InfertilityMECANEMBNCT06408389
Mechanics of Human Pre Implantation Development
An observational study of Infertility, run by Assistance Publique - Hôpitaux de Paris.
Trial summary
The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). Read more about this study
- Who is it for?
- Ages 18 to 43 years
- Conditions the study is for
- Infertility
- How many people
- 1,500 participants
- Where
- No sites listed yet
- Study dates
- Nov 2025to Nov 2028
- 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 18 to 43 years
- All sexes
- Adult
Study population: Couples enrolled in an IVF process (conventional IVF or with sperm micro-injection (ICSI))
Who may be able to join
- Couples enrolled in an IVF process and with embryos cultured in time-lapse
- Couples informed non opposed to research
Who cannot join
- Couples opposed to research
- Couples under curator or tutorship
- Couples under state xxx
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: From Oocyte to Embryo: Analysis of Mechanics of Human Pre Implantation Development
The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.
The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm. The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation using machine learning and to link these factors to human embryo mechanistic properties.
Read the detailed description
The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.
The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm.
Machine learning is one of the main methods of data analysis that could define algorithms that are unbiased, more robust and applicable to all centers. But the optimal algorithm is not yet defined. Recently, an artificial intelligence approach applied to a large collection of time-lapse embryo images was developed to determine the embryo with the highest grade of evolution, with an AUC> 0.98. Using clinical data, the authors created a decision tree to integrate embryo quality and female age and identify the chances of pregnancy. However, this approach did not take into account the whole kinetics of development, focusing on certain particular stages, nor the influence of parental and extrinsic factors other than age.
The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation and embryo development in IVF/ICSI using machine learning algorithms and relate these morpho-kinetic factors to the mechanical characteristics of cells.
- Conditions
- Infertility
- Keywords
- In vitro fertilization, embryo, human time lapse, pregnancy, delivery, machine learning
- Medical subject headings
- Infertility
What is being measured
The primary outcome is the main question the study is designed to answer.
Prediction of embryo implantation by the machine learning algorithm from embryo morphokinetic parameters and patient health data.
The algorithm outcome will be evaluated retrospectively on human embryos which have been transferred, for which we know whether its implantation was successful and led to birth. Using embryo morphokinetic and health patient data, we will predict a probability of implantion and compare its value (<0.5: no implantation or >0.5: implantation) to the true result of the embryo transfer (no implantation or implantation). This will allow us to evaluate the potential of the algorithm to support clinical decision-making in the future.
Measured: 2 years
Secondary outcomes (27)
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Age (years) : female / male
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Weight (kg) : female / male
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Height (cm) : female / male
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Weight and height combined for BMI (kg/M2) : female / male
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : Day-3 FSH (IU/l)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : Day-3 LH (IU/l)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : Day-3 Estradiol (pg/ml)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : Day-3 AMH (ng/ml)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : Day-3 Antral Follicular count
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : cause of infertility (endometriosis (yes/no))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : cause of infertility (tubal (yes/no))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Female : cause of infertility (diminished ovarian reserve (yes/no))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : sperm parameters (volume (ml))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : sperm parameters (concentration (10^6/ml))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : sperm parameters (progressive mobility (%))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : sperm parameters (vitality (%))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : sperm parameters (normal form (%))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : FSH (IU/l)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : LH (IU/l)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : total testosterone (ng/ml)
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
caryotype : Female/male
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : cause of male infertility (obstructive azoospermia (yes/no))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : cause of male infertility (non-obstructive azoospermia (yes/no))
Measured: 3 years
Link between couples' parameters and embryo morpho-kinetics
Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :
Male : cause of male infertility (oligoasthenoteratospermia (yes/no))
Measured: 3 years
Statistical correlation between embryo implantation prediction and morphokinetic parameters
The machine learning algorithm (neural network) trained for the primary outcome will be used to quantify the average percentage contributed by each morphokinetic parameter in the prediction of implantation success or failure ("explainable artificial intelligence"). This will allow us to determine what morphokinetic parameters influence the most positively or negatively the prediction of implantation.
Measured: 3 years
Embryo reconstruction in 3D
Develop an automatic method for reconstructing the morphology of embryos in 3 dimensions from 2-dimensional images in transmitted light (Geri incubator or Embryoscope type)
Measured: 3 years
Software developing
Develop decision support software for the benefit of embryologists as part of an ART attempt
Measured: 3 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 May 2024
- Study startNov 2025 (estimated)
- Primary completionNov 2028 (estimated)
- Study completionNov 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for InfertilityStudies of the same condition, open and under way.
- More trials run by Assistance Publique - Hôpitaux de ParisThe sponsor's other registered studies.
- 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
- Retrospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Assistance Publique - Hôpitaux de Paris
- Sponsor type
- University, hospital or other
- Collaborators
- Collège de France, Institut Curie, Centre National de la Recherche Scientifique, France, URC-CIC Paris Descartes Necker Cochin
- Responsible party
- Sponsor
- Investigators
- Catherine PATRAT, MD, PhD, Principal investigator, AP-HP (Professor in Medicine faculty and Hospital practitioner (APHP.centre - Université de Paris, site Cochin)Jean-Léon MAITRE, PhD, Study director, Institut Curie CNRS UMR3215 INSERM U934Hervé TURLIER, Study director, Collège de France, CIRB CNRS UMR7241
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06408389
- Sponsor's protocol ID
- APHP210563
- Acronym
- MECANEMB
- Status last verified
- Sep 2025
- First submitted
- 16 Nov 2021
- Last updated
- 12 Sep 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 12 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- From Oocyte to Embryo: Analysis of Mechanics of Human Pre Implantation Development
- ClinicalTrials.gov ID
- NCT06408389
- Acronym / sponsor ID
- MECANEMB / APHP210563
- Conditions
- Infertility
- Keywords
- In vitro fertilization, embryo, human time lapse, pregnancy, delivery, machine learning
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- Assistance Publique - Hôpitaux de ParisUniversity, hospital or other
- Collaborators
- Collège de France, Institut Curie, Centre National de la Recherche Scientifique, France, URC-CIC Paris Descartes Necker Cochin
- Study start
- Nov 2025 (estimated)
- Primary completion
- Nov 2028 (estimated)
- Study completion
- Nov 2028 (estimated)
- First posted
- 10 May 2024 (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.
The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.
The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm. The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation using machine learning and to link these factors to human embryo mechanistic properties.
Detailed description
The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.
The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm.
Machine learning is one of the main methods of data analysis that could define algorithms that are unbiased, more robust and applicable to all centers. But the optimal algorithm is not yet defined. Recently, an artificial intelligence approach applied to a large collection of time-lapse embryo images was developed to determine the embryo with the highest grade of evolution, with an AUC> 0.98. Using clinical data, the authors created a decision tree to integrate embryo quality and female age and identify the chances of pregnancy. However, this approach did not take into account the whole kinetics of development, focusing on certain particular stages, nor the influence of parental and extrinsic factors other than age.
The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation and embryo development in IVF/ICSI using machine learning algorithms and relate these morpho-kinetic factors to the mechanical characteristics of cells.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 43 years
- Sex
- All
- Age groups
- Adult
- Study population
- Couples enrolled in an IVF process (conventional IVF or with sperm micro-injection (ICSI))
Key inclusion criteria (2 listed)
- Couples enrolled in an IVF process and with embryos cultured in time-lapse
- Couples informed non opposed to research
Key exclusion criteria (3 listed)
- Couples opposed to research
- Couples under curator or tutorship
- Couples under state xxx
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Prediction of embryo implantation by the machine learning algorithm from embryo morphokinetic parameters and patient health data.
Time frame: 2 years
The algorithm outcome will be evaluated retrospectively on human embryos which have been transferred, for which we know whether its implantation was successful and led to birth. Using embryo morphokinetic and health patient data, we will predict a probability of implantion and compare its value (<0.5: no implantation or >0.5: implantation) to the true result of the embryo transfer (no implantation or implantation). This will allow us to evaluate the potential of the algorithm to support clinical decision-making in the future.
27 secondary outcomes
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Link between couples' parameters and embryo morpho-kinetics
Time frame: 3 years
Statistical correlation between embryo implantation prediction and morphokinetic parameters
Time frame: 3 years
Embryo reconstruction in 3D
Time frame: 3 years
Software developing
Time frame: 3 years
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 12 Sep 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.
Catherine PATRAT, MD, PhD principal investigator
AP-HP (Professor in Medicine faculty and Hospital practitioner (APHP.centre - Université de Paris, site Cochin)
Jean-Léon MAITRE, PhD study director
Institut Curie CNRS UMR3215 INSERM U934
Hervé TURLIER study director
Collège de France, CIRB CNRS UMR7241
Questions about this trial
What is this clinical trial studying?
An observational study of Infertility, run by Assistance Publique - Hôpitaux de Paris.
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 2 inclusion and 3 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: opening soon, as of the sponsor's last update on 12 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
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?
Contact Catherine PATRAT, MD,PhD (00 33 1 58 41 37 34, catherine.patrat@aphp.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Prediction of embryo implantation by the machine learning algorithm from embryo morphokinetic parameters and patient health data. (time frame: 2 years). 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 12 Sep 2025.