Benzodiazepine abuse remains a significant public health concern. Current sample preparation methods for benzodiazepine analysis from human serum often involve complex procedures that require large sample volumes and extensive organic solvent use. To address these limitations, this study presents a novel and efficient sample preparation method utilizing 3D-printed sorbent devices. The 3D-printed devices, fabricated from a thermoplastic composite incorporating C18-modified silica, demonstrated exceptional performance in extracting benzodiazepines from human serum. The method was optimized and validated according to ICH guidelines, ensuring its reliability for quantitative benzodiazepine analysis. Notably, the method required minimal sample and solvent volumes, eliminating the need for protein precipitation, evaporation, and reconstitution. This novel sample preparation approach offers significant advantages over traditional methods, providing a more efficient and environmentally friendly solution for benzodiazepine analysis. The versatility of 3D printing allows for the customization of sorbent devices for various analytes and matrices, expanding the potential applications of this method. Coupled with a rapid and robust LC-MS method optimized with DryLab, this approach presents a valuable and sensitive tool for benzodiazepine monitoring in clinical and toxicological settings.

Polychlorinated biphenyls (PCBs) are persistent organic pollutants that pose significant health risks, especially for neonates. Traditional urine analysis methods for PCBs are often complex and prone to contamination. This study introduces a novel, efficient, and contamination-free method for PCB analysis in neonatal urine using 3D-printed extraction devices. A headspace extraction method was developed, utilizing a 3D-printed device containing C18-modified silica particles. Urine samples were heated to 90 °C, and volatile PCBs were sorbed onto the particles. The method was optimized for maximum extraction efficiency and selectivity, demonstrating excellent linearity, precision, and accuracy. The optimized method was successfully applied to analyze neonatal urine samples, revealing detectable levels of PCBs. This innovative approach, leveraging 3D-printed devices, offers a promising solution for sample preparation, minimizing contamination risks and enabling the analysis of volatile compounds. The customizable nature of 3D-printed devices opens up possibilities for future advancements in environmental analysis.

The measurement of selected norepinephrine metabolites, such as 3,4-dihydroxyphenylglycol (DHPG), 3-methoxy-4-hydroxyphenylethylenglycol (MHPG), and vanillylmandelic acid (VMA), in biological matrices—including urine—is of great clinical importance for the diagnosis and monitoring of diseases. This fact has forced researchers to evaluate new analytical methodologies for their isolation and preconcentration from biological samples. In this study, the three most popular extraction techniques—liquid-liquid extraction (LLE), solid-phase extraction (SPE), and a new 3D-printed system for dispersive solid-phase extraction (3D-DSPE)—were investigated. Micellar electrokinetic chromatography (MEKC) with a diode array detector (DAD) at 200 nm wavelength was applied to the separation of analytes, allowing for the assessment of the extraction efficiency (R) and enrichment factor (EF) for the tested extraction types. The separation buffer (BGE) consisted of 5 mM sodium tetraborate decahydrate, 50 mM SDS, 15% (v/v) MeOH, 150 mM boric acid, and 1 mM of 1-hexyl-3-methylimidazolium chloride (the apparent pH of the BGE equaled 7.3). The EF for each extraction procedure was calculated with respect to standard mixtures of the analytes at the same concentration levels. The 3D-DSPE procedure, using DVB sorbent and acetone as the desorption solvent, proved to be the most effective approach for the simultaneous extraction and determination of the chosen compounds, achieving over 3-fold signal amplification for DHPG and MHPG and over 2-fold for VMA. Moreover, all extraction protocols used for the selected norepinephrine metabolites were estimated and discussed. It was also confirmed that the 3D-DSPE-MEKC approach could be considered an effective tool for sample pretreatment and separation of chosen endogenous analytes in urine samples.