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Artificial intelligence in pharmacovigilance (PV) has the potential to disrupt life sciences industry while making the process quicker and data driven. This paper explores the role of AI in PV with special emphasis on ‘learning’-based observational processing. The system bundles the proprietary best-in-class natural language processing (NLP) and AI technologies capable of cleaning and contextually analyzing PV data identifying trends and outliers, including signals that can impact patient safety. Leveraging a combination of rule-based deterministic and probabilistic approaches to abstract patient data, medical events, drug, and reporter information. The most efficient results are produced when AI and PV professionals work closely in a symbiotic relationship where the bulk-processing is handled by AI systems, thus contributing to precise, quick, and informed decision-making by the pharmacovigilance professionals (PVP).
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