Human health is affected by many different factors. Through careful study of these components, we seek to advance our understanding of Human Development. Major themes include women’s health, paediatric health, metabolic health, and neurodevelopmental health.

Our clinician-scientists, biologists, and statisticians work together to identify the associations and causal relationships between clinical phenotypes and developmental outcomes, upon which real-world change can be moulded. We have since made strides towards our translational objectives, such as updating paediatric clinical imaging methods so that infant MRI can now be carried out without sedation. Such achievements have sparked interest from industry partners, expanded research capacity in complementary domains, and extended collaborative clinical research through participation in developmental cohorts.

Our cornerstone development cohort is the longitudinal study, GUSTO, which aims to provide insights into how conditions in pregnancy and early childhood influence the health and development of women and children.

Find out more about our researchers with the Human Development programme.

Singapore’s economic growth is increasingly knowledge-based, relying on brain health across the population as the foundation for human capital. The challenge is to promote brain health across society, which demands studies of brain development and function across diverse cultural and socio-economic contexts. Our Translational Neurosciences initiative will pioneer the integration of neuroscience into Singaporean society by targeting determinants of individual differences in brain health across the population. We will leverage advances in neuroscience to address major public health challenges facing Singapore’s society.

Find out more about our researchers with the Translational Neurosciences programme.

Data is only as valuable as the decisions it enables, which is why the Biostatistics and Bioinformatics programme is a cornerstone of the work we do at SICS. Through the application of cutting-edge epidemiologic and biostatistical methods to complex data acquired from clinical and population health projects, we are able to develop a deeper understanding of maternal, child, and adolescent health. Some of these methods include longitudinal causal inference approaches to investigating developmental mechanisms and estimating potential benefits of early life interventions, and principled consideration of machine learning algorithms for developing and testing prediction models for maternal and child outcomes. 

Closely integrated with the Biostatistics and Data Management teams, as well as with multiple Singapore and international collaborative partners, the Bioinformatics Core integrates expertise in computer science with biology and mathematics to support analytics with large and/or multi-dimensional data. Developing capacity in knowledge transfer with modular bioinformatic tutorials targeting researchers across the basic and health sciences, the Core comprises pipelines and advanced, biologically informed analytics for genomic, epigenomic, transcriptomic and metabolic data sets; it also includes capacity in multiple Artificial Intelligence approaches. Notable projects include simulating effects of early life interventions on child adiposity, epigenetic mechanisms on assisted reproductive technology and infertility on child health, and environmental exposures in reproductive and child health.

Find out more about our researchers with the Biostatistics and Bioinformatics programme.