Longitudinal Clinical Observation of a Digital Twin Model for Blastocyst Evaluation in IVF Clinics

NCT07305480 | Active Not Recruiting

• 2 other identifiers: IVFDT-LONGOBS-001UABA-IVF-DT-001
• Study Type: observational
• Target: 1
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

IVF; Digital Twin; Embryo selection; Multi-omics; Pregnancy outcomes; AI modeling

Outcome Measures

Primary Outcomes (1)

• Accuracy of Digital Twin Model in Predicting Embryo Implantation

  Evaluation of the predictive performance of the digital twin model for embryo implantation outcomes based on integrated multi-omics, morphokinetic, and clinical data. The accuracy will be measured by AUC, sensitivity, specificity, and calibration metrics against real clinical implantation outcomes.

  From embryo transfer (Day 0) to confirmation of clinical pregnancy (up to 12 weeks of gestation).

Study Arms (1)

Cohort: IVF Patients Monitored With Digital Twin Embryo Evaluation

This cohort includes patients undergoing in-vitro fertilization (IVF) whose embryos are evaluated using the Digital Twin model for blastocyst quality and implantation prediction. No clinical intervention is performed. The study collects multi-omics, morphological, and clinical data to monitor implantation success, pregnancy progression, and neonatal outcomes up to 3 years after birth.

Other: Digital Twin Computational Modeling

Interventions

Digital Twin Computational Modeling OTHER

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.

Cohort: IVF Patients Monitored With Digital Twin Embryo Evaluation

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population includes women undergoing in vitro fertilization (IVF) treatment whose embryo-related clinical, laboratory, molecular, and biochemical data are collected as part of routine clinical care. The dataset consists of fully de-identified non-image embryo development information, including text-based morphological descriptions, PGT-A results, secretome and exosomal biomarkers, endometrial receptivity profiles, and IVF cycle parameters required to construct and validate a multimodal digital twin model of blastocyst implantation potential. Participants represent typical reproductive-age IVF patients receiving standard ovarian stimulation, oocyte retrieval, embryo culture, assessment, and embryo transfer procedures. No experimental interventions, investigational drugs, or investigational devices are used. Only retrospective and/or prospectively collected routine clinical data are analyzed for computational model development.

You may qualify if:

• Women undergoing in vitro fertilization (IVF) treatment at participating fertility clinics.
• Availability of non-image embryo development data.
• Availability of text-based morphological embryo descriptions.
• Availability of PGT-A results.
• Availability of secretome and exosomal biomarker data.
• Availability of molecular and biochemical data collected during routine clinical care.
• Availability of IVF cycle parameters collected during routine clinical workflow.
• Embryos evaluated according to standard clinic protocols with documented implantation outcomes.
• Age of the oocyte provider between 20 and 42 years.
• Signed informed consent allowing use of fully de-identified clinical, laboratory, molecular, and follow-up data.

You may not qualify if:

• Embryos lacking sufficient non-image developmental data required for digital twin generation or implantation outcome assessment.
• Use of donor oocytes or donor embryos when linkage with required clinical or laboratory metadata is not possible.
• Cases in which implantation outcome cannot be confirmed.
• Presence of severe uterine abnormalities prior to embryo transfer that may affect implantation reliability.
• Withdrawal of consent for use of anonymized clinical, laboratory, or follow-up data.

Sponsors & Collaborators

• Ukraine Association of Biobank: lead

Study Sites (1)

Ukrainian Association of Biobanks Austria - Digital Twin Lab

Graz, 8010, Austria

Location

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 12, 2025
• First Posted: December 26, 2025
• Study Start: January 2, 2023
• Primary Completion: December 15, 2023
• Study Completion (Estimated): December 15, 2026
• Last Updated: December 29, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share

Locations

AU (1)