Evidence map›Paper›PMID 39789629›Full record

ArticleBMC chemistry2025

Eco-sustainable chromatographic method for the determination of favipiravir and nitazoxanide for COVID-19: application to human plasma.

Amal B Ahmed, Maha M Abdelrahman, Fadwa H Edrees

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Amal B AhmedPharmaceutical Chemistry Department, Faculty of Pharmacy, Nahda University (NUB), Sharq El-Nile, Beni-Suef, 62511, Egypt. amal.badawy@nub.edu.eg.
Maha M AbdelrahmanPharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Alshaheed Shehata Ahmad Hegazy St, Beni-Suef, 62514, Egypt.
Fadwa H EdreesPharmaceutical Chemistry Department, Faculty of Pharmacy, Nile Valley University (NVU), El Fayoum, 63518, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19), an extremely contagious illness, has posed enormous challenges to healthcare systems around the world. Although the evidence on COVID-19 management is growing, antiviral medication is still the first line of treatment. Therefore, it is critical that effective, safe, and tolerable antivirals be available to treat early COVID-19 and stop its progression. Recently, favipiravir (FAV) has received FDA approval as safe and effective antiviral medication for COVID-19 management. Nitazoxanide (NTZ) also possesses antiviral and immunomodulating activities. Moreover, FAV and NTZ in combination are clinically used in COVID-19 treatment with reported safety, synergistic antiviral and immunomodulating effects. Despite the availability of various clinical studies on both FAV and NTZ, no existing analytical application for the simultaneous estimation of FAV and NTZ exists. As a result, the current work goal is to establish a green HPLC method for their analysis and implementation to human plasma. The developed method utilizes isocratic elution with 0.1% aqueous formic acid: ethanol (55:45, v/v) and dantrolene as internal standard. The bioanalytical validation parameters passed the FDA acceptance criteria. NEMI, eco scale, AGREE and ComplexGAPI approaches were used for qualitative and quantitative evaluation of the method's greenness.

Indexed as

COVID-19FavipiravirGreen HPLC methodNitazoxanidePlasmaTherapeutic drug monitoring

Identifiers

PMID39789629
PMCPMC11714856

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.