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Biomedical Text Mining pp 237–258Cite as

A Text Mining Protocol for Predicting Drug–Drug Interaction and Adverse Drug Reactions from PubMed Articles

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2496))

Abstract

Drug–drug interactions (DDIs) and adverse drug reactions (ADRs) occur during the pharmacotherapy of multiple comorbidities and in susceptible individuals. DDIs and ADRs limit the therapeutic outcomes in pharmacotherapy. DDIs and ADRs have significant impact on patients’ life and health care cost. Hence, knowledge of DDI and ADRs is required for providing better clinical outcomes to patients. Various approaches are developed by the scientific community to document and report the occurrences of DDIs and ADRs through scientific publications. Due to the enormously increasing number of publications and the requirement of updated information on DDIs and ADRs, manual retrieval of data is time consuming and laborious. Various automated techniques are developed to get information on DDIs and ADRs. One such technique is text mining of DDIs and ADRs from published biomedical literature in PubMed. Here, we present a recently developed text mining protocol for predicting DDIs and ADRs from PubMed abstracts.

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Author information

Author notes

  1. Mohamed Saleem Abdul Shukkoor

    Present address: College of Pharmacy, Riyadh Elm University, Riyadh, Kingdom of Saudi Arabia

Authors and Affiliations

  1. Regenerative Biology, Morgridge Institute for Research, Madison, WI, USA

    Kalpana Raja

  2. Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA

    Kalpana Raja

  3. Department of Human Anatomy, Faculty of Medicine and Health Sciences, University Putra Malaysia (UPM), Serdang, Selangor, Malaysia

    Mohamad Taufik Hidayat Baharuldin

  4. Unit of Physiology, Department of Preclinical, Faculty of Medicine and Defence Health, National Defence University of Malaysia,, Kuala Lumpur, Malaysia

    Mohamad Taufik Hidayat Baharuldin

Authors
  1. Mohamed Saleem Abdul Shukkoor
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  2. Kalpana Raja
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  3. Mohamad Taufik Hidayat Baharuldin
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Editor information

Editors and Affiliations

  1. Morgridge Institute for Research, University of Wisconsin, Madison, WI, USA

    Kalpana Raja

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© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Shukkoor, M.S.A., Raja, K., Baharuldin, M.T.H. (2022). A Text Mining Protocol for Predicting Drug–Drug Interaction and Adverse Drug Reactions from PubMed Articles. In: Raja, K. (eds) Biomedical Text Mining. Methods in Molecular Biology, vol 2496. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2305-3_13

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  • DOI: https://doi.org/10.1007/978-1-0716-2305-3_13

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2304-6

  • Online ISBN: 978-1-0716-2305-3

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