Digital twin could revolutionize IVF success predictions
NCT ID NCT07305480
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This observational study aims to create a digital twin model that predicts whether an embryo will implant successfully during IVF. Researchers will analyze de-identified data from one participant, including clinical, molecular, and biochemical information. The model does not affect treatment decisions and is only used for research. If it works, it may help doctors choose the best embryos for transfer.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If successful, this could lead to a tool that helps doctors predict which embryos are most likely to implant, potentially improving IVF success rates.
- What could go wrong
- This is a very early, small study with only one participant, so results may not apply broadly. The model is not yet proven and may not improve real-world outcomes.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
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1 person
The number who actually took part.
- Started
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Jan 2023
- Expected to finish
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Dec 2026
An estimate. End dates often move.
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
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.
- Ages
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Children (under 18), adults (18 to 64) and older adults (65 and over)
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * 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. Exclusion Criteria: * 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.
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As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Ukrainian Association of Biobanks Austria - Digital Twin Lab
Graz, 8010, Austria
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