Qure.ai Partners with GARBH-INi to Deploy AI-Enabled Ultrasound Reporting for Preterm Birth Risk Stratification

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Qure.ai Partners with GARBH-INi to Deploy AI-Enabled Ultrasound Reporting for Preterm Birth Risk Stratification

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A government-backed initiative in India called the GARBH-INi programme is developing AI-powered tools targeting preterm births, a leading cause of neonatal death. The programme enrolled 12,000 pregnant women to build one of South Asias largest pregnancy datasets, generating more than 1.6 million biospecimens and over a million ultrasound images, serving as the data foundation for training AI models that support personalised risk prediction tailored to the Indian population. Dr Jitendra Singh, Science and Technology Minister of State, emphasised Indias significant share of the global burden of preterm births, highlighting the need for locally developed solutions tailored to the local population. Early outcomes include developing AI-based pregnancy dating models, microbiome-based predictors of preterm birth, rapid diagnostic tools, and genetic markers aimed at enabling earlier and more accurate risk assessment. The programme also established a national biorepository and a data sharing platform called GARBH-INi-DRISHTI, supporting broader research access and collaboration. Partnerships have been formalised to translate research into clinical tools, including technology transfer of microbiome-based biotherapeutics to Sundyota Numandis Probioceuticals and agreements with Womens health startup Doto Health and medical imaging AI company Qure.ai to develop AI-enabled ultrasound reporting and risk stratification systems. The next phase will focus on deploying and scaling the predictive models and platforms developed.

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