Evidence map›Paper›PMID 37250167›Full record

ArticleActa pharmaceutica Sinica. B2023

Data-driven engineering framework with AI algorithm of Ginkgo Folium tablets manufacturing.

Lijuan Ma, Jing Zhang, Ling Lin, Tuanjie Wang, Chaofu Ma, Xiaomeng Wang, Mingshuang Li, Yanjiang Qiao, Yongxiang Wang, Guimin Zhang and 1 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Acta pharmaceutica Sinica. B, 2023. 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
0.5field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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

11 authors at 4 institutions in 1 country.

Lijuan MaBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Jing ZhangBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Ling LinBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Tuanjie WangJiangsu Kanion Pharmaceutical Co., Ltd., State Key Laboratory of New Technology in Pharmaceutical Process of Traditional Chinese Medicine, Lianyungang 222001, China.
Chaofu MaBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Xiaomeng WangBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Mingshuang LiBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Yanjiang QiaoBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Yongxiang WangYangtze River Pharmaceutical (Group) Co., Ltd., State Pharmaceutical Engineering Technology Research Center of Traditional Chinese Medicine, Taizhou 225321, China.
Guimin ZhangLunan Pharmaceutical Group Co., Ltd., State Key Laboratory of Generic Technology of Traditional Chinese Medicine, Linyi 276005, China.
Zhisheng WuBeijing University of Chinese Medicine, Engineering Research Center for Pharmaceutics of Chinese Materia Medica and New Drug Development, Ministry of Education, Beijing 100029, China.
Beijing University of Chinese Medicine · CNKanion Pharmaceutical (China) · CNLuye Pharma (China) · CNYangtze River Pharmaceutical Group (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart manufacturing still remains critical challenges for pharmaceutical manufacturing. Here, an original data-driven engineering framework was proposed to tackle the challenges. Firstly, from sporadic indicators to five kinds of systematic quality characteristics, nearly 2,000,000 real-world data points were successively characterized from Ginkgo Folium tablet manufacturing. Then, from simplex to the multivariate system, the digital process capability diagnosis strategy was proposed by multivariate

Indexed as

Artificial intelligenceData-driven engineeringEnd-to-endInformation fusionProcess capability indexQuality traceabilityReal-world Ginkgo Folium productsSmart manufacturing

Identifiers

PMID37250167
PMCPMC10213986
OpenAlexW4292722289

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.