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India made a major step forward in biomedical research today with the opening of its first Ferret Research Facility, the launch of the GARBH-INi-DRISHTI data repository.

  • The newly opened THSTI Ferret Research Facility is a state-of-the-art facility with top biosafety and research standards.

About GARBH-INi-DRISHTI

  • It is the Department of Biotechnology (DBT)’s Data Repository and Information Sharing Hub at Translational Health Science and Technology Institute (THSTI) in the NCR Biotech Science Cluster, Faridabad, Haryana.
  • The facility will focus on vaccine development, therapeutic testing, and research on emerging infectious diseases.
  • It strengthens India’s pandemic preparedness and boosts its global scientific position.
  • It empowers researchers to conduct transformative research aimed at improving maternal and neonatal health outcomes.
  • This platform is developed under the GARBH-INi program and provides access to an unprecedented wealth of clinical data, images, and biospecimens collected from over 12,000 pregnant women, newborns, and postpartum mothers.

What is GARBH-Ini Program

  • GARBH-ini is a mission to promote maternal and child health and develop prediction tools for pre-term birth.
  • The programme focuses on finding solutions for better birth outcomes utilizing a multi-pronged approach of integrating clinical epidemiology, multi-omics biomarkers and AI-driven tools for personalized predictions
  • Objectives of Program
    • Gaining a detailed understanding of preterm birth and fetal growth restriction through pregnancy data to guide clinical practice and policy.
    • Developing AI tools using clinical and ultrasound images for personalized birth outcome predictions.
    • Identifying multi-omics biomarkers to create personalized clinical decision-making tools.
    • Discovering potential biomarkers to improve understanding of disease mechanisms and help in diagnostics and treatments.
    • Integrating clinical, epidemiological, imaging, and biological data to create a dynamic prediction algorithm for preterm birth decision-making.
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