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Generative artificial intelligence (GenAI) shows promise in automating key tasks involved in conducting systematic literature reviews (SLRs), including screening, bias assessment and data extraction. This potential automation is increasingly relevant as pharmaceutical developers face challenging requirements for timely and precise SLRs using the population, intervention, comparator and outcome (PICO) framework, such as those under the impending European Union (EU) Health Technology Assessment Regulation 2021/2282 (HTAR). This proof-of-concept study aimed to evaluate the feasibility, accuracy and efficiency of using GenAI for mass extraction of PICOs from PubMed abstracts.

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