Evidence map›Paper›PMID 40114249›Full record

ArticleBMC chemistry2025

Development of UV-Chemometric techniques for resolving the overlapped spectra of aspirin, caffeine and orphenadrine citrate in their combined pharmaceutical dosage form.

Sobhy M El-Adl, Amr A Mattar, Omar M El-Abassy, Mahmoud M Sebaiy

Abstract read
In one paragraph

Article in BMC chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sobhy M El-AdlMedicinal Chemistry Department, Faculty of Pharmacy, Zagazig University, Zagazig, 44519, Egypt.
Amr A MattarMedicinal Chemistry Department, Faculty of Pharmacy, Zagazig University, Zagazig, 44519, Egypt.
Omar M El-AbassyPharmaceutical Chemistry Department, Faculty of Pharmacy, Egyptian Russian University, Badr City, Cairo, 11829, Egypt. omar-magdy@eru.edu.eg.
Mahmoud M SebaiyMedicinal Chemistry Department, Faculty of Pharmacy, Zagazig University, Zagazig, 44519, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A UV-chemometric approach has been developed to analyze a ternary combination of aspirin, caffeine, and orphenadrine citrate without the need for previous separation. The method is easy, specific, accurate, and highly precise. The three medications were evaluated simultaneously utilizing CLS, PLS, and PCR, which were generated based on separate data sets that yielded superior findings. Regrettably, their accurate estimation could only be achieved using the PLS approach. In order to determine the prediction power of each chemometric approach, its validity has been tested using 8 synthetic mixes. The latent variable number varies across various models as the dataset changes. The comparison of various methodologies and the assessment of the predictive capacity of each set of data were done using the predicted residual error sum of squares (PRESS) and the root mean square error of prediction (RMSEP). The created approach was also used to statistically compare the performance of PLS in a dataset with zero absorption, as well as to compare the performance of the offered chemometric methods in various datasets. The environmental impact of the created approach was assessed to determine the overall ecological sustainability of the designed methodology. According to the new Blue Applicability Grade Index (BAGI) evaluation methodology, the suggested technique was also found to be practicable.

Indexed as

AGREEAspirinBAGICaffeineGAPIOrphenadrine citratePLS

Identifiers

PMID40114249
PMCPMC11927279

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.