Akshaya V. Annapragada

Akshaya Annapragada studies a signal that standard mutation searches can miss: the way cell-free DNA breaks apart in the bloodstream. In a 2025 ovarian-cancer study of 591 women, she was an equal first author on a machine-learning fragmentomics approach that reported greater than 99% specificity. Sensitivity was stage-dependent — 72% for stage I, 69% for stage II, 87% for stage III and 100% for stage IV in the reported dataset — a profile that makes both the promise and the remaining gap visible.

Her research record inside the window did not stop with one cancer type. She contributed to 2025 work on cell-free DNA in brain cancer and became first author of a 2026 translational paper examining fragmentome patterns for disease classification. Across these studies, the recurring contribution is methodological: extracting a richer biological signature from DNA fragments and testing how well it separates clinically relevant groups.

The work is retrospective and case-control rather than a prospective screening programme. High specificity in a study cohort does not establish population-level performance, and no test described here is an approved screening product. Annapragada's standing rests on the quality and continuity of the translational research, her visible authorship and the importance of solving the false-positive problem in early detection.