Prof. Howard Lee was featured in a show called 'Surprising Proof' by tvN, a local network broadcasting company in Korea. Prof. Lee spoke about why and how biopharmaceuticals have gained so much popularity in the treatment community over the past decades. Prof. Lee also discussed the impact of new biopharmaceuticals, mostly novel and innovative, on the society as a whole. Below is an excerpt from the program uploaded to YouTube.
The semester-long course "Understanding
New Health Technology Development" successfully concluded on
December 9 with final presentations by students. The event provided an
opportunity for participants to demonstrate their comprehensive understanding
of the drug development process and gain practical experience with its complexities.
During the presentations, students analyzed and presented the development journey of globally recognized
drugs, including Leqembi, Wegovy, and Zolgensma. Each team focused on the New
Drug Application (NDA) process, addressing preclinical and clinical phases,
regulatory hurdles, and market entry strategies. Their presentations showcased
a well-rounded understanding of the scientific, regulatory, and market
challenges involved in drug development.
The course was designed to emphasize the
importance of interdisciplinary collaboration in creating new health
technologies. Students explored critical decision-making principles at each
stage of the development process, equipping themselves with practical knowledge
essential for careers in the health tech sector. Key topics in the
presentations included — The mechanism of action and scientific foundations of
the drugs, Preclinical and clinical testing phases, Regulatory approval
procedures, and Market strategies and societal impact.
One student shared, "This course gave
us the unique opportunity to design and analyze the entire drug development
process, offering invaluable insights that extend beyond theoretical
knowledge." The "Understanding New Health Technology
Development" course concluded successfully, marking a significant
milestone in fostering future professionals equipped to advance the health
technology field.
The 2024 Seoul National University – Hokkaido University Joint Symposium was held with the theme "Exploring New Frontiers in Convergent Science and Technology." It brought together leading researchers and institutions to discuss cutting-edge advancements and to foster international collaboration. Hosted by the Graduate School of Convergence Science and Technology (GSCST) at Seoul National University, in partnership with Hokkaido University, the symposium featured a variety of talks, poster sessions, and networking opportunities.
CCADD attended the symposium, and more importantly, presented study results highlighting our research projects. As the dean of GSCST, Professor Howard Lee delivered a talk entitled "Application of Artificial Intelligence to Clinical Trials." The presentation emphasized that while AI in clinical trials is still in its infancy, its transformative potential cannot be overlooked. Professor Lee highlighted the importance of understanding the clinical domain to maximize AI’s impact, setting the stage for a future where AI can fundamentally improve trial success rates and the efficiency of drug development.
CCADD members also delivered poster presentations that showcased the breadth of our research. Jung-Hyun Won explored the feasibility of utilizing single-center real-world data from SNUH’s EMR system, demonstrating its representativeness for cancers such as liver and pancreatic cancer. David Seung U Lee introduced a cost-effective approach to enhance large language models for extracting clinical information from real-world clinical notes, focusing on optimizing prompt configurations and addressing data drift challenges. Yujin Kim presented a novel strategy for extracting chemotherapy-related adverse events in pediatric leukemia patients by combining structured data analysis with minimal manual chart reviews. Lastly, Yunjin Choi conducted an indirect comparative analysis of the efficacy between Tisagenlecleucel, a CAR-T cell therapy, and salvage/reinduction chemotherapy in pediatric relapsed/refractory leukemia, highlighting the complete remission rates achieved by CAR-T therapy.
This joint symposium provided a valuable opportunity to learn from diverse research fields and exchange insights, fostering mutual growth and collaboration among participants.
The event was especially meaningful because David Seung U Lee and Yu Jin Kim delivered oral presentations there.
The theme of this year’s conference was "From Vision to Value: AI's Role in Shaping Modern Healthcare." It focused on how artificial intelligence (AI) is reshaping the future of healthcare and transforming itself from a mere vision into tangible value. The discussions delved deeply into AI's roles in this transformative process. The conference provided a platform to share the latest research achievements and explored how AI contributes to patient care and system improvement in real-world medical settings.
As for the oral presentations by our members, David Seung U Lee presented the study entitled “Improving Few-shot Performance of Large Language Models to Extract Clinical Information from Real World Clinical Notes.” His research addressed the challenges of extracting information from unstructured and noisy clinical notes using large language models (LLMs). The study proposed a cost-effective strategy to enhance LLM performance by optimizing factors such as model size, example selection, and arrangement strategies. Using 2,110 annotated clinical notes from Seoul National University Hospital, the study demonstrated the trade-offs between prompt design and performance, with optimal results achieved using 15 examples and BM25-based example selection. Additionally, the research explored the impact of data drift on LLM robustness, offering insights into devising better prompting strategies for real-world applications.
Aligned with the focus of the conference, Yu Jin Kim also presented the study entitled “Adverse Event Extraction from EMR-Based Real-World Data in Pediatric Acute Lymphoblastic Leukemia Patients Receiving Chemotherapy.” The study introduced a sequential strategy for efficiently extracting adverse events (AEs) from electronic medical records (EMR), combining structured data analysis with minimal manual review. The method effectively captured clinically relevant AEs with reasonable accuracy, demonstrating its potential to enhance real-world data utilization for evaluating treatment safety in pediatric patients with acute lymphoblastic leukemia.
The conference was organized around the theme "Clinical Pharmacology in Innovative Therapeutics" and featured various sessions on latest topics, including Live Biotherapeutic Products, ICT in Clinical Trials, Voice from the Clinical Trial Field, Innovative Sites for Early Phase Clinical Trials, Omics with Clinical Pharmacology, and GCP Updates.
In the Live Biotherapeutic Products session, insights were shared on the discovery, CMC, non-clinical, and clinical studies of microbiome therapeutics, a promising new treatment modality. The ICT in Clinical Trials session addressed the latest developments in Real-World Evidence-based clinical trials and Decentralized Clinical Trials.The Voice from the Clinical Trial Field session brought together experts from institutions, SMOs, CROs, and clinical trial sites to share practical insights.
More importantly, CCADD members introduced their works through poster presentations.
David Seung U Lee, as the lead presenter, introduced the study "Improving Few-Shot Performance of Large Language Models to Extract Clinical Information from Real-World Clinical Notes." This research evaluated how large language models (LLMs) like Llama-3.18 perform on clinical information extraction tasks using annotated notes from Seoul National University Hospital. The study demonstrated the importance of optimized prompting strategies and entity distributions, achieving high accuracy and robustness. These findings highlight the potential of LLMs in advancing clinical text analysis for real-world applications. Meanwhile Jung-Hyu Won and Yun Jin Choi presented their study titled "Comparing the Therapeutic Efficacy of Tisagenlecleucel and Salvage Chemotherapy in Pediatric Relapsed/Refractory B-Cell Acute Lymphoblastic Leukemia: A MAIC Approach." This research retrospectively analyzed outcomes using the Matching-Adjusted Indirect Comparison (MAIC) method to evaluate Tisagenlecleucel, a CD19-targeting CAR-T cell therapy, against salvage/reinduction chemotherapy. Results showed that while no significant differences were observed in overall remission rates (ORR) or overall survival (OS), Tisagenlecleucel achieved a significantly higher complete remission (CR) rate. These findings highlight the potential of CAR-T therapy as an effective option for pediatric relapsed/refractory B-ALL.
Through their participation in this conference, CCADD members gained a deeper understanding of the latest advancements in clinical pharmacology and therapeutics.
Yunjin Choi is currently undergraduate researcher at CCADD, following the completion of the 2024 Summer Internship program. Yunjin Choi has studied mathematics at Stony Brook University. After college, Yunjin worked as a statistical analyst at the Biomedical Research Institute, Korea University Guro Hospital. She has mainly assisted conducting retrospective observational studies on nephrology and neurology. As an analyst, Yunjin developed an interest in real-world data (RWD), such as electronic medical records (EMR). She intends to pursue her interest while at CCADD.
On September 1, 2024, Prof. Howard Lee was sworn in as Dean of the Graduate School of Convergence Science and Technology, Seoul National University. In this capacity, Prof. Lee will lead GSCST to transform its strengths to another level. In his inaugural speech, Prof. Lee stressed urgent changes that need to take place to regain the uniqueness of GSCST, which can happen only if the school fully embraces adaptability in a fast-moving environment and challenges. Prof. Lee will serve for two years, which can be repeated one more term.
Through the program, David aims to leverage advanced machine learning technologies to accelerate the development of precision medicine and drug discovery. His research will integrate real-world data, including various omics data and electronic health records, to develop personalized disease risk and treatment response prediction models. These models will not only help in formulating personalized treatment strategies that optimize outcomes and minimize adverse effects but will also propose cost-reduction methods by applying these models to the time-consuming and expensive clinical trial phases, enabling rapid and accurate selection of eligible patients.
David expressed his honor in being selected for the program, stating, "I am thrilled to have the opportunity to collaborate with emerging researchers in Sweden on significant societal issues such as climate change, precision medicine, and innovative energy solutions. The guidance and support from experienced mentors will undoubtedly enhance my research capabilities. I am committed to utilizing the knowledge and experience gained from this program to achieve better research outcomes and contribute to both academia and society."
Won J-H, Hong Y, Kim SU, Lee H. One-year Post-Acute COVID-19 Syndrome and Mortality in South Korea: A Nationwide Matched Cohort Study Using Claims Data. Frontiers in Public Health, 12, 1403153. DOI 10.3389/fpubh.2024.1403153
CCADD members attended the 2024 Spring Conference of the Korean Society of Medical Informatics (KoSMI), held from June 19th to 21st at the Catholic University of Korea. The conference, aimed at advancing information-oriented societies, brought together experts from diverse sectors, including medicine, nursing, pharmacy, and engineering.
The conference featured several noteworthy sessions. Discussions on drug adverse reactions focused on improving patient safety through better detection and reporting mechanisms. The DUR platform sessions explored advancements in drug utilization review systems that help prevent medication errors. Presentations on natural language processing (NLP) showcased its application in extracting meaningful data from unstructured clinical notes, enhancing decision-making in clinical settings. Meanwhile, sessions on the limitations of multi-center Common Data Model (CDM) research highlighted challenges such as data standardization and integration across different institutions.
Lively discussions ensued on these topics, with various studies showcasing the innovative use of medical data to improve healthcare outcomes. The conference emphasized the dynamic and evolving nature of medical informatics, driven by continuous advancements in technology. A key theme throughout the conference was the importance of collaboration. Speakers and participants highlighted how interdisciplinary teamwork and partnerships between medical institutions, academic bodies, and industry are crucial for overcoming challenges and driving innovation in medical informatics.
This achievement stems from a collaborative effort involving CCADD, the Medical Informatics Lab of the College of Medicine at The Catholic University of Korea, led by Prof. In Young Choi, and hemato-oncologists from both hospitals. Dr. Choi's presentation provided an in-depth evaluation of the algorithm developed to extract information automatically from CDWs into the registry, highlighting its practical applications and significant implications for pediatric ALL research.
The session chair lauded Dr. Choi’s presentation, commending its excellence and the potential impact of this innovative work on future medical research and patient care.
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.
HOME
