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Biomedical Literature Mining pp 227–251Cite as

Role of Text Mining in Early Identification of Potential Drug Safety Issues

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1159))

Abstract

Drugs are an important part of today’s medicine, designed to treat, control, and prevent diseases; however, besides their therapeutic effects, drugs may also cause adverse effects that range from cosmetic to severe morbidity and mortality. To identify these potential drug safety issues early, surveillance must be conducted for each drug throughout its life cycle, from drug development to different phases of clinical trials, and continued after market approval. A major aim of pharmacovigilance is to identify the potential drug–event associations that may be novel in nature, severity, and/or frequency. Currently, the state-of-the-art approach for signal detection is through automated procedures by analyzing vast quantities of data for clinical knowledge. There exists a variety of resources for the task, and many of them are textual data that require text analytics and natural language processing to derive high-quality information. This chapter focuses on the utilization of text mining techniques in identifying potential safety issues of drugs from textual sources such as biomedical literature, consumer posts in social media, and narrative electronic medical records.

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Acknowledgment

Mei Liu is supported by funds from the New Jersey Institute of Technology. Yong Hu is supported by the National Science Foundation of China (71271061, 70801020); Science and Technology Planning Project of Guangdong Province, China (2010B010600034, 2012B091100192); and Business Intelligence Key Team of Guangdong University of Foreign Studies (TD1202). Buzhou Tang is supported by the China Postdoctoral Science Foundation (2011 M500669).

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  1. Department of Computer Science, New Jersey Institute of Technology, University Heights, Newark, NJ, 07102, USA

    Mei Liu

  2. Institute of Business Intelligence, Guangdong University of Foreign Studies, Sun Yat-sen University, Guangzhou, 510006, People’s Republic of China

    Yong Hu

  3. Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, 518055, People’s Republic of China

    Buzhou Tang

Authors
  1. Mei Liu
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  2. Yong Hu
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  3. Buzhou Tang
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Correspondence to Mei Liu .

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Editors and Affiliations

  1. GlaxoSmithKline, King of Prussia, Pennsylvania, USA

    Vinod D. Kumar

  2. GlaxoSmithKline, Hitchin, Hertfordshire, United Kingdom

    Hannah Jane Tipney

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© 2014 Springer Science+Business Media New York

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Liu, M., Hu, Y., Tang, B. (2014). Role of Text Mining in Early Identification of Potential Drug Safety Issues. In: Kumar, V., Tipney, H. (eds) Biomedical Literature Mining. Methods in Molecular Biology, vol 1159. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0709-0_13

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  • DOI: https://doi.org/10.1007/978-1-4939-0709-0_13

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0708-3

  • Online ISBN: 978-1-4939-0709-0

  • eBook Packages: Springer Protocols

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