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Home | Hyderabad | Uoh Gets Rs 4 98 Crore Icmr Grant For Ai Based Pcos Research

UoH gets Rs 4.98 crore ICMR grant for AI-based PCOS research

Researchers from the University of Hyderabad have received a Rs 4.98-crore ICMR grant to develop an AI-based, non-invasive blood test for PCOS. The project will study molecular signatures in blood cells and aims to create an affordable diagnostic platform.

By Telangana Today
Published Date - 17 September 2026, 05:40 PM
UoH gets Rs 4.98 crore ICMR grant for AI-based PCOS research
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Hyderabad: The University of Hyderabad (UoH) on Thursday announced that a multidisciplinary team of researchers from its School of Life Sciences has been awarded an Rs 4.98 crore research grant from the Indian Council of Medical Research (ICMR).

Sanctioned under the ICMR Intermediate Extramural Grants (ICMR Nischayak Anveshan Extramural Grants) 2026 call, the grant is for the project titled “Multi-Modal Artificial Intelligence Integration of Systemic and Follicular Single-Cell Transcriptomics for Non-Invasive PCOS Theranostics, Molecular Endotyping, and Early Discovery”. The project aims to leverage advanced genomics and artificial intelligence to create a non-invasive, affordable blood test for Polycystic Ovary Syndrome (PCOS)—a leading cause of infertility affecting millions of women across India.


PCOS is a complex endocrine disorder that disproportionately affects Indian women of reproductive age, often manifesting with heightened severity due to underlying insulin resistance.

The UoH-led project addresses this challenge by analysing circulating immune cells in peripheral blood, which carry distinct molecular signatures reflective of the follicular environment. By accurately decoding these signals using machine learning models, the research team aims to replace invasive evaluations with a simple routine blood sample.

The ultimate objective is to deliver a patented, made-in-India diagnostic platform targeted at under Rs 2,000. This kit will classify patients into distinct molecular PCOS endotypes, enabling clinicians to predict IVF outcomes before initiating expensive treatment regimens.

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