Researchers, clinicians, and engineers working at the crossroads of artificial intelligence and medicine got together once again this summer, and CCADD (Prof. Howard, David, Seeun) was there to join them. The occasion was the Conference on Health, Inference, and Learning (CHIL) 2026, a three-day gathering hosted in Seattle, Washington from June 28th through 30th.

Among a handful of research groups that were extended an invitation to the conference, Prof. Howard traveled together with his team Dr. David and Seeun. What made the trip especially meaningful this year was the publication of a paper from the lab, "Generation of Biingual Synthetic Clinical Notes for Realistic Data Augmentation," which the team unveiled to the community at the conference. Standing beside their poster, they walked visitors through the motivation and findings of the work, answering questions from curious attendees.

This year marked the seventh gathering of CHIL, jointly hosted by Sage Bionetworks and Seattle Children's Research Institute and hosted at the Institute's B. Wayne Hughes Building. As always, the program spanned a broad cross-section of issues shaping AI's role in healthcare. The conference opened with a keynote from Dr. Chris Longhurst, CEO of Seattle Children's, who spoke on "Evidence-based Medicine in the AI Era" and made the case for grounding AI adoption in real clinical implementation rather than hype. Dr. Pang Wei Koh followed with an invited talk on reinforcement learning approaches for deep research, and Dr. Jessilyn Dunn later delivered a keynote on wearable technology for disease detection titled "The Digital Physiome." A track devoted entirely to mental health also drew particular attention, weaving together talks on evaluating harm in AI safety, personalizing psychotherapy through language models, and building governance frameworks informed by practitioners, which were all capped off with a lively panel discussion.

For the team, the days in Seattle offered far more than a chance to share their research. They came away with new perspectives, new connections, and a renewed sense of how much further this field still has to grow.

CCADD, led by Professor Howard Lee, attended the 2026 Spring Conference of the Korean Society of Medical Informatics (KOSMI). The conference was held over three days, from June 24 to June 26, 2026, at OSCO in Cheongju and co-hosted by KOSMI and the Korea Health Industry Development Institute (KHIDI). This year’s theme was “From Operating System to Operating Society: Next Mission of Medical Informatics.” The sessions focused on artificial intelligence (AI) and large language models (LLMs) in medical informatics. Topics ranged from trustworthy medical AI to lifelog analysis and digital healthcare.

David Seung U Lee, a postdoctoral researcher at CCADD, gave an oral presentation in Session 2 (LLM-based Clinical Decision Support) on “DDI-Expert: Explainable Prediction of Pharmacokinetic Drug Interaction in Humans using Mixture of Experts.” His work moves beyond the limits of conventional drug–drug interaction (DDI) prediction. Using a Mixture of Experts (MoE) architecture that combines domain adaptation with domain application, it predicts pharmacokinetic DDI outcomes while also explaining their underlying mechanisms.

Yujin Kim, a student at CCADD, presented in the e-poster session (Generative AI and Clinical Text) on “Information Extraction and Structuring from Drug Approval Review Reports Using Large Language Models.” Her study introduced a pipeline that accurately extracts and structures information from drug approval review reports, which often have complex, multi-table layouts, while keeping costs low and performance high. The work covered the full process from model adaptation to evaluation.

Both presentations were well received at the conference. David Seung U Lee received the Best Oral Presentation Award, and Yujin Kim received the Best Poster Award. The awards mark another step in CCADD’s continued efforts to advance medical informatics through LLMs and AI-based approaches. CCADD will continue its research toward reliable and practical AI applications in healthcare and drug development.

On Friday, December 26, 2025, CCADD had the annual Year-End Workshop at Seoul National University, Seoul, South Korea. The workshop brought together all current CCADD members, part-time students and winter interns. Throughout a full day of presentations and discussions, CCADD members reflected on the year 2025 and looked ahead to 2026.

The workshop began with arrival and reception, followed by a series of presentations covering research progress, academic development, and practical lessons learned. As the first speaker, Seoyoon opened the program with a session titled “Looking Back on the Year 2025,” highlighting CCADD’s accomplishments in 2025 and celebrating the achievements of its members.

The yearly report was followed by Suhyun, who shared key takeaways from a year of full-time work at CCADD across two phases, from undergraduate research to the first semester of the master’s program. Then, Seeun presented “Preparation for the 1st Oral Presentation,” reflecting on her year-long research and walking through her conference-presentation preparation process. After that, Sunyoung delivered a presentation titled “Life in the Industry vs. Graduate School,” in which she introduced the role of a Clinical Project Leader at Daewoong Pharmaceutical Company highlighting key differences between life in industry and life as a master’s student. As the last session before lunch, David delivered a talk about the things he wished he had known early on, including having a daily habit of reading papers and making a usable personal template to take notes of what you learned from papers.

Following the morning sessions, participants took a break for lunch and then toured the main library at Seoul National University’s Gwanak Campus, exploring its study spaces, archives, and facilities. After the tour, members gathered for a photo time and captured group photos inspired by this year’s Pantone Color theme.

Soyoung presented “How I Learned Actually to Write” and explained what she learned while writing during the second half of 2025 under the supervision of Prof. Howard Lee. Then, Sungwook delivered a workshop talk titled “How I Became the Pre-crastinator at CCADD.” In the talk, he defined a “pre-crastinator” as someone who finishes tasks early and stays in the lab late to keep studying. It was followed by Chaeyoung, who shared her journey for the 2025 Google Solution Challenge, from ideation and development to presenting at the Asian Development Bank in the Philippines. She also reflected on pitching on an international stage and the lessons learned through receiving the award.

After a short break, the workshop continued with sessions focused on practical milestones and next-year planning. In the afternoon session, Seoyoon presented “First Grant Proposal: What I Learned and What I Wish I’d Known,” sharing key challenges and lessons from her first grant project management experience. In the tenth session, Yujin led “Looking Ahead to 2026 at CCADD,” presenting a vision for the center’s research trajectory in the coming year.  It also compiled target conferences for future submissions and concluded with a shared aspiration for deeper research in 2026.

Moreover, in the session, "AI 2027: Where we were, where we are, and where we will be", David went over the prospective report, "AI 2027," in which the authors made predictions on what will happen to the state of AI arms race between US and China. In addition to peeking into the future of AI, David emphasized the need for shifting gears toward using agentic AIs and understanding their inner workings by briefly discussing important developments in the field of agentic AI.

The most significant part of the workshop came in the closing talk, where Prof. Howard presented a paradigm shift from +AI to AI+. He contrasted a domain-first approach with an AI first approach and explaining how research strategy changes under an AI+ framework. He emphasized CCADD’s future direction toward AI-centered approach and proposed holding a “CCADD AI+ Conversion Meeting” in the early 2026 to brainstorm and define core research themes and strategies.

The workshop concluded with closing remarks from Prof. Howard, and everyone gathered for dinner. The 2025 CCADD Year-End Workshop provided members with an opportunity to exchange ideas, reflect on progress, and align on shared goals for the year ahead.

David Seung U Lee, a Ph.D. student at CCADD, and Seeun Park, an undergraduate researcher and the soon-to-be Master’s student at CCADD, received the Outstanding Presentation Awards at the 2025 Fall Conference of the Korean Society of Medical Informatics (KOSMI).

David presented his study titled "Improving Large Language Model-Based Drug-Drug Interaction Prediction Using Conformal Prediction." His research demonstrated that incorporating input features with coverage guarantees, verified through conformal prediction, significantly improves the performance of LLM-based DDI prediction in both in-context learning and fine-tuning settings.

Seeun Park, presented her study titled “Improving Synthetic Clinical Note Generation via Expert Prompting Reflecting Linguistic and Structural Characteristics.” Her research proposes a data augmentation framework that incorporates the knowledge of medical professionals into LLM-based prompting, coupled with a feedback-driven iterative generation loop. This approach enables the model to produce synthetic clinical notes that more closely reflect the characteristics of real-world clinical notes.

These awards highlight the growing importance of LLMs in the healthcare industry and recognizes the potential impact of our work in advancing AI-driven medical text generation.

CCADD members attended the 2025 Fall Conference of the Korean Society of Medical Informatics(KOSMI), held from November 23 to 24 at Songdo Convensia in Incheon. With the theme “Generative AI in Healthcare Systems: From Insight to Impact,” the conference showcased the latest developments, real-world applications, and future opportunities for generative AI in healthcare. Major sessions explored LLM evaluation, LLM-based clinical ation and validation, and AI-driven prediction of neurological disorders.

The conference featured keynote lectures from leading experts in Korea and Taiwan. Professor Sang-Hoon Jeon from Seoul National University Bundang Hospital discussed initiatives aimed at reducing global healthcare disparities, including the establishment of a Global Smart Hospital Network and the development of cloud-based platforms for clinician education and severe disease consultation. He emphasized that the key challenge is not merely how AI can reduce healthcare disparities, but how quickly high-quality medical services can reach those who are waiting for them. Professor Ming-Chin Lin from the College of Medicine at Taipei Medical University addressed the shared challenges facing both Korea and Taiwan—rapid population aging, declining birth rates, and increasing strain on healthcare professionals. He introduced Ambient Intelligence as the next evolution beyond ambient recording and traditional AI systems: a context-aware, ethically governed, sensor-integrated healthcare environment designed to support clinicians and empower patients.

More importantly, CCADD delivered five oral presentations.

David presented his work on “improving the performance of drug interaction prediction using conformal prediction”, which delved into a new method of selecting input for LLM-based prediction module using the statistical framework. 

Yujin presented her work on “Constructing a Domain-Specific Korean–English Parallel Corpus and Dictionary for Medical Translation Using a Large Language Model,” which aims to improve the reliability and consistency of LLM-based medical translation. By introducing a large-scale corpus construction framework, she provided foundational resources that can support future research in the field. During the session, she exchanged insights with reviewers and fellow researchers and explored ways to further expand and deepen the study.

Suhyun An presented her research on “Investigating LLM-based Reasoning and Training Strategies for automating causality assessment of adverse drug reactions”. Her study systematically explored optimal reasoning strategies and training methods to enable large language models to emulate the clinical decision-making process of medical experts.

Seoyoon Jang presented her work on "LLM-Based Extraction of Adverse Events from Real-World Clinical Notes", which leveraged open-source LLMs to build a privacy-preserving and robust framework capable of extracting adverse events from real-world clinical notes.

Seeun Park presented her work titled “Improving Synthetic Clinical Note Generation via Expert Prompting Reflecting Linguistic and Structural Characteristics”. Her research proposed a new synthetic data-augmentation framework that captures the characteristics of real-world clinical notes, demonstrating its potential to support large-scale, high-quality synthetic datasets for AI training.

Through this conference, CCADD members reaffirmed that their research aligns with the current interest in the generative AI, which will play a pivotal role in advancing the healthcare industry. The event strengthened our commitment to pursuing impactful research and contributing to the development of next-generation AI-driven healthcare systems.

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.

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.

Prof. Howard Lee spoke at a conference held by The Korean Society of Food, Drug and Cosmetics Regulatory Sciences, December 13, 2024, in the Hoam Faculty Club, Seoul National University. Prof. Lee discussed the current status and future perspectives as to the application of artificial intelligence technologies to clinical drug development. A newspaper article focused on the point that Prof. Lee emphasized at the Q&A session, where Prof. Lee stressed the establishment of the standards in order for AI to be more broadly accepted into the real-world practices of drug development, particularly for the clinical stage including post-marketing approval.