Bioanalytical Uncertainty Assessment of Ultra‐High‐Performance Liquid Chromatography‐High Resolution Mass Spectrometry Method for Caffeine and Lidocaine in Equine Antidoping: A Dual Perspective on Bottom‐up and Top‐Down Approaches
The quality of quantitative results in bioanalysis requires not only a validated analytical method but also a rigorous estimation of measurement uncertainty. This study examines the challenges associated with the implementation of two distinct approaches in equine anti-doping control for the assessment of uncertainty associated with an ultra-high-performance liquid chromatography-high resolution mass spectrometry quantitative method for caffeine and lidocaine in horse urine. The bottom-up approach, based on the ISO Guide to the Expression of Uncertainty in Measurement (ISO GUM), was compared to the top-down approach using β-content, γ-confidence tolerance intervals (β,γ-CCTI) via F-test. The key limitation of the ISO GUM method was accurately quantifying the various uncertainty components; it gives standardized uncertainty estimates but requires detailed assumptions and modeling about error sources. The direct application of the GUM method imposes the beforehand correction of the matrix effect to provide reliable results. Parallelly, the chemometric approach β,γ-CCTI offers more flexible and realistic estimations. Four combinations of β and γ were investigated to assess their influence on uncertainty interval width: β = 66.7% and 80%; γ = 90% and 95%; and the method was evaluated under repeatability and intermediate precision conditions through the use of advanced computation that adjusts for matrix effects and proves more straightforward for capturing variability inherent in experimental data. The top-down approach is a reliable alternative for routine use and, particularly, for ensuring compliance with regulatory requirements, with the fact that a known proportion β of future results will be within predefined acceptance limits.
Authors
- Taoufiq Saffaj (ORCID: https://orcid.org/0000-0002-6270-8755)
- Fayssal Jhilal (ORCID: https://orcid.org/0000-0001-8284-1708)
- Maha El-Hamdani (ORCID: https://orcid.org/0000-0001-7981-3212)
- Fadil Bakkali (ORCID: https://orcid.org/0000-0002-2591-9844)
- Taha El Kamli (ORCID: https://orcid.org/0000-0001-5027-1173)
- Lamia Zaari Lambarki (ORCID: https://orcid.org/0009-0001-5845-2988)
- Adnane Benmoussa (ORCID: https://orcid.org/0000-0002-1037-7819)
- Wafaa El‐Ghaly (ORCID: https://orcid.org/0009-0007-8351-8954)
- Fatima‐ezzahra Lahkak
- Lhousaine Balouch
Institutions
- Bishop's University (CA)
- Université Ibn-Tofail (MA)
- Université Mohammed VI des Sciences et de la Santé (MA)
- Institut Agronomique et Vétérinaire Hassan II (MA)
- Sidi Mohamed Ben Abdellah University (MA)
Publication Details
- Journal
- Journal of Separation Science
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/jssc.70308
- Primary Topic
- Pesticide Residue Analysis and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00