Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance

被引:0
|
作者
Raymond Kassekert
Neal Grabowski
Denny Lorenz
Claudia Schaffer
Dieter Kempf
Promit Roy
Oeystein Kjoersvik
Griselda Saldana
Sarah ElShal
机构
[1] GlaxoSmithKline,Novartis, Chief Medical Office and Patient Safety
[2] Global Safety,undefined
[3] AbbVie,undefined
[4] Pharmacovigilance and Patient Safety Business Process Office,undefined
[5] Bayer AG,undefined
[6] Medical Affairs and Pharmacovigilance,undefined
[7] Pharmaceuticals,undefined
[8] Merck Healthcare,undefined
[9] Case and Vendor Management-Global Patient Safety,undefined
[10] Genentech,undefined
[11] A Member of the Roche Group,undefined
[12] Novartis Global Drug Development,undefined
[13] Trinity College,undefined
[14] MSD,undefined
[15] R&D IT,undefined
[16] Amgen,undefined
[17] Pharmacovigilance Operations,undefined
[18] UCB,undefined
[19] IT Patient Safety,undefined
来源
Drug Safety | 2022年 / 45卷
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摘要
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.
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页码:439 / 448
页数:9
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