Union Minister of State (Independent Charge) for Science and Technology, Dr Jitendra Singh said that India's largest pregnancy cohort study on 12,000 women under the GARBH-INi initiative is aimed at solving the problem of preterm births indigenously. The aim is to develop an artificial intelligence (AI)-based solution. Premature birth is one of the leading causes of neonatal mortality and morbidity in adulthood.
Dr Jitendra Singh was addressing an event titled "Dissemination of Findings and Outcomes of GARBH-INi (Interdisciplinary Group for Advanced Research on Birth Outcomes)" at India Habitat Centre in New Delhi. The programme is an initiative of the Department of Biotechnology.
The Minister said that around 12,000 pregnant women have been successfully enrolled under this initiative, creating one of the largest pregnancy cohorts in South Asia. The programme has generated a vast repository of over 1.6 million well-classified bio-samples and more than one million ultrasound images, creating a strong foundation for advanced research.
Dr Jitendra Singh said the outcomes of the programme include the development of AI-based pregnancy dating models specifically tailored for the Indian population, identification of microbiome-based indicators of preterm birth, rapid diagnostic tools, and identification of genetic markers for early risk assessment.
He also said that such indigenous solutions are extremely important for improving maternal and child health outcomes in the country.
The Minister released a compendium documenting the key learnings and outcomes of the GARBH-INi programme. He said that the initiative has also established the National Bio-Repository and the GARBH-INi-DRISHTI data-sharing platform, enabling wider access for the research community and contributing to global scientific publications.
On the occasion, key partnerships and technology transfer programmes were formalised- The transfer of microbiome-based biotherapeutics technology to GARBH-INi-AnandiMaa initiative from DOTO Health; and signing of Letters of Intent with DOTO Health and Qure.ai Technologies for AI-enabled ultrasound reporting systems and risk stratification platforms under the GARBH-INi-AnandiMaa initiative.
