Implantation, EmbryoIVFDTNCT07305480
Longitudinal Clinical Observation of a Digital Twin Model for Blastocyst Evaluation in IVF Clinics
An observational study of Implantation, Embryo, run by Ukraine Association of Biobank at 1 site in Austria.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Implantation, Embryo
- What is being tested?
- Digital Twin Computational Modeling
- How many people
- 1 participants
- Where
- 1 siteAustria
- Study dates
- 2 Jan 2023to 15 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
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.
Who may be able to join
- 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.
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- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
Austria1 site
Ukrainian Association of Biobanks Austria - Digital Twin Lab
Graz, 8010
About this study
Official title: Longitudinal Observational Study for Developing and Validating a Digital Twin Model of Human Blastocyst Development, Implantation Potential, and Pregnancy Outcomes Using Fully De-Identified, Multimodal IVF Clinical and Molecular Data
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.
Read the detailed description
This observational study collects and integrates multimodal, non-image data from routine IVF cycles to construct digital twin models of human blastocysts. The dataset includes synchronized molecular, cellular, biochemical, and clinical parameters describing both the embryo and the maternal environment during implantation and early pregnancy. All information is fully de-identified and obtained as part of standard clinical care.
Parental and Clinical Background
The dataset incorporates:
demographic factors, reproductive history, and relevant risk factors;
karyotype results, thrombophilia and autoimmune screening;
sperm DNA fragmentation indices;
ovarian stimulation parameters and hormonal dynamics throughout the IVF cycle.
IVF Laboratory Data
Non-image embryologic information includes:
oocyte maturity and fertilization method (e.g., ICSI);
early cleavage development documented in descriptive text format (no images or videos);
blastocyst grading;
preimplantation genetic testing for aneuploidy (PGT-A), including ploidy status and mosaicism.
Molecular and Secretome Data
Embryo- and culture-media-associated biomarkers include:
cytokines, growth factors, LIF, and metabolic indicators in spent media;
exosomal microRNA signatures linked to implantation potential;
transcriptomic and methylation profiles of trophectoderm samples when available.
Endometrial and Immune Environment
Maternal environment assessment includes:
transcriptomic profiling of the endometrial receptivity window (ERA-like signatures);
uterine immune parameters such as uNK cell activity and T-regulatory balance.
Pregnancy, Delivery, and Child Follow-Up
Collected follow-up information includes:
β-hCG kinetics, early ultrasound development, and pregnancy complications;
delivery outcomes and newborn characteristics;
longitudinal developmental assessments of the child up to 3 years of age.
Study Objectives
To construct digital twin representations of individual blastocysts by integrating multi-omics and clinical parameters obtained during IVF.
To identify non-invasive biomarkers of implantation success and embryo viability.
To analyze associations between early embryo molecular profiles and neonatal or early childhood developmental outcomes.
Study Design
This is a non-interventional, observational study. All data are obtained retrospectively and/or prospectively from routine clinical practice in IVF clinics. No experimental procedures, investigational drugs, or investigational devices are introduced. Participation involves only the use of fully de-identified clinical, laboratory, and follow-up data for research purposes. Parents provide informed consent for use of de-identified information.
The study is not conducted under an IND or IDE, and it does not involve FDA-regulated products.
Significance
The resulting longitudinal dataset will support the development of AI-based digital twin models, facilitate biomarker discovery, and advance precision reproductive medicine. These models aim to predict blastocyst competence, implantation potential, and early developmental trajectories using non-image, multimodal clinical and molecular data.
- Conditions
- Implantation, Embryo
- Being tested
- Digital Twin Computational Modeling
- Keywords
- IVF, Digital Twin, Embryo selection, Multi-omics, Pregnancy outcomes, AI modeling
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Digital Twin Computational ModelingOther
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Other: Digital Twin Computational Modeling |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: From embryo transfer (Day 0) to confirmation of clinical pregnancy (up to 12 weeks of gestation).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Dec 2025
- Study start2 Jan 2023
- Primary completion15 Dec 2023
- Study completion15 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Implantation, EmbryoStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 1 participants (actual)
Sponsor and investigators
- Lead sponsor
- Ukraine Association of Biobank
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07305480
- Sponsor's protocol ID
- IVFDT-LONGOBS-001
- Other IDs
- UABA-IVF-DT-001
- Acronym
- IVFDT
- Status last verified
- Dec 2025
- First submitted
- 12 Dec 2025
- Last updated
- 29 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Longitudinal Observational Study for Developing and Validating a Digital Twin Model of Human Blastocyst Development, Implantation Potential, and Pregnancy Outcomes Using Fully De-Identified, Multimodal IVF Clinical and Molecular Data
- ClinicalTrials.gov ID
- NCT07305480
- Acronym / sponsor ID
- IVFDT / IVFDT-LONGOBS-001
- Conditions
- Implantation, Embryo
- Keywords
- IVF, Digital Twin, Embryo selection, Multi-omics, Pregnancy outcomes, AI modeling
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1 participants (actual)
- Lead sponsor
- Ukraine Association of BiobankUniversity, hospital or other
- Study start
- 2 Jan 2023 (actual)
- Primary completion
- 15 Dec 2023 (actual)
- Study completion
- 15 Dec 2026 (estimated)
- First posted
- 26 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This observational study collects and integrates multimodal, non-image data from routine IVF cycles to construct digital twin models of human blastocysts. The dataset includes synchronized molecular, cellular, biochemical, and clinical parameters describing both the embryo and the maternal environment during implantation and early pregnancy. All information is fully de-identified and obtained as part of standard clinical care.
Parental and Clinical Background
The dataset incorporates:
demographic factors, reproductive history, and relevant risk factors;
karyotype results, thrombophilia and autoimmune screening;
sperm DNA fragmentation indices;
ovarian stimulation parameters and hormonal dynamics throughout the IVF cycle.
IVF Laboratory Data
Non-image embryologic information includes:
oocyte maturity and fertilization method (e.g., ICSI);
early cleavage development documented in descriptive text format (no images or videos);
blastocyst grading;
preimplantation genetic testing for aneuploidy (PGT-A), including ploidy status and mosaicism.
Molecular and Secretome Data
Embryo- and culture-media-associated biomarkers include:
cytokines, growth factors, LIF, and metabolic indicators in spent media;
exosomal microRNA signatures linked to implantation potential;
transcriptomic and methylation profiles of trophectoderm samples when available.
Endometrial and Immune Environment
Maternal environment assessment includes:
transcriptomic profiling of the endometrial receptivity window (ERA-like signatures);
uterine immune parameters such as uNK cell activity and T-regulatory balance.
Pregnancy, Delivery, and Child Follow-Up
Collected follow-up information includes:
β-hCG kinetics, early ultrasound development, and pregnancy complications;
delivery outcomes and newborn characteristics;
longitudinal developmental assessments of the child up to 3 years of age.
Study Objectives
To construct digital twin representations of individual blastocysts by integrating multi-omics and clinical parameters obtained during IVF.
To identify non-invasive biomarkers of implantation success and embryo viability.
To analyze associations between early embryo molecular profiles and neonatal or early childhood developmental outcomes.
Study Design
This is a non-interventional, observational study. All data are obtained retrospectively and/or prospectively from routine clinical practice in IVF clinics. No experimental procedures, investigational drugs, or investigational devices are introduced. Participation involves only the use of fully de-identified clinical, laboratory, and follow-up data for research purposes. Parents provide informed consent for use of de-identified information.
The study is not conducted under an IND or IDE, and it does not involve FDA-regulated products.
Significance
The resulting longitudinal dataset will support the development of AI-based digital twin models, facilitate biomarker discovery, and advance precision reproductive medicine. These models aim to predict blastocyst competence, implantation potential, and early developmental trajectories using non-image, multimodal clinical and molecular data.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Cohort: IVF Patients Monitored With Digital Twin Embryo Evaluation | – | Other: Digital Twin Computational ModelingThis 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. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- 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.
Key inclusion criteria (10 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Digital Twin Computational ModelingComputational 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. | Other | Cohort: IVF Patients Monitored With Digital Twin Embryo Evaluation |
Primary outcome
Accuracy of Digital Twin Model in Predicting Embryo Implantation
Time frame: From embryo transfer (Day 0) to confirmation of clinical pregnancy (up to 12 weeks of gestation).
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Dec 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Implantation, Embryo, run by Ukraine Association of Biobank at 1 site in Austria.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 10 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 29 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Austria. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of Digital Twin Model in Predicting Embryo Implantation (time frame: From embryo transfer (Day 0) to confirmation of clinical pregnancy (up to 12 weeks of gestation).). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Dec 2025.