Centre for Quantitative Medicine

We lead pioneering research in Data Science, AI, statistical methodology, computational omics, and systems biology. Our work drives fundamental scientific discovery and accelerates translational impact in areas such as drug discovery, clinical innovation, and healthcare solutions.

We collaborate closely with partners across Duke-NUS, the SingHealth Duke-NUS Academic Medical Centre, national institutions, and global research leaders - including Duke University - to address complex biomedical challenges and amplify scientific impact.

We provide a unified, end-to-end biostatistics and data analytics ecosystem that supports genetics and genomics, multi-omics integration, clinical data analysis, AI/ML modelling, health informatics, and more.
Our integrated approach enables:

• Holistic data integration across omics and clinical domains
• Streamlined analytical workflows and reduced redundancy
• Advanced AI, machine learning, and computational biology methodologies
• Interdisciplinary collaboration among scientists, clinicians, and data experts
• Scalable, flexible support for studies from exploratory research to large clinical cohorts
• High-quality, reproducible results through standardized pipelines

We cultivate the next generation of biomedical data science leaders through a cohesive educational ecosystem spanning the QBM PhD and forthcoming Data Science MSc programmes.
Our training framework offers:

• A comprehensive, harmonized curriculum covering core and advanced quantitative biomedical sciences
• Flexible learning pathways and cross-training opportunities across health informatics, computational biology, and statistical modelling
• Access to diverse faculty expertise and collaborative, interdisciplinary teaching
• Streamlined administration, advising, and resource sharing for an enhanced student experience