A research article entitled "Design and Evaluation of an Automated Pediatric Acute Lymphoblastic Leukemia Registry from Clinical Data Warehouses" has been published in BMC Medical Informatics and Decision Making (2026). BMC Medical Informatics and Decision Making is a leading international journal that publishes high-impact research on the development, implementation, and evaluation of medical informatics, clinical decision-making systems, and health information technologies. Our study presents a comprehensive framework for constructing a high-quality, scalable pediatric acute lymphoblastic leukemia (ALL) registry through automated extraction of electronic medical record (EMR)-based real-world data (RWD) from clinical data warehouses (CDWs).

The study developed PeARL (Pediatric ALL Registry using eLectronic medical record-based RWD) by integrating standardized mapping, multivariate transformations, and rule-based natural language processing (NLP) to capture clinically relevant variables from two university-affiliated tertiary-care hospitals in South Korea: Seoul National University Hospital (SNUH) and the Catholic Medical Center (CMC). A total of 1,609 pediatric patients with ALL (663 from SNUH and 946 from CMC) were included. Data quality was systematically evaluated using 228 rules across five dimensions (completeness, validity, accuracy, uniqueness, consistency).

The results showed that the automated data extraction proportion reached 89.7% at SNUH and 75.0% at CMC, with most elements processed through single-field transformations. After applying the quality management process, the overall error rate decreased from 1.858% to 0.001% at SNUH and from 0.129% to 0.001% at CMC, corresponding to an estimated reliability of 99%. Moreover, the registry demonstrated robust multicenter applicability through standardized table specifications and cross-site review, despite structural differences between institutional CDWs.

Overall, the study highlights the potential of a clinically guided, standardized framework as a reproducible and scalable solution for registry construction. By combining structured mapping, multivariate transformation, and rule-based NLP, the proposed approach offers a practical pathway for multicenter research and regulatory-grade real-world evidence generation.

Sunyoung Lee is a Master’s student at the Department of Molecular Medicine and Biopharmaceutical Science (MMBS), Graduate School of Convergence Science, Seoul National University. She is a registered nurse who earned her nursing degree from Ajou University and gained clinical experience at Seoul National University Hospital. She later worked as a Clinical Project Leader at the Development Center of Daewoong Pharmaceutical Company and partook in the clinical research of Fexuprazan and URSA. With her growing interest in real-world data (RWD) and real-world evidence (RWE), she joined CCADD during the 2025 Summer Internship Program to further explore the field and develop her research competencies.

This summer, CCADD welcomes five interns - Minseop Yeom, Sungwook Choi, Sunyoung Lee, Soyoung Park and Chaeyoung Chang - for the 2025 Summer Internship Program.

Minseop Yeom is a student majoring in Biotechnology and Big Data Convergence at Sangmyung University. He is particularly interested in how artificial intelligence (AI) can be applied in clinical research and used to improve the efficiency of drug development systems. Through the CCADD internship, he hopes to gain hands-on experience in data-driven approaches to clinical development. This opportunity will serve as an essential step toward his long-term goal of becoming a researcher who contributes to advancing clinical processes and drug discovery through AI-based innovation.

Sungwook Choi is a student majoring in Software Engineering and Business Administration at Konkuk University. He previously worked as a part-time employee at Celltrion, where he developed an interest in biosimilars and clinical statistics. During the upcoming summer internship program, he aims to enhance efficiency in the drug development process and contribute to the development of manufacturing and analytical methods using AI.

Sunyoung Lee is a registered nurse who earned her nursing degree from Ajou University. She gained clinical experience at Seoul National University Hospital and later worked as a Clinical Project Leader at the Development Center of Daewoong Pharmaceutical Company. With a growing interest in real-world data (RWD) and real-world evidence (RWE), she joined the CCADD internship program to further explore and develop her research competencies.

Soyoung Park is an undergraduate at Hongik University, majoring in Materials Science and Engineering with a double major in Industrial Data Engineering. At the Artificial Intelligence & Application Lab (AIA Lab), she contributed to developing machine learning models for predicting rotator cuff re-tear and reoperation. Rather than feeding MRI images directly into models, she reviewed each scan to identify the tear site and consistently measured its size. She then structured the data for modeling. By integrating these imaging features with clinical variables, she built predictive datasets and became familiar with the challenges of working with RWD, such as missing values, inconsistent ation, and the need for clinical context. This experience led to her interest in RWD analysis and how it can support data-driven decision-making in medicine. Her current interests include RWD analysis, medical AI, and applying generative AI to clinical workflows. Through the CCADD internship, she hopes to gain practical experience in clinical data analysis and build a strong foundation for future research in drug development.

Chaeyoung Chang is an undergraduate student majoring in Chemistry at Konkuk University, with a keen interest in integrating AI into drug development. She built foundational skills in data analysis through the K-Software Empowerment Bootcamp. Recently, she participated in the 2025 Google Solution Challenge, where her team developed an AI-powered emergency room matching service in the healthcare track. The team was selected among the global Top 10 and received the Most Societal Impact Award as one of the winners. She is now joining the CCADD internship to further explore AI-driven drug development and gain practical experience with real-world data.

During the 2025 summer internship, we hope interns continue to build confidence, stay curious, and actively engage in deepening their understanding of drug development and regulatory science with independence and passion.

Seoyoon Jang is enrolled in the Integrated Ph.D. Course at the Department of Molecular Medicine and Biopharmaceutical Science (MMBS), Graduate School of Convergence Science and Technology, Seoul National University. She previously worked as an undergraduate researcher at CCADD after completing the 2024 Winter Internship Program. Seoyoon Jang majored in Systems Biotechnology at Chung-Ang University. Her research interests include generating real-world evidence (RWE) from real-world data (RWD) using electronic medical records (EMR) and AI-based drug development. Through her internship, she became proficient in R, and during her undergraduate research experience, she further developed her research skills by working with a variety of LLM models.

Seeun Park is a Master’s student at the Department of Molecular Medicine and Biopharmaceutical Science (MMBS), Graduate School of Convergence Science, Seoul National University. She previously worked as an undergraduate researcher at CCADD after completing the 2024 Winter Internship Program. She majored in Bioengineering at Yonsei University. She was able to gain knowledge and hands-on experience on artificial intelligence for clinical drug development by the project “Improving the Generalizability of Natural Language Process Models to Extract Drug Safety Information from Clinical Notes”. With passion in healthcare and safety, she focuses on exploring clinical pharmacology and regulatory science more specifically Real-World Data (RWD) and policy analysis in Korea. It is her goal to work on expertise for the improvement of disease prevention and control.

This summer, CCADD welcomes three interns-Kim Chanmin, Choi Yunjin, and Yoo Kyungwan -for the 2024 Summer Internship Program.

Kyungwan Yoo, a student at Kyung Hee University, earned his Bachelor’s degree in genetic engineering. He worked as an undergraduate researcher at the Kyung Hee University Regenerative Medicine Institute, focusing on creating cell-targeting treatments. Currently, he is interested in integrating biological science with artificial intelligence (AI) technology and applying it to drug development. Kyungwan applied for the 2024 CCADD Summer Internship Program to expand his knowledge of drug development in general, be it clinical trials, and/or utilizing medical big data. He also intends to gain practical experiences in applying programming languages to these domains.

Yunjin Choi has graduated from Stony Brook University with a Bachelor’s degree in mathematics. After graduating, Yunjin worked as a statistical analyst at the Biomedical Research Institute, Korea University Guro Hospital. She has mainly conducted retrospective studies on nephrology and neurology. For example, she published a paper entitled "Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort", which examined the impact of fasting glucose variability on the risk of developing dementia in Parkinson's disease patients over a nine-year period. The study found that greater variability in fasting glucose levels was associated with a higher risk of dementia, further suggesting that stabilizing glucose levels might be beneficial for cognitive health in these patients. Besides being the first author of the study, she was also responsible for data analysis and interpretation, ensuring the accuracy and reliability of the study results. She also has the opportunity to learn how to draft and revise the manu and enhance its scientific merit. During this time, Yunjin developed an interest in Real-World Data (RWD), such as electronic medical records (EMR). She intends to pursue her interest while at CCADD.

Chanmin Kim is a Biological Engineering major at Kangwon National University. She became interested in developing new drugs while learning drug delivery systems. She also completed GMP training. After receiving the Excellence Award for designing smart healthcare products at Gachon University's DNA (Data, Network, AI) School Camp , she became interested in improving the efficiency of developing new drugs by applying data science and AI. Her goal is to become a researcher in the development of new drugs using AI. Through her 2024 CCADD summer internship program, she will pursue this goal.

We hope that during their summer internship, they will gain confidence in their field of study, learn how to study independently and explore new knowledge, and devote all their passion to gaining a deep understanding of drug development and regulatory science over the course of these two months.

Yunha Noh is currently an undergraduate research student at CCADD, following her successful completion of the 2023 Winter Internship Program. She has received dual Bachelor’s degrees in Biotechnology and Computer Engineering from Duksung Women's University. Her primary research interests include applying machine learning to drug repurposing and leveraging real world data (RWD) to real world evidence in medical science.

The study "Effectiveness and Safety of Sodium-Glucose Cotransporter 2 Inhibitors Added to Dual or Triple Treatment in Patients with Type 2 Diabetes Mellitus," authored by Yesol Hong, Yoomin Jeon, Yoona Choi, Tae Kyu Chung, and Howard Lee, was published in the Diabetes Therapy on December 20, 2023. Conducted at Seoul National University Hospital (SNUH) in South Korea, this research by the CCADD team delved into the use of Sodium-Glucose Cotransporter 2 Inhibitors (SGLT2i) in Type 2 Diabetes Mellitus (T2DM) treatment. The study, utilizing Real-World Data (RWD) from electronic medical records (EMR) from SNUH's a Common Data Model database, revealed improvements in HbA1c levels and a higher rate of patients achieving targeted HbA1c levels with SGLT2i therapy.

Furthermore, CCADD is dedicated to continuing its use of EMR-based RWD to generate important clinical evidence, particularly in areas where Randomized Controlled Trials (RCTs) may face limitations. This commitment underscores CCADD's role in advancing medical research and improving patient care through innovative data utilization.

Yoona Choi and Jung-Hyun Won attended the 65th Annual Meeting & Exposition of the American Society of Hematology (ASH), which took place from December 9 to 12, 2023, in San Diego, USA. Annually, the ASH conference brings together healthcare professionals, researchers, clinicians, and academics from around the globe to explore advancements in hematology. This prestigious event not only focuses on the study, diagnosis, treatment, and prevention of blood disorders but also features a variety of social events and opportunities for collaboration and the sharing of insights among experts in the field. Official photos from ASH are available here.

At the 'Outcomes Research—Lymphoid Malignancies: Poster II' session, Yoona Choi, serving as the first author and representing the entire research team, presented a study titled 'Evaluating the Effectiveness and Safety of Prephase Steroid Treatment before Remission Induction Chemotherapy in Pediatric Acute Lymphoblastic Leukemia: A Common Data Model-Based Real-World Data Approach.' This study investigated steroid pretreatment in pediatric acute lymphoblastic leukemia (ALL) patients undergoing remission induction chemotherapy (RIC), with the aim of reducing complications such as tumor lysis syndrome (TLS). Analyzing data from Seoul National University Hospital and Catholic University Seoul St. Mary’s Hospital, the study compared patients who received steroid pretreatment at least seven days before RIC with those who did not. The findings indicated a significant reduction in TLS incidence in the pretreated group. While overall survival rates were higher in this group, the difference was not statistically significant. These results provide important real-world evidence for the effectiveness of steroid pretreatment in reducing TLS risk in pediatric ALL patients.

This study was part of a larger project, funded by a grant from the Ministry of Health and Welfare, aiming to develop a disease registry database for pediatric ALL using real-world data in the clinical data warehouse (CDW) of Seoul National University Hospital and Catholic University Seoul St. Mary’s Hospital, thereby generating real-world evidence for pediatric ALL.