Research Interest

 Our laboratory is dedicated to advancing drug development and precision medicine through the convergence of artificial intelligence and clinical pharmacology. By integrating population PK/PD modeling and quantitative systems pharmacology (QSP) with cutting-edge machine learning and large language models, we build AI-driven platforms that predict drug behavior, tumor dynamics, and patient outcomes at the individual level. We further harness multimodal omics data, knowledge graphs, and retrieval-augmented generation (RAG) to develop clinically actionable decision-support systems. A central ambition of our lab is to construct digital patient twins computational representations of individual patients that simulate biological characteristics and treatment responses in silico ultimately enabling AI to contribute across the full continuum of drug development, from preclinical modeling to personalized pharmacotherapy in real-world clinical settings. 

AI-Driven PK/PD Modeling & Clinical Platform 

Quantitative Systems Pharmacology (QSP) & Tumor Dynamics 

Biomedical RAG & AI-Powered Clinical Decision Support 

Our laboratory is equipped with a high-performance computing infrastructure purpose-built for large-scale AI research in clinical pharmacology. The computing environment includes NVIDIA RTX 5090, NVIDIA A6000, and NVIDIA B200 GPUs, supporting a wide range of workloads from deep learning model training to large-scale pharmacological simulation. In addition, we operate RNGD NPU, enabling cutting-edge research on NPU-optimized inference for clinical and omics-based RAG systems. This infrastructure positions our lab at the forefront of next-generation AI accelerator research in the biomedical domain.