Improving IVF through integration of morphological and molecular analyses – BOOSTIVF

As In Vitro Fertilization (IVF) success rate is limited, it is crucial to improve IVF outcome by gaining better knowledge on embryo quality assessment. As morphology is poorly predictive of implantation, the identification of non-invasive markers of embryo quality is a relevant strategy, such as combination of time-lapse and secretomics considered here. Our team already obtained preliminary results that support this project, i.e. automated morphokinetic annotation tool and human early embryo transcriptome converted into virtual secretome. The main objectives of this 48 months project are (i) improving our automated system for new unsupervised morphokinetic analysis (ii) using our transcriptomic pseudotime model to unravel signaling cues active during human preimplantation development (iii) validating biomarkers identified in the blastocyst secretome with MRM-based proteomic approach. The expected identification of predictive biomarkers aims at improving pregnancy rate in IVF cycles.