The research article entitled “Prephase Steroid Treatment before Remission Induction Chemotherapy in Patients with Pediatric Acute Lymphoblastic Leukemia Using Common Data Model-Based Real-World Data: A Retrospective Observational Study”¹, which was first-authored by the former CCADD graduate,Yoona Choi, and co-authored by the members of CCADD  has been cited in the lastest haematology guidelines on the diagnosis and managemet of tumour lysis syndrome² published by the British Society for Haematology. Moreover, the study was cited in a recent review article published in the New England Journal of Medicine (NEJM)³ detailing the epidemiology and pathophysiology of tumor lysis syndrome.

The British Society for Haematology produces up-to-date evidence-based guidelines on the diagnosis and treatment of haematological disease, while The New England Journal of Medicine is one of the prominent journals of new medical knowledge and clinical best practicies worldwide (Impact Factor 78.5).

This recognition highlights the clinical significance of our study in advancing evidence-based practice for pediatric acute lymphoblastic leukemia. CCADD takes pride in producing research that informs medical decision-making, and will continue efforts to deliver impactful studies.

1_Choi Y, Kim BK, Won JH, Yoo JW, Choi W, Jung S, Kim JY, Choi IY, Chung NG, Lee JW, Choi JY, Kang HJ, Lee H. Prephase steroid treatment before remission induction chemotherapy in patients with pediatric acute lymphoblastic leukemia using common data model-based real-world data: a retrospective observational study. Clin Epidemiol. 2024 Apr 22;16:293-304. doi:10.2147/CLEP.S454263. PMID:38681782; PMCID:PMC11049150.

2_Chan YLT, El-Sharkawi D, Shah P, Chanouzas D, O’Connor D, Marks SD, et al. British Society for Haematology updated guidelines for the diagnosis and management of tumour lysis syndrome in adults and children with haematological malignancies: a focus on patient safety. Br J Haematol. 2025;00:1-11. doi:10.1111/bjh.70092.

3_Bociek RG, Lunning M. Tumor lysis syndrome. N Engl J Med. 2025 Sep 18;393(11):1104-1116. doi:10.1056/NEJMra2300923. PMID:40961427.

Prof. Howard and his team (David and Yujin) presented their works at the 2025 American College of Clinical Pharmacology (ACCP) Annual Meeting, held in Phoenix, Arizona, from September 14–16, 2025. Under the theme “Leveraging Innovative Approaches to Transform Clinical Pharmacology,” the conference gathered experts to exchange insights on the evolving landscape in the field of clinical pharmacology.

The team delivered three poster presentations: 1) “Optimized In-Context Learning Outperforms Finetuning for Clinical Information Extraction across Diverse Healthcare Settings,” 2) “A Set of Inputs with Coverage Guarantee Enhances the Prediction of Drug Interactions,” and 3) “Constructing a Domain-Specific English–Korean Parallel Dictionary for Clinical Pharmacology and Regulatory Science Using a Large Language Model”. The presentations attracted considerable attention and prompted engaging exchanges among participants. The team’s research showed that in-context learning can serve as a data-efficient alternative to finetuning for clinical information extraction, offering practical guidance for applying large language models in healthcare settings with limited resources. They also demonstrated that incorporating input features with coverage guarantees, validated through conformal prediction, enhances the performance of LLM-based drug–drug interaction prediction. Lastly, the team showed that a domain-specific English–Korean parallel dictionary helps overcome language barriers and strengthens communication in clinical pharmacology and regulatory science.

As for the sessions in the ACCP conference, it began with a plenary session on optimizing patient outcomes through individualized pharmacotherapy. Subsequent symposia explored a wide range of critical topics, including diversity plans outlined by the U.S. Food and Drug Administration (FDA), therapeutic strategies for maternal and pediatric populations, innovations in dosing for preterm infants, therapeutic drug monitoring for biologics, and the application of artificial intelligence. Each meeting offered a clear picture of where clinical pharmacology is heading. The focus on individualized pharmacotherapy and model-informed drug development showed how artificial intelligence and mechanistic modeling are reshaping trial design and outcome prediction. At the same time, discussions on therapeutic drug monitoring for biologics and dosing in preterm infants revealed the field’s growing ability to tailor therapy for vulnerable populations.

Collectively, the conference underscored the expanding role of clinical pharmacology at the intersection of data science, patient diversity, and regulation. For the team, presenting at ACCP 2025 was not only an opportunity to share their own research but also a chance to situate their work within the broader trends shaping the field. The experience affirmed the value of their research trajectory and highlighted promising new directions for interdisciplinary and globally relevant contributions to clinical pharmacology.

Sungwook Choi completed the 2025 Summer Internship Program at CCADD and is currently working as an undergraduate researcher. He majored in Software Engineering and Business Administration at Konkuk University. During his undergraduate studies, he authored a thesis titled “Risk Evaluation of Adverse Events Associated with Dupixent in COPD Patients”, in which he conducted survival analysis using a spontaneous reporting database provided by the FDA Adverse Event Reporting System. His current goal at CCADD is to deepen his understanding in causal inference for generating real-world evidence (RWE) and in drug–drug interaction research.

Chaeyoung Chang is an undergraduate researcher at CCADD, after completing the 2025 Summer Internship Program. She majors in Chemistry at Konkuk University. During the internship, she gained experience in leveraging large language models for regulatory applications and real-world data analysis. She aims to apply AI to advance drug development and generate clinical evidence from real-world data.

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.

Minseop Yeom is currently an undergraduate researcher at CCADD after completing the 2025 Summer Internship Program. He majors in Biotechnology and Big Data Convergence at Sangmyung University. During the internship, he gained foundational domain knowledge in AI-driven drug development and also partook in the research projects using large language models (LLMs) in various stages of drug development. He is particularly interested in AI-driven approaches to ensure medical-data integrity and detect anomalies. Ultimately, his goal is to contribute to biomedical research by leveraging emerging AI technologies.

Soyoung Park is an undergraduate researcher at CCADD after completing the 2025 Summer Internship program. She is a double major in Material Science and Engineering and Industrial and Data Engineering at Hongik University. During her undergraduate years, she was able to combine a strong foundation in engineering with advanced data analysis skills. During the internship, she participated in the research projects, where she gained experience in causality assessment for drug safety and developed a broader understanding of the overall drug development process. Building on these experiences, she is now exploring AI-driven approaches to drug development, with a particular interest in drug–drug interaction prediction and explainable machine learning, aiming to contribute to the advancement of safer and more effective drug development.

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.

This winter, CCADD welcomes six interns- Minsol Kim, Suhyun An, SeoYoon Jang, Seeun Park, Yura Choi and Nayoung Ku -  for the 2025 Winter Internship Program.

Minsol Kim is majoring in veterinary medicine at Seoul National University. She is interested in exploring the application of domain knowledge in the process of AI model development by utilizing her knowledge of pharmacology, toxicology, and physiology. Her goal is to build a solid foundation in AI and gain hands-on experience analyzing clinical data and investigating the drug development process. Through the 2025 CCADD winter internship program, she aims to explore potential career paths in the field of drug discovery.

Suhyun An is a student majoring in Stem Cell and Regenerative Biotechnology at Konkuk University. She previously worked as an undergraduate researcher in the Immunopharmacology Laboratory at Seoul National University College of Medicine, where she studied drug toxicity. Her current research interests include Drug-Drug Interactions (DDIs) and drug repurposing using artificial intelligence (AI). Her previous training primarily involved wet lab research. The CCADD internship will allow her to gain experience in data science applied to drug development, which will serve as a critical foundation for achieving her future research goals.

SeoYoon Jang is majoring in Systems Biotechnology at Chung-Ang University. She has a keen interest in AI and data science, which led her to complete the 2024 Boostcourse <DATA SCIENCE PROJECTS> coaching study program. Subsequently, she developed an interest in drug delivery and interned at the Lab of Drug Delivery and Cell Therapy at Sungkyunkwan University School of Medicine. Her growing passion for integrating AI into drug development led her to a winter internship at the CCADD. Through this internship, she aims to gain proficiency in data analysis tools and deepen her domain knowledge, with the goal of becoming a researcher specializing in AI-driven drug development.

Seeun Park is a senior at Yonsei University, double majoring in Biotechnology and Public Administration. She is willing to explore clinical pharmacology and regulatory science during this winter internship program. With passion in healthcare and safety, she focuses on gaining more experience and knowledge on artificial intelligence for clinical drug development and more specifically epigenetic study and policy analysis in Korea. It is her goal to work on expertise for the improvement of disease prevention and control.

Yura Choi is an undergraduate student in the Department of Chemistry at Kyung Hee University. She is passionate about AI-driven drug development, applying data science to pharmaceutical research. Through the LAIDD program, she has gained valuable insights into how AI can be applied to drug development. She aims to contribute to drug development and explore innovative therapeutic modalities by leveraging AI-driven data analysis. Currently, she is participating in the CCADD winter internship to strengthen her AI and data science expertise and deepen her understanding of research in drug development.

Nayoung Ku is an undergraduate in life science and AI convergence at Handong Global University. She previously earned a Bachelor’s degree in psychology at the National Institute of Lifelong Education by Examination for Self-Education. Nowadays, Nayoung mainly develops prediction modelling and optimization algorithms with various datasets. She had been a research assistant at Biodata Laboratory, Handong Global University, focusing on cancer diagnostic machine learning models using tumour-educated platelet (TEP) RNA-seq data for a year. Recently, she did a capstone project on NLP for an ovarian cancer diagnostic model using TEP RNA-seq pre-processed data, which showed her creativity in analytic approach. She received the Daewoong Pharmaceutical CEO Award at the JUMP AI 2024 Drug Discovery Competition, sponsored by the Korea Pharmaceutical and Bio-Pharma Manufacturers Association. In the competition, Nayoung and her team developed an advanced multi- perceptron to predict IC50 values for IRAK4 inhibitors by applying novel and strategic approaches to accelerate drug discovery processes. With her enthusiasm for enhancing the efficiency of drug discovery, she participates in this internship to experience real-world clinical data and its analysis, like electronic medical records. With a heart of admiration, she is yearning to learn the extraordinary methodology of CCADD. 

We hope that during their winter internship, they will build confidence in their area of expertise, develop independent learning skills to explore new knowledge, and dedicate their enthusiasm to gaining a comprehensive understanding of drug development and regulatory science throughout these two months.

CCADD members attended the 2025 Spring Conference of the Korean Society of Medical Informatics (KOSMI), held from June 22 to 24 at the Busan Port International Exhibition & Convention Center. Under the theme “AI and Human Collaboration in the Age of Generative AI,” the conference brought together experts from medicine, engineering, law, and industry to discuss the latest developments and practical applications in medical informatics.

Key topics included strategies to automate workflows involving electronic medical records (EMRs) , such as methods using large language models (LLMs), strategies for utilizing MyData in healthcare, integration of genomic and spatial biology data for precision medicine, the potential of quantum computing in medicine, and AI-driven clinical prediction and decision support systems (CDSS).

In the keynote speech, Prof. Adrian Zai of UMass Chan Medical School delivered a presentation titled “Steering the Future of Medicine: Human-Centered AI in the Generative Age.” He emphasized the importance of moving beyond what AI can do, toward how its impact should be directed in clinical settings. He highlighted human-centered design, ethical oversight, and global collaboration as essential to ensuring AI truly supports care delivery.

Dr. Yoona Choi, a former member of CCADD and now a research professor at Seoul National University Hospital's Child Cancer and Rare Disease Project, presented her work on developing an LLM-based computable phenotype for pediatric lymphoma subtypes. The model leverages structured and unstructured EMR data—such as pathology reports and genetic test results—to improve classification accuracy based on real-world clinical data.

Prof. Howard Lee, Founding Director of CCADD and CEO of the digital health startup PMATCH, introduced PillTalk, a mobile app that allows patients to independently check drug–drug interactions using public data made available by the Ministry of Food and Drug Safety. The app provides AI-powered, accessible information to help patients make safer medication decisions. Prof. Lee emphasized that public pharmaceutical datasets can be transformed into practical, patient-centered tools to enhance medication safety.

Through this conference, CCADD members were able to reflect on the essential role of interdisciplinary collaboration and responsible innovation in leveraging digital technologies to advance patient-centered care.