Artificial Intelligence, Real-World Automation and the Safety of Medicines
Despite huge technological advances in the capabilities to capture, store, link and analyse data electronically, there has been some but limited impact on routine pharmacovigilance. We discuss emerging research in the use of artificial intelligence, machine learning and automation across the pharmac...
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| Veröffentlicht in: | Drug safety 2021-02, Vol.44 (2), p.125-132 |
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| container_title | Drug safety |
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| creator | Bate, Andrew Hobbiger, Steve F. |
| description | Despite huge technological advances in the capabilities to capture, store, link and analyse data electronically, there has been some but limited impact on routine pharmacovigilance. We discuss emerging research in the use of artificial intelligence, machine learning and automation across the pharmacovigilance lifecycle including pre-licensure. Reasons are provided on why adoption is challenging and we also provide a perspective on changes needed to accelerate adoption, and thereby improve patient safety. Last, we make clear that while technologies could be superimposed on existing pharmacovigilance processes for incremental improvements, these great societal advances in data and technology also provide us with a timely opportunity to reconsider everything we do in pharmacovigilance operations to maximise the benefit of these advances. |
| doi_str_mv | 10.1007/s40264-020-01001-7 |
| format | Article |
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| identifier | ISSN: 0114-5916 |
| ispartof | Drug safety, 2021-02, Vol.44 (2), p.125-132 |
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| language | eng |
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| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Algorithms Artificial Intelligence Automation Breast cancer Current Opinion Drug Safety and Pharmacovigilance Humans Learning algorithms Life cycle analysis Machine learning Mammography Medicine Medicine & Public Health Neural networks Patient safety Pharmacology Pharmacology/Toxicology Pharmacovigilance Safety |
| title | Artificial Intelligence, Real-World Automation and the Safety of Medicines |
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