Longitudinal Clinical Observation of a Digital Twin Model for Blastocyst Evaluation in IVF Clinics
NCT07305480 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1
Last updated 2025-12-29
Summary
This study aims to develop and validate a non-image, multimodal digital twin model of the human blastocyst using fully de-identified clinical, laboratory, molecular, biochemical, and long-term follow-up data obtained during routine IVF treatment. The dataset includes parental clinical background, IVF cycle parameters, embryo morphology in text format, PGT-A results, secretome and exosomal biomarkers, endometrial receptivity profiles, pregnancy course, delivery outcomes, and child development data up to 3 years of age.
The purpose of this observational study is to create a longitudinal reference dataset linking embryo-level molecular and biochemical characteristics with clinical outcomes from implantation to early childhood. The digital twin model is intended to investigate predictors of implantation success, embryo viability, and early developmental trajectories without the use of images or videos. No investigational drugs or devices are used, and no procedures beyond standard clinical practice are added.
Conditions
- Implantation, Embryo
Interventions
- OTHER
-
Digital Twin Computational Modeling
Computational digital twin model that analyzes fully de-identified, non-image clinical, molecular, biochemical, and laboratory data from routine IVF care to evaluate embryo implantation potential. The model does not influence clinical decision-making and is used only for retrospective and prospective observational analysis.
Sponsors & Collaborators
-
Ukraine Association of Biobank
lead OTHER
Eligibility
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2023-01-02
- Primary Completion
- 2023-12-15
- Completion
- 2026-12-15
Countries
- Austria
Study Locations
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