Transitioning from concept to application: Comprehensive analytical validation of antibody-based smart sampling
Smart sampling, introduced in 2018, is a technique that integrates crucial sample preparation steps for LC-MS protein analysis directly into the sampling process, improving efficiency. Currently most studies in this area are limited to proof of concept with a brief evaluation. Therefore, our objective is to fully validate the utility of smart samplers for quantitative analysis of bioactive proteins in biological matrices. This study builds on previous work where a paper-based antibody sampler was developed, and human chorionic gonadotropin (hCG) was used as a model protein. hCG is both a biomarker, a drug, and on the doping list for male athletes. Initially, the fabrication of the sampler was optimized, resulting in a reduction of antibody amount per sampler from 50 µg to 5 µg, reducing manufacturing cost while maintaining acceptable performance. It was also shown that removing the sampler before trypsination, but after reduction and alkylation greatly improved signal output while reducing the peptide background, suggesting a cleanser extract was achieved. The optimized smart sampler was validated for hCG in human serum using EMA's ICH M10 guidelines on bioanalytical methods as a guide. Three calibration curves (seven levels) were made in the concentration range of 0.5 ng/mL to 75 ng/mL all displaying excellent linearity (r<sup>2</sup> ≥ 0.9955). The accuracy and precision both for the between-run (precision ≤ 10 % CV and accuracy 91-105 % (n = 3)) and within-run (precision ≤ 14 % CV and accuracy 94-105 % (n = 5)) runs were all well within the guideline's acceptance limits. The samplers also showed to be stable for at least ten weeks at room temperature. The optimization and validation of the antibody sampler detailed in this paper marks a notable progression, advancing the concept of "smart sampling" a step closer from the lab to practical application.
Authors
- Trine Grønhaug Halvorsen (ORCID: https://orcid.org/0000-0002-2545-3474)
- Ago Mrsa (ORCID: https://orcid.org/0009-0001-2172-2024)
- Léon Reubsaet (ORCID: https://orcid.org/0000-0001-5165-2701)
- Rihana B. Ishaq
- Laila Brandoli
Institutions
- University of Oslo (NO)
Publication Details
- Journal
- Journal of Pharmaceutical and Biomedical Analysis
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1016/j.jpba.2025.116825
- Citations
- 2
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.35