Evidence map›Paper›PMID 26673466›Full record

ArticleInternational journal of health policy and management2015

Biopharmaceutical Innovation System in China: System Evolution and Policy Transitions (Pre-1990s-2010s).

Hao Hu, Chao-Chen Chung

Abstract read
In one paragraph

Article in International journal of health policy and management, 2015. 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
–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

3 citing papers in PubMed.

  1. Review
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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

2 authors.

Hao HuInstitute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, Macau.
Chao-Chen ChungDepartment of Political Science, National Cheng- Kung University, Tainan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis article sets up the initial discussion of the evolution of biopharmaceutical innovation in China through the perspective of sectoral innovation system (SIS).

methodsTwo data sources including archival documentary data and field interviews were used in this study. Archival documentary data was collected from China Food and Drug Administration (CFDA) and Chinese National Knowledge Infrastructure (CNKI). In addition, industrial practitioners and leading researchers in academia were interviewed.

resultsBiopharmaceutical in China was established through international knowledge transfer. The firms played more active role in commercializing biopharmaceutical in China though universities and research institutes were starting to interact with local firms and make contribution to biopharmaceutical industrialization. The transition of the Chinese government's policies continuously shapes the evolution of biopharmaceutical sector. Policies have been dramatic changes before and after 1980s to encourage developing biopharmaceutical as a competitive industry for China.

conclusionA SIS for biopharmaceutical has been shaped in China. However, currently biopharmaceutical is still a small sector in China, and for the further growth of the industry more synthetic policies should be implemented. Not only the policy supports towards the research and innovation of biopharmaceuticals in the early stage of development should be attended, but also commercialization of biopharmaceutical products in the later stage of sales.

Indexed as

Biomedical ResearchBiotechnologyDrug IndustryGovernmentPublic PolicyAcademies and InstitutesBiological ProductsChinaCommerceHumansUnited StatesUniversitiesBiological ProductsBiopharmaceuticalBiotechnologyChinaPharmaceutical IndustrySectoral Innovation System (SIS)

Identifiers

PMID26673466
PMCPMC4663085

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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.