Evidence map›Paper›PMID 40526757›Full record

ArticlePloS one2025

Quantitative evaluation and obstacle factor diagnosis of drug regulatory capacity in China.

Mingming Zhai, Liwen Huang, Shijie Sun, Liying Cao, Xueqiong Yue, Yuanxia Hu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Mingming ZhaiSchool of Medical Devices, Shenyang Pharmaceutical University, Shenyang.ORCID 0009-0008-5819-6575
Liwen HuangSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang.
Shijie SunSchool of Medical Devices, Shenyang Pharmaceutical University, Shenyang.
Liying CaoSchool of Medical Devices, Shenyang Pharmaceutical University, Shenyang.
Xueqiong YueSchool of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang.
Yuanxia HuSchool of Pharmacy, Shenyang Pharmaceutical University, Shenyang.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo quantitatively evaluate the drug regulatory capacity in China, aiming to optimize the drug regulatory system, precisely enhance local regulatory effectiveness, and reduce regional regulatory disparities.

methodsUsing the methods of literature research, expert interviews, investigation and analysis, the quantitative evaluation indicator system of supervision ability was established in all directions; the indicator data were collected and quantified; the indicator weight setting algorithm of the evaluation system was improved and the indicator weight was set by combining AHP and entropy method; the differences among eastern, central, and western provincial-level regions were analyzed by variance analysis; panel data were constructed for spatio-temporal evolution analysis; obstacle factor diagnosis model was used to analyze the obstacle factors.

resultsThe quantitative indicator system was constructed from five aspects: resource acquisition, function performance, learning and development, performance level and Internet application,and the relevant indicators of pharmacovigilance and risk response were analyzed at the national macro level. From the analysis of horizontal comparative variance, the comprehensive indicator and resource acquisition indicator of various provincial-level regions were significantly different(P < 0.05), while others were not significant. From the perspective of dynamic development, except for the performance level in 2022, all provincial-level regions were generally on the rise. From the perspective of obstacle factors, they were mainly in the aspects of learning development and functional performance. Regarding national pharmacovigilance and risk response, despite the synergistic development of all links ensuring drug safety and promoting industrial progress, new issues and challenges demand continuous attention and optimization of the regulatory system.

conclusionThere are regional differences in drug regulation in China. A drug regulation capacity improvement plan should be formulated in combination with the characteristics of the city itself and obstacle factors to achieve efficient and balanced development of drug regulation.

Indexed as

Drug and Narcotic ControlAlgorithmsChinaHumansPharmacovigilance

Identifiers

PMID40526757
PMCPMC12173186

What Socratic holds

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LicenceCC BY
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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 Socratic graph.