ArticleClinical and translational science2024
Expert survey on real-world data utilization and real-world evidence generation for regulatory decision-making in drug lifecycle in Korea.
Article in Clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Legal Basis and Regulatory Requirements for Utilizing Real-World Evidence in Medical Product Regulatory Decision-Making.Pharmacoepidemiology and drug safety · 2026Article
- The global flexible and navigable suction ureteral access sheaths (FANS) survey on utility, practices and future needs in flexible ureteroscopy: a EAU Endourology, PEARLS and IAU collaboration.World journal of urology · 2026Article
- Key Stakeholders' Knowledge, Opinions, and Interests on Real-World Evidence in the Regulatory Process-Results of an EU-Wide Survey.Clinical and translational science · 2025Article
- Pretrained patient trajectories for adverse drug event prediction using common data model-based electronic health records.Communications medicine · 2025Article
- Expert survey on real-world data utilization and real-world evidence generation for regulatory decision-making in drug lifecycle in Korea.Clinical and translational science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the importance of utilizing real-world data (RWD)/real-world evidence (RWE) for supporting regulatory scientific decision-making continues to grow, experiences and inputs from experts become crucial for developing a systematic and practice-oriented plan for the use of fit-for-purpose RWD/RWE. This study aimed to survey relevant experts from government agencies, industries, and academia to identify prerequisites for the drug life cycle in Korea. The questionnaire comprised the following: (A) the definition and categories of RWD/RWE, (B) the suitability and feasibility of using RWD/RWE at each authorization stage by the types of RWD, and (C) the challenges and solutions for the use of RWD/RWE. A total of 46 respondents completed the online survey, with 89.1% of them having prior experience with RWD/RWE usage. A majority of respondents agreed that RWD can be obtained from various sources. Among these sources, the registry was the most suitable source. It is suitable to compensate for the limitations of randomized control trials and ensure quality in data collection. Though there was consensus among the respondents for the use of RWD/RWE in post-marketing surveillance, the use of such data in new drug application (NDA) was disagreeable. Respondents considered it necessary to write a protocol in advance for RWD collection and RWE generation, for all RWD types. In conclusion, this study examined the perceptions of experts for RWD/RWE use at each approval stage of drugs. The results suggest that guidelines for the fit-for-purpose use of RWD/RWE should be developed via careful deliberation among experts in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.