연구진 소개

Prof. Yu is interested in various topics related to personalized drug therapy, early phase clinical trials, clinical drug development, and clinical studies involving decentralized elements. He leads or supports many research projects every year, spanning various kinds of industry-sponsored clinical trials and government-funded regulatory initiatives. Dr. Yu is also giving many consultations regarding clinical drug development.

Dr. Lee has expertise in pharmacometrics, clinical trials design, drug development science, and drug regulations (in South Korea and the US). Dr. Lee’s research areas include first-in-human studies of new drugs, including biologics, AMS-enabled microdosing and microtracer studies, pharmacokinetic-pharmacodynamic modeling, and regulatory issues related to biosimilar products. Recently, Dr. Lee has expanded his research field to the application of artificial intelligence (AI) to clinical drug development. For example, Dr. Lee spearheaded the application of AI technology to improve the efficiency of patient enrollment into clinical trials. Based on this technology, Dr. Lee founded a tech startup called PMATCH in early 2022, which has developed Battery, a smart phone application that recommends individualized health supplements based on AI, and PillTalk, an AI-based drug interaction prediction app. Moreover, Dr. Lee built a natural language processing (NLP) model that extracts information on drug-drug interaction and adverse drug reactions from clinical notes.

Professor Joo-Youn Cho conducts research aimed at elucidating disease pathophysiology, discovering novel biomarkers, and advancing precision medicine through mass spectrometry-based metabolomics, lipidomics, and pharmacometabolomics. His primary research interests include the prediction of drug response, immunometabolism, metabolomics-driven investigation of infectious and chronic diseases, and the molecular characterization of tissue microenvironments using spatial metabolomics. In recent years, his research has focused on the integrated analysis of metabolomic and lipidomic alterations in blood, tissues, and various biological specimens using LC–MS/MS and Mass Spectrometry Imaging (MSI) technologies. Through these approaches, he seeks to identify disease-specific biomarkers and novel therapeutic targets. He is also actively engaged in interdisciplinary collaborations with basic medical scientists to investigate metabolic heterogeneity and immune responses within tumor microenvironments, neuroinflammatory conditions, viral infections, and tissue injury, incorporating advanced spatial omics technologies. In addition, Professor Cho integrates pharmacogenomics and metabolomics to predict individual drug responses and develop personalized therapeutic strategies. Leveraging extensive national and international clinical and translational research networks, he is pursuing the development of innovative biomarkers and diagnostic platforms to facilitate the implementation of precision medicine. Ultimately, his research aims to contribute to disease diagnosis, prognostic assessment, therapeutic response monitoring, and the discovery of novel therapeutic targets through metabolomics-based approaches.

Technology and Regulatory Research in Response to Evolving Clinical Trial Environments We are investigating emerging technologies being introduced into clinical trials, including blockchain, wearable devices, and the utilization of local medical institutions, and are conducting research to explore their feasibility within the domestic setting to accelerate real-world adoption. In parallel, we are expanding the breadth of clinical pharmacology through regulatory research that addresses the shifting landscape of clinical trials. We are also undertaking research aimed at developing and implementing clinical trial IT infrastructure, such as remote monitoring systems, to enhance the competitiveness of clinical trials in Korea. Early-Phase Clinical Trials for New Drug Development Early-phase clinical trials for new drug development represent a pivotal process that determines the direction of subsequent clinical development, requiring in-depth investigation of safety and tolerability as well as pharmacokinetics and pharmacodynamics. We design first-in-human clinical trials based on nonclinical findings and contribute to the formulation of clinical development strategies grounded in the resulting data. More recently, we have also been conducting research that applies artificial intelligence to predict clinical trial outcomes.