India developing indigenous AI tools for early prediction of preterm births: MoS

New Delhi — India is advancing efforts to tackle preterm births through homegrown artificial intelligence solutions, Union Minister of State for Science and Technology Jitendra Singh said on Monday.

Speaking at an event, Singh highlighted the GARBH-INi initiative, one of South Asia’s largest pregnancy cohort studies, which has enrolled around 12,000 women. The programme is focused on developing AI-driven tools tailored specifically to Indian populations, including pregnancy dating models, microbiome-based predictors, rapid diagnostic kits, and genetic markers for early risk detection.

He noted that such innovations could significantly improve maternal and child health outcomes, especially as preterm births remain a leading cause of neonatal deaths and long-term health complications.

The study has also built a massive research repository, comprising over 1.6 million biospecimens and more than one million ultrasound images, providing a strong foundation for advanced scientific analysis.

Emphasising the urgency, Singh pointed out that India bears a substantial share of the global burden of preterm births, making locally relevant solutions critical. The initiative integrates clinical epidemiology, multi-omics biomarkers, and AI to enable more personalised and accurate predictions.

The programme has further established a national biorepository along with the GARBH-INi-DRISHTI data-sharing platform, allowing researchers broader access to valuable datasets and contributing to global scientific work.

During the event, several partnerships and technology transfer agreements were formalised, including those related to microbiome-based biotherapeutics. Singh added that initiatives like GARBH-INi reflect a broader national mission to link scientific innovation with long-term development goals.

Highlighting India’s progress in the sector, he said the country’s bioeconomy has grown significantly over the past decade and is increasingly being recognised for its strengths in preventive and primary healthcare driven by indigenous innovation.

Meanwhile, V. K. Paul, Member of NITI Aayog, stressed that the next phase of the programme should focus on effectively utilising the tools and predictive models already developed.

With inputs from IANS