Ex) Article Title, Author, Keywords
Ex) Article Title, Author, Keywords
Pharmacoepidemiology and Risk Management 2023; 15(1): 11-22
Published online March 31, 2023 https://doi.org/10.56142/perm.23.0004
Copyright © Korean Society for Pharmacoepidemiology and Risk Management.
MinJeong Jeon1, MinYoung Ha1, HiGin Sung1, Hyesung Lee1,2, JaeHwan Song1, Ju-Young Shin1,2,3
전민정1, 하민영1, 성희진1, 이혜성1,2, 송재환1, 신주영1,2,3
Correspondence to:Ju-Young Shin
School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangangu, Suwon 16419, Korea
Tel: +82-31-290-7702
Fax: +82-31-292-8800
E-mail: shin.jy@skku.edu
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
After enacting the 21st Century Cures Act of 2016, real-world data (RWD) and realworld evidence (RWE) have been increasingly used to support drug development and approval worldwide. The importance of RWD/RWE is growing for decisionmaking, while the reliability of RWD/RWE is still a concern regarding the quality of data, reproducibility, and transparency. Regulatory agencies have published diverse guidelines to encourage the appropriate use of RWD/RWE, but there are differences in practical information detailing methodological and analytic approaches among countries. We compared guidelines focusing on study design and data analysis for RWD/RWE in the United States, Europe, South Korea from 2017 to 2022. We summarized RWD/RWE guidelines according to the timeline and conducted a GAP analysis from the following perspectives: (1) the roadmap for the use of RWD/RWE; (2) the current guideline for study design and data analysis; (3) features of guideline. Based on our findings, we suggest a future direction for developing governance in terms of study design and data analysis to enhance the utilization of RWD/RWE in South Korea.
KeywordsReal-World Data, Real-World Evidence, Guidelines, Study design, Data analysis
