking study at low (LQC), medium (MQC), and high (HQC) quality control levels (n = 6), repeated on three separate occasions, showed % RSD values within 20% and % recovery between 80 and 120%. The method met validation requirements, showed reliability in Intra-Laboratory Comparison, Blind Testing (BT) and received high ratings for greenness (Green Analytical Procedure Index, Analytical GREEnness) and practicality (Blue Applicability Grade Index).