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Intelligent Classifier: A Tool to Impel Drug Technology Transfer from Academia to Industry
Hui-Heng Lin1; Defang Ouyang1; Yuanjia Hu1,2
2018-06-02
Source PublicationJournal of Pharmaceutical Innovation
ISSN1872-5120
Pages1-7
Abstract

Purpose Pharmaceutical technology transfer is one of the components of pharmaceutical innovation. Currently, a gap exists in pharmaceutical technology transfer from academia to industry. This study aims to develop an objective model to identify valuable pharmaceutical technologies for transferring in order to drive pharmaceutical innovation.
Methods We created a support vector machine classifier model using the data of pharmaceutical patents held by universities to predict the licensing outcomes of those patents.We collected data on 369 United States (US) pharmaceutical patents, using 142 licensed patents as the positive samples and 227 unlicensed patents as the negative samples.We also collected the licensing data of the patents, and the distinguished patent features were selected for model training and generation. Upon optimization, the machine learning model was evaluated using different scoring methods.
Results Our support vector machine-based model achieved a fairly good performance of 82.50% in precision and 88.89% in specificity.
Conclusions To the best of our knowledge, our study is the first to apply the machine learning approach to predict the licensing outcomes for pharmaceutical patent valuation and technology transfer. Our work is a good alternative to the current patent valuation methods available in the market, and it could be further developed for practical use in real business contexts.

KeywordUniversity Patents Patent Licensing Machine Learning Prediction Support Vector Machine Pharmaceutical Patents Technology Transfer
DOIhttps://doi.org/10.1007/s12247-018-9332-2
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Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
Corresponding AuthorYuanjia Hu
Affiliation1.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical SciencesUniversity of MacauMacauChina
2.The Research Center of National Drug Policy and Ecosystem, Nanjing, China
First Author AffilicationInstitute of Chinese Medical Sciences
Corresponding Author AffilicationInstitute of Chinese Medical Sciences
Recommended Citation
GB/T 7714
Hui-Heng Lin,Defang Ouyang,Yuanjia Hu. Intelligent Classifier: A Tool to Impel Drug Technology Transfer from Academia to Industry[J]. Journal of Pharmaceutical Innovation,2018:1-7.
APA Hui-Heng Lin,Defang Ouyang,&Yuanjia Hu.(2018).Intelligent Classifier: A Tool to Impel Drug Technology Transfer from Academia to Industry.Journal of Pharmaceutical Innovation,1-7.
MLA Hui-Heng Lin,et al."Intelligent Classifier: A Tool to Impel Drug Technology Transfer from Academia to Industry".Journal of Pharmaceutical Innovation (2018):1-7.
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