Literature DB >> 30632414

Research and development of anti-Parkinson's drugs: an analysis from the perspective of technology flows measured by patent citations.

Jingwen Qu1, Jiahong Lu1, Yuanjia Hu1.   

Abstract

INTRODUCTION: By 2020, nearly one million people will live with Parkinson's disease (PD) in the U.S. This disorder has a significant impact on patients' quality of life and is a burden on families and society. Protracted efforts have been made to treat the disease. Cumulative technological innovations are encapsulated by patents, and patent citations have been used to analyze technology diffusion processes in R&D, which is essential to identifying technology evolution trends and providing a review of PD treatment from the perspective of technology flows. AREAS COVERED: A patent citation network was utilized to analyze technology flows. Patents related to anti-PD drugs were collected from the U.S. Patent and Trademark Office (U.S. PTO) database. A total of 1,231 patents and 2,995 internal citations granted between 1988 and 2017 were included and analyzed. EXPERT OPINION: To launch drugs with greater efficiency and safety, approaches such as long-acting sustained release, controlled osmotic release, and other novel drug delivery systems should be emphasized. Multi-target agents could effectively reduce side effects in mono-drug therapy and are worth further exploration. Investors should keep an eye on alpha-synuclein-related therapy, gene therapy, and other experimental therapies that might trigger a historic revolution in the treatment domain.

Entities:  

Keywords:  Parkinson’s disease; patent citation network; research and development; technology evolution; technology flow

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Year:  2019        PMID: 30632414     DOI: 10.1080/13543776.2019.1567712

Source DB:  PubMed          Journal:  Expert Opin Ther Pat        ISSN: 1354-3776            Impact factor:   6.674


  2 in total

1.  Delivery of therapeutic small interfering RNA: The current patent-based landscape.

Authors:  Yu Chen; Shi-Hang Xiong; Fei Li; Xiang-Jun Kong; De-Fang Ouyang; Ying Zheng; Hua Yu; Yuan-Jia Hu
Journal:  Mol Ther Nucleic Acids       Date:  2022-06-22       Impact factor: 10.183

Review 2.  Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network.

Authors:  Ting Zhang; Juan Chen; Yan Lu; Xiaoyi Yang; Zhaolian Ouyang
Journal:  PLoS One       Date:  2022-08-22       Impact factor: 3.752

  2 in total

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