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Treffer: Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance.

Title:
Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance.
Authors:
Kassekert R; GlaxoSmithKline, Global Safety, Upper Providence, PA, USA., Grabowski N; AbbVie, Pharmacovigilance and Patient Safety Business Process Office, North Chicago, IL, USA. neal.grabowski@abbvie.com., Lorenz D; Bayer AG, Medical Affairs and Pharmacovigilance, Pharmaceuticals, Berlin, Germany., Schaffer C; Merck Healthcare, Case and Vendor Management-Global Patient Safety, Darmstadt, Germany., Kempf D; Genentech, A Member of the Roche Group, South San Francisco, CA, USA., Roy P; Novartis, Chief Medical Office and Patient Safety, Novartis Global Drug Development, Dublin, Ireland.; Trinity College, Dublin, Ireland., Kjoersvik O; MSD, R&D IT, Prague, Czech Republic., Saldana G; Amgen, Pharmacovigilance Operations, Los Angeles, CA, USA., ElShal S; UCB, IT Patient Safety, Brussels, Belgium.
Source:
Drug safety [Drug Saf] 2022 May; Vol. 45 (5), pp. 439-448. Date of Electronic Publication: 2022 May 17.
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Adis, Springer International Country of Publication: New Zealand NLM ID: 9002928 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1179-1942 (Electronic) Linking ISSN: 01145916 NLM ISO Abbreviation: Drug Saf Subsets: MEDLINE
Imprint Name(s):
Publication: Auckland : Adis, Springer International
Original Publication: [Mairangi Bay, Auckland, N.Z. : ADIS Press Limited, c1990-
MeSH Terms:
Artificial Intelligence* , Pharmacovigilance*, Automation ; Humans ; Machine Learning ; Technology
References:
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Pharmaceut Med. 2020 Feb;34(1):7-18. (PMID: 32036574)
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Drug Saf. 2019 Apr;42(4):491-497. (PMID: 30343417)
Pharmaceut Med. 2019 Apr;33(2):109-120. (PMID: 31933254)
Clin Ther. 2021 Feb;43(2):372-379. (PMID: 33478803)
Drug Saf. 2021 Mar;44(3):261-272. (PMID: 33523400)
Comput Biol Med. 2021 Aug;135:104517. (PMID: 34130003)
Clin Ther. 2019 Aug;41(8):1414-1426. (PMID: 31248680)
Drug Saf. 2021 Feb;44(2):125-132. (PMID: 33026641)
Ther Innov Regul Sci. 2020 Jul;54(4):888-899. (PMID: 32557311)
Drug Saf. 2021 Mar;44(3):373-382. (PMID: 33354751)
Entry Date(s):
Date Created: 20220517 Date Completed: 20220519 Latest Revision: 20231105
Update Code:
20250114
PubMed Central ID:
PMC9114066
DOI:
10.1007/s40264-022-01164-5
PMID:
35579809
Database:
MEDLINE

Weitere Informationen

TransCelerate reports on the results of 2019, 2020, and 2021 member company (MC) surveys on the use of intelligent automation in pharmacovigilance processes. MCs increased the number and extent of implementation of intelligent automation solutions throughout Individual Case Safety Report (ICSR) processing, especially with rule-based automations such as robotic process automation, lookups, and workflows, moving from planning to piloting to implementation over the 3 survey years. Companies remain highly interested in other technologies such as machine learning (ML) and artificial intelligence, which can deliver a human-like interpretation of data and decision making rather than just automating tasks. Intelligent automation solutions are usually used in combination with more than one technology being used simultaneously for the same ICSR process step. Challenges to implementing intelligent automation solutions include finding/having appropriate training data for ML models and the need for harmonized regulatory guidance.
(© 2022. TransCelerate BioPharma Inc.)