Data is only as valuable as the decisions it enables, which is why the Biostatistics 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. 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.