Shinjini Bhatnagar
Shinjini Bhatnagar is Professor of Eminence and Head of Maternal and Child Health Research at the Translational Health Science and Technology Institute (THSTI), Faridabad. A paediatric gastroenterologist and clinical scientist, she is dedicated to advancing child and maternal health in low-resource settings. At THSTI, she leads large multidisciplinary programs investigating vaccine responsiveness, fetal growth restriction, and neonatal infections, while developing affordable diagnostics for childhood diseases. During her distinguished 25-year tenure at the All India Institute of Medical Sciences (AIIMS), New Delhi, she pioneered evidence-based interventions including protocols for persistent diarrhoea, low-osmolarity oral rehydration salts, and zinc supplementation. Elected Fellow of India’s three national science academies and a WHO advisor on child diarrhoeal diseases, she continues to shape national and global health policy and practice.
Session 1D: Special Lecture
Chairperson: Satish K Gupta, Gurgaon
From discovery to delivery: Translating science to improve maternal and child health
Advanced scientific methods have accelerated discovery with immense potential to transform clinical practice and public health, but their true impact emerges only when guided by societal needs. India bears a high burden of preterm birth and adverse pregnancy outcomes, driven by biological, environmental, and socio-economic factors. Launched in 2015, GARBH-Ini (Interdisciplinary Group for Advanced Research on Birth Outcomes – DBT India Initiative) integrates clinical epidemiology, biotechnology, and data science to improve pregnancy outcomes. As DBT India’s flagship longitudinal cohort, it has collected multidimensional data from over 12,000 women across trimesters in North India. The programme has identified biomarkers, genetic panels, and vaginal microbiome-based assays to predict preterm birth, and developed a microbial consortia now translated into a nutraceutical product. AI-enabled ultrasound models, multimodal risk-prediction algorithms, and point-of-care tools are advancing clinical validation. The GARBH-Ini DRISHTI repository serves as a national resource, exemplifying how multidisciplinary, socially aligned science can translate discovery into scalable solutions for maternal and child health.