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.

One of our team’s studies has been recently accepted for publication in Scientific Reports, a peer-reviewed open-access journal from the Nature Portfolio. The study, entitled "Improving ACS Prediction in T2DM Patients by Addressing False Records in Electronic Medical Records Using Propensity Score," proposed a novel method to tackle inaccuracies in electronic medical records (EMRs)—specifically, false positives, false negatives (including potentially missing data) in clinical information that is expressed as binary categorical variables.

The study redefined propensity scores to adjust for incorrect or incomplete data entries. Our team demonstrated that this correction approach enhanced both the predictive performance and interpretability of machine learning models assessing the risk of acute coronary syndrome (ACS) in patients undergoing basal insulin therapy.

This research not only explored the application of statistical tools in digital health but also underscored the potential of machine learning to deliver more reliable and actionable predictions in routine clinical care.

This study was supported by the Seokcheon Nanum Foundation’s Future Medicine Research Support Program.

Suhyun An is a Master’s student at the Department of Molecular Medicine and Biopharmaceutical Science (MMBS), Graduate School of Convergence Science, Seoul National University.

Her research centers around Medical Decision Making and AI-based drug discovery using large language models and deep neural networks, with a focus on adverse drug reactions and drug–drug interactions.

Suhyun An participated in CCADD during the 2024 Winter Internship Program and gained experience in real world data preprocessing, and machine learning. After the internship, Suhyun An continued as an undergraduate researcher at CCADD and participated in projects analyzing real-world data, including electronic medical records and clinical notes. These projects improved skills in natural language processing, applications of Large Language Models, and programming languages like R, Python, and Structured Query Language (SQL).

Nayoung Ku is currently an undergraduate researcher at CCADD, following the successful completion of her internship program. She is pursuing studies in life science and AI convergence at Handong Global University, with a previous Bachelor's degree in psychology. Nayoung specializes in developing prediction modeling and optimization algorithms with diverse datasets.

Her research includes work at the Biodata Laboratory developing cancer diagnostic machine learning models, and she received the Daewoong Pharmaceutical CEO Award at the JUMP AI 2024 Drug Discovery Competition for her team's work on IRAK4 inhibitor prediction.

On January 16, CCADD was selected as the lead research institution for the 2025 Contract Research and Development Project by the Ministry of Food and Drug Safety (MFDS). The project aims to develop a large-scale Korean-English corpus and translation model specialized in the pharmaceutical field. The total research funding amounts to KRW 1 billion (approximately USD 692,900). For this project, CCADD will collaborate with the Structure & Knowledge Injection into Machine Learning lab (SKIML) at the Graduate School of Data Science, Seoul National University (PI: Prof. Jaeyoon Lee) and the Korea Regulatory Science Center (PI: Dr. Sungkoo Son).

As part of this research, the team will develop a high-quality, domain-specific Korean-English corpus, ensuring consistent translation quality. The corpus will be rigorously validated and evaluated by experts to maintain translation accuracy and reliability. Furthermore, the team will develop a -level Korean-English neural machine translation (NMT) model and a large language model (LLM) in the pharmaceutical and medical fields based on this corpus.

CCADD and its research team officially launched the project with an initiation meeting on February 13 with MFDS. During the meeting, key stakeholders established research objectives and outlined a strategic roadmap for the next two years.

The team members, David Seung U Lee, Yujin Kim, and Prof. Howard Lee anticipate this research will establish Korea’s first high-quality pharmaceutical corpus and develop an advanced translation model processing pharmaceutical information accurately. With expertise in regulatory science, drug development, and AI, CCADD aims to successfully complete the project and contribute to advancements in pharmaceutical and medical fields.

Professor Howard and David attended the 84th Scientific Sessions of the American Diabetes Association (ADA). It was held from June 21 to 24 in Orlando, Florida, hosting experts in diabetes research from all over the world. The event brought together leading scientists, healthcare professionals, and stakeholders to discuss critical issues, including advancements in diabetes technology. It also showcased cutting-edge research and innovations in diabetes treatment and management, ranging from obesity and GLP-1 receptor agonists to autoantibody testing and early diabetes detection.

The event also provided a memorable venue for Prof. Howard and David, where they presented their work on “Developing Machine Learning Model for Predicting Acute Coronary Syndrome in Type 2 Diabetes Mellitus Patients through Substitution of Propensity Scores for Binary Variables”. During the poster presentation session, questions were asked and answered, ideas were exchanged, and constructive comments were offered. The event, along with the opportunity to present the work, paved the way for improving the study and provided a valuable experience to learn from world-renowned researchers.

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.

On February 26th, Professor Howard and the CCADD members gathered to honor the graduation of Tae Kyu Chung and the successful completion of the winter internship program by Seorin Choi and Yunha Noh.

Tae Kyu, who studied the realm of biology-neurobiology as an undergrad, joined CCADD in February 2018 as an intern. Under the guidance of Professor Howard Lee thenceforth, he navigated through the rigors of an integrated master's and PhD program. His persistent dedication to PKPD modeling culminated in a doctoral thesis entitled “Comparison of Machine Learning and Population Pharmacokinetic Models for Predicting Antiepileptic Drug Concentrations Based on Therapeutic Drug Monitoring Records”, earning him a Doctor of Medicine degree. On the graduation day, his relentless pursuit was duly awarded.

Simultaneously, a ceremony to mark the completion of Seorin and Yunha's internship was conducted at the main campus of Seoul National University. Throughout their internship, they immersed themselves in a series of educational endeavors, presentations, and assignments. On that day, their efforts, all contained within a comprehensive poster presentation, were met with a deep appreciation. Members of CCADD also attended the ceremony to celebrate the completion of their internships.

As we congratulate their accomplishments, we also look forward with anticipation to their future as independent researchers.