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OtherReview Article

Review of Natural Language Processing in Pharmacology

Dimitar Trajanov, Vangel Trajkovski, Makedonka Dimitrieva, Jovana Dobreva, Milos Jovanovik, Matej Klemen, Aleš Žagar and Marko Robnik-Šikonja
Pharmacological Reviews March 17, 2023, PHARMREV-AR-2022-000715; DOI: https://doi.org/10.1124/pharmrev.122.000715
Dimitar Trajanov
1
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  • For correspondence: dimitar.trajanov@finki.ukim.mk
Vangel Trajkovski
2Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia
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Makedonka Dimitrieva
2Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia
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Jovana Dobreva
2Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia
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Milos Jovanovik
2Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia
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Matej Klemen
3Faculty of Computer and Information Science, University of Ljubljana, Slovenia
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Aleš Žagar
3Faculty of Computer and Information Science, University of Ljubljana, Slovenia
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Marko Robnik-Šikonja
3Faculty of Computer and Information Science, University of Ljubljana, Slovenia
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Abstract

Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and use it in various applications. This area has rapidly developed in the last few years and now employs modern variants of deep neural networks to extract relevant patterns from large text corpora. The main objective of this work is to survey the recent use of NLP in the field of pharmacology. As our work shows, NLP is a highly relevant information extraction and processing approach for pharmacology. It has been used extensively, from intelligent searches through thousands of medical documents to finding traces of adversarial drug interactions in social media. We split our coverage into five categories to survey modern NLP methodology, commonly addressed tasks, relevant textual data, knowledge bases, and useful programming libraries. We split each of the five categories into appropriate subcategories, describe their main properties and ideas, and summarize them in a tabular form. The resulting survey presents a comprehensive overview of the area, useful to practitioners and interested observers.

Significance Statement The main objective of this work is to survey the recent use of NLP in the field of pharmacology, in order to provide a comprehensive overview of the current state in the area after the rapid developments which occurred in the last few years. We believe the resulting survey to be useful to practitioners and interested observers in the domain.

  • adverse drug reactions
  • drug analysis
  • drug discovery
  • Copyright © 2023 American Society for Pharmacology and Experimental Therapeutics

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Pharmacological Reviews: 75 (2)
Pharmacological Reviews
Vol. 75, Issue 2
1 Mar 2023
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OtherReview Article

Review of Natural Language Processing in Pharmacology

Dimitar Trajanov, Vangel Trajkovski, Makedonka Dimitrieva, Jovana Dobreva, Milos Jovanovik, Matej Klemen, Aleš Žagar and Marko Robnik-Šikonja
Pharmacological Reviews March 17, 2023, PHARMREV-AR-2022-000715; DOI: https://doi.org/10.1124/pharmrev.122.000715

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OtherReview Article

Review of Natural Language Processing in Pharmacology

Dimitar Trajanov, Vangel Trajkovski, Makedonka Dimitrieva, Jovana Dobreva, Milos Jovanovik, Matej Klemen, Aleš Žagar and Marko Robnik-Šikonja
Pharmacological Reviews March 17, 2023, PHARMREV-AR-2022-000715; DOI: https://doi.org/10.1124/pharmrev.122.000715
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