Key Points
- Researchers from Majmaah University and Ain Shams University developed an ecofriendly method combining UV spectroscopy with dimension reduction algorithms (DRAs) to accurately quantify veterinary drugs dexamethasone sodium phosphate (DXM) and prednisolone acetate (PRD).
- The method demonstrated high analytical accuracy and reproducibility, with mini-batch sparse principal component analysis (sPCA) performing best, and results showing no significant differences compared to HPLC.
- Greenness assessment tools confirmed the method’s minimal environmental impact, and future work may explore more advanced DRAs to improve predictive accuracy for complex datasets.
A recent study conducted by a research team led by Ahmed M. Ibrahim of Majmaah University in Saudi Arabia and Ain Shams University in Egypt presented an analytical method that can accurately quantify veterinary drugs. This study, which was published in the journal Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, presented a method that combined ultraviolet (UV) spectroscopy with dimension reduction algorithms (DRAs) (1). The researchers demonstrated that their method could serve as an environmentally friendly approach that is accurate and cost-effective.
What veterinary drugs were tested in this study?
The researchers tested their method to accurately characterize two popular veterinary drugs: dexamethasone sodium phosphate (DXM) and prednisolone acetate (PRD). DXM is often used to treat conditions such as arthritis, skin diseases, and eye problems (2). PRD, meanwhile, is a corticosteroid used in veterinary medicine to treat inflammation and pain that comes from infections or surgery (3).
Both DXM and PRD are difficult to quantify accurately in pharmaceutical formulations. This is especially true in resource-limited settings where advanced chromatographic techniques, such as high-performance liquid chromatography (HPLC) may not be readily accessible (1). Addressing this gap, the research team developed a spectrophotometric method that could serve as a sustainable alternative.
How did the researchers construct their method?
The research team took 17 evaluated DRAs and combined them with UV spectroscopy. The algorithms helped reduce data complexity while preserving key analytical information, which improved the precision of UV-based quantification (1). Out of the 17 DRAs, mini-batch sparse principal component analysis (sPCA) was the most effective in predicting the DXM and PRD concentrations (1).
After constructing their method, the researchers ran it through four performance metrics designed to test its effectiveness. The four metrics were mean squared error (MSE), mean absolute error (MAE), median absolute error (MedAE), and coefficient of determination (R²) (1). The results indicated high analytical accuracy and reproducibility. Additionally, a statistical comparison with a previously validated HPLC method revealed no significant differences at the 95% confidence level, confirming the reliability of the new approach (1).
What made this study unique?
A key objective of this study was to develop a method that could be economically feasible and environmentally sustainable. Because this was a top priority for the research team, they applied five greenness assessment tools to measure the ecological footprint of their method. The five tools used were the green solvent selection tool (GSST), the National Environmental Methods Index (NEMI), the green certificate modified Eco-Scale, a carbon footprint analysis, and the modified green analytical procedure index (MoGAPI).
In all, their method achieved a GSST score of 84, a MoGAPI score of 81, and a whiteness assessment of 90.1 using the RGB12 algorithm (1). The carbon footprint was also low, at just 0.0006 kg CO₂ equivalent per sample (1).
What are the next steps in this research?
The UV-DRA method presented by the researchers, and the results they achieved, opens the door for expanding evaluations of other DRAs. The authors suggest some possible DRAs that can be examined, including uniform manifold approximation and projection (UMAP) and t-distributed stochastic neighbor embedding (t-SNE) (1). The authors believe that these additional DRAs could help improve the predictive accuracy of their method when applied to larger and more complex data sets (1). Furthermore, they acknowledge that while the proposed method is cost-effective and ecofriendly, its reliance on computational tools may present barriers in laboratories lacking sufficient digital infrastructure (1).
This new analytical pathway reflects a growing shift toward integrating machine learning tools with traditional spectroscopic techniques, with an eye on making analytical methods more sustainable. By offering a practical, affordable, and environmentally sound solution for drug quantification in veterinary medicine, the researchers provide a meaningful advancement in pharmaceutical analysis, with implications far beyond the field of veterinary medicine (1).
References
- Ibrahim, M. A.; Algohary, A. M.; Al-Ghamdi, Y. O.; Ibrahim, A. M. A Green Analytical Method for Simultaneous Determination of Dexamethasone Sodium Phosphate and Prednisolone Acetate in Veterinary Formulations Using UV Spectroscopy and Dimension Reduction Algorithms. Spectrochimica Acta Part A: Mol. Biomol. Spectrosc. 2025, 328, 125446. DOI: 10.1016/j.saa.2024.125446
- Kaiser Permanente, Dexamethasone Sodium Phosphate 4 mg/mL Injection Solution. Kaiser Permanente. Available at: https://healthy.kaiserpermanente.org/health-wellness/drug-encyclopedia/drug.dexamethasone-sodium-phosphate-4-mg-ml-injection-solution.273633#:~:text=Dexamethasone%20is%20used%20to%20treat%20conditions%20such,bowel%20disorders%2C%20cancer%2C%20and%20immune%20system%20disorders. (accessed 2025-06-27).
- Ware, E. Prednisolone for Dogs, Cats, and Horses. Wedgewood. Available at: https://www.wedgewood.com/medications/prednisolone/ (accessed 2025-06-27).
