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AI-Driven Embryo Selection Platform for Enhanced Implantation in IVF: A Phased Development and Randomized Clinical Trial

Award Number: R61HD123536
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/15/2026
PERIOD OF PERFORMANCE END DATE: 08/31/2028

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AI-Driven Embryo Selection Platform for Enhanced Implantation in IVF: A Phased Development and Randomized Clinical Trial - Project Summary / Abstract Infertility affects millions of couples worldwide, yet implantation failure remains a primary cause of unsuccessful in vitro fertilization (IVF) cycles. Current embryo selection relies heavily on manual visual grading by embryologists, a subjective process prone to inter-observer variability and suboptimal outcomes. While Artificial Intelligence (AI) promises to standardize assessment, existing systems are often limited by narrow training datasets and lack rigorous prospective validation. This project will establish and validate next-generation AI foundation models for embryo selection that are robust, interpretable, and clinically proven. Building on our team's development of FEMI, a multimodal foundation model trained on over 18 million embryo images, we aim to bridge the gap between computational innovation and clinical utility. In the R61 phase, we will train and benchmark advanced AI architectures using harmonized time-lapse datasets from different IVF centers to ensure generalizability. Crucially, we will apply advanced causal inference methods to retrospectively evaluate whether AI-guided selection would have altered clinical decision-making to improve implantation outcomes, providing the first causal validation of such models in reproductive medicine. In the R33 phase, contingent on R61 success, the best-performing AI model will be deployed in a multicenter randomized controlled trial (RCT). This trial will prospectively compare AI-guided embryo selection against standard morphological grading to determine if AI-driven selection results in statistically superior implantation and pregnancy rates. By integrating foundation AI modeling, causal inference, and prospective clinical trials, this proposal will deliver a regulatory-ready platform for embryo selection. This work directly advances the NICHD mission to transform infertility care through responsible, data-driven innovation.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $472,674 )
2026	2026	WEILL MEDICAL COLLEGE OF CORNELL UNIVERSITY	575 LEXINGTON AVE FL 9	NEW YORK	NY	10022	NEW YORK	USA	Child Health and Human Development Extramural Research	000	1	9/11/2026	NEW	$472,674
														Subtotal = $472,674

Grand Total All Awards = $472,674

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AI-Driven Embryo Selection Platform for Enhanced Implantation in IVF: A Phased Development and Randomized Clinical Trial

Award Number: R61HD123536

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/15/2026

PERIOD OF PERFORMANCE END DATE: 08/31/2028

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