Sustainable and renewable approaches in biomaterial-based integrated dried urine sampling/solid-phase extraction devices for drugs and metabolites: challenges, bioanalytical applications, and future directions

Abstract

Urine samples are gaining increasing importance as preferred biological matrices in bioanalytical studies due to their non-invasive collection, abundance, and ability to reflect systemic metabolism. However, conventional urine sampling and storage methods face significant challenges, especially in resource-limited areas where transportation and preservation infrastructure are inadequate. Traditional methods of liquid urine collection require refrigeration to prevent analyte degradation, making long-term storage and global sample transport costly and impractical. Biomaterial-based integrated dried urine sampling (DUS) devices integrate both storage and extraction into a single-step process, significantly enhancing efficiency and reliability. The porous sorbent is designed with a high surface area and tailored molecular binding capacity, ensuring the selective adsorption of target metabolites while minimizing matrix effects. Its structure allows for rapid drying and ambient-temperature storage, eliminating the need for cold-chain logistics. This feature is particularly beneficial for field studies and resource-constrained settings where maintaining refrigeration is impractical. Biomaterial-based DUS devices could be cost-effective and customizable and enable long-term stabilization of urinary metabolites. By reducing drying times, enhancing analyte recovery, and improving storage conditions, this technology enhances the feasibility of large-scale bioanalytical studies, therapeutic drug monitoring, and clinical diagnostics. Furthermore, its ability to selectively extract metabolites streamlines laboratory workflows and improves overall analytical precision. Porous biomaterial-based DUS devices could present a transformative, sustainable, and renewable solution for bioanalysis. By addressing the critical issues of sample stability, extraction efficiency, and cost-effectiveness, this approach has the potential to revolutionize metabolomics research, personalized medicine, and biomarker discovery in both clinical and research settings.