TruFERT: a new AI-enabled tool to tailor endometrial readiness in frozen embryo transfer
Official title: Quantitative Assessment of Free Steroid Hormones to Characterize Endometrial Receptivity Towards Improving Pregnancy Outcomes in Frozen Embryo Transfer (FET) Cycles
Funded at Brigham and Women's Hospital · NIH-11455938 · Data updated 2026-11-12
A patient-friendly platform using AI and hormone data to better time frozen embryo transfers and improve chances of implantation.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | September 10, 2026 |
| Project end | August 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $477,694 |
| NIH project number | 1R61HD123436-01 |
| Project ID | NIH-11455938 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals undergoing frozen embryo transfer who may benefit from optimized timing based on endometrial receptivity and hormone profiles.
✕Less likely to help
Patients not undergoing FET or those not using AI-driven decision support may see limited direct benefit.
What this research studies
This project aims to create TruFERT™, a noninvasive diagnostic system that uses AI to combine hormone measurements with endometrial imaging and clinical data to identify a personalized window for embryo transfer. In the R61 phase, researchers will analyze archived samples from hundreds of prior FET cycles to build a predictive model of endometrial receptivity. The goal is a scalable clinical decision support tool that clinicians can use to optimize timing and improve pregnancy outcomes for people undergoing IVF with frozen embryos.
Why it matters
Potential benefit: If successful, TruFERT™ could help more patients achieve successful pregnancies by better timing embryo transfers.
How similar studies have gone: Previous work shows that endometrial receptivity is a key predictor of implantation, and AI approaches are increasingly used to integrate complex data, though this exact platform is novel.
Where this research is happening
-
Brigham and Women's Hospital
Boston, United States Active
Researchers
- Principal investigator: Bhasin, Shalender — Brigham and Women's Hospital
- Study coordinator: Bhasin, Shalender
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.