Modern biological high-throughput technologies have generated a data deluge—from which low and middle-incomes countries (LMICs) have not yet fully benefited. These technologies generate methodologically and biologically distinct omics data types (e.g., genomics, proteomics, metabolomics and most recently exposomics)—each of which imparts different but complementary information. New insight from these omics data can deepen our understanding of the fundamental biology of maternal and newborn health vulnerabilities, and contribute to the development of interventions that promote healthy pregnancies and the birth of health babies in the developing world. The Bill and Melinda Gates Foundation has funded two large-scale, biomedical studies (MISAME-III and DenBalo, both coordinated by UGent) designed to explore the pathways that drive prenatal and fetal development and infant growth. We request an additional fund from FWO for the FasOmics project, a integration initiative that will concatenate multi-omics data from MISAME-III/DenBalo into a single data matrix, for a subsequent, systematic analysis. Our approach is unbiased and hypothesis-generating, and uses machine learning and artificial intelligence methods, with a specific emphasis on epidemiological outcomes. The FasOmics project will reveal new biological insights not found in any dataset analyzed in isolation—and will serve as an evidence-base for the development of interventions against adverse perinatal outcomes in LMICs.