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
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 1
- 试验地点
- 1
- 主要终点
- Accuracy of Digital Twin Model in Predicting Embryo Implantation
研究概览
简要总结
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.
详细描述
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;
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Other
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Accuracy of Digital Twin Model in Predicting Embryo Implantation
时间窗: 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.
次要结局
未报告次要终点