Evidence map›Paper›PMID 37566594›Full record

ArticlePloS one2023

Usefulness of medicine screening tools in the frame of pharmaceutical post-marketing surveillance.

Christelle Ange Waffo Tchounga, Pierre-Yves Sacré, Raffaella Ravinetto, Marya Lieberman, Patient Hamuli Ciza, Rose Ngono Mballa, Eric Ziemons, Philippe Hubert, Roland Djang'eing'a Marini

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
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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

9 authors at 5 institutions in 5 countries.

Christelle Ange Waffo TchoungaDepartment of Pharmacy, Laboratory of Pharmaceutical Analytical Chemistry, University of Liege (ULiege), CIRM, Liège, Belgium.ORCID 0000-0002-1540-4230
Pierre-Yves SacréDepartment of Pharmacy, University of Liege (ULiege), CIRM, Research Support Unit in Chemometrics, Liège, Belgium.ORCID 0000-0001-7113-758X
Raffaella RavinettoDepartment of Public Health, Institute of Tropical Medicine Antwerp, Antwerp, Belgium.
Marya LiebermanDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, United States of America.
Patient Hamuli CizaFaculty of Pharmaceutical Sciences, University of Kinshasa, Lemba, Kinshasa, Democratic Republic of the Congo.
Rose Ngono MballaFaculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon.
Eric ZiemonsDepartment of Pharmacy, Laboratory of Pharmaceutical Analytical Chemistry, University of Liege (ULiege), CIRM, Liège, Belgium.ORCID 0000-0001-6117-2031
Philippe HubertDepartment of Pharmacy, Laboratory of Pharmaceutical Analytical Chemistry, University of Liege (ULiege), CIRM, Liège, Belgium.
Roland Djang'eing'a MariniDepartment of Pharmacy, Laboratory of Pharmaceutical Analytical Chemistry, University of Liege (ULiege), CIRM, Liège, Belgium.
University of Liège · BEUniversité de Yaoundé I · CMInstituut voor Tropische Geneeskunde · BEUniversity of Kinshasa · CDUniversity of Notre Dame · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The negative consequences of Substandard and falsified (SF) medicines are widely documented nowadays and there is still an urgent need to find them in more efficient ways. Several screening tools have been developed for this purpose recently. In this study, three screening tools were used on 292 samples of ciprofloxacin and metronidazole collected in Cameroon. Each sample was then analyzed by HPLC and disintegration tests. Seven additional samples from the nitro-imidazole (secnidazole, ornidazole, tinidazole) and the fluoroquinolone (levofloxacin, ofloxacin, norfloxacin, moxifloxacin) families were analyzed to mimic falsified medicines. Placebo samples that contained only inert excipients were also tested to mimic falsified samples without active pharmaceutical ingredient (API). The three screening tools implemented were: a simplified visual inspection checklist, a low-cost handheld near infrared (NIR) spectrophotometer and paper analytical devices (PADs). Overall, 61.1% of the samples that failed disintegration and assay tests also failed the visual inspection checklist test. For the handheld NIR, one-class classifier models were built to detect the presence of ciprofloxacin and metronidazole, respectively. The APIs were correctly identified in all the samples with sensitivities and specificities of 100%. However, the importance of a representative and up-to-date spectral database was underlined by comparing models built with different calibration set spanning different variability spaces. The PADs were used only on ciprofloxacin samples and detected the API in all samples in which the presence of ciprofloxacin was confirmed by HPLC. However, these PADs were not specific to ciprofloxacin since they reacted like ciprofloxacin to other fluoroquinolone compounds. The advantages and drawbacks of each screening tool were highlighted. They are promising means in the frame of early detection of SF medicines and they can increase the speed of decision about SF medicines in the context of pharmaceutical post-marketing surveillance.

Indexed as

Counterfeit DrugsSubstandard DrugsCiprofloxacinHumansLevofloxacinMetronidazoleProduct Surveillance, PostmarketingCiprofloxacinCounterfeit DrugsLevofloxacinMetronidazoleSubstandard Drugs

Identifiers

PMID37566594
PMCPMC10420354
OpenAlexW4385757428

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.