Dr Alice CHEN - Auxogyn, Inc. UNITED STATES

Dr Alice A. Chen is the Head of Biomedical Research at Auxogyn, Inc., a Silicon Valley startup that is advancing the field of reproductive health through its uniquely combined knowledge of early human developmental biology, advanced computer vision technology and best clinical practices. Dr Chen has worked for over a decade at the interface of engineering and biomedicine to help develop new systems to model, diagnosis and treat human development and disease. Her specific areas of interest include regenerative medicine, cell and tissue biology, drug development, and micro/nano devices.

Dr Chen holds a Ph.D. in Biomedical Engineering and Medical Physics from Harvard and MIT, S.M. in Engineering Sciences from Harvard University, and B.S. in Bioengineering from the University of California, Berkeley. She has been honored internationally for her research, innovation and community impact and is also passionate about inspiring today’s youth to pursue careers in science, engineering and entrepreneurship.

Project: Non-invasive, automated aneuploidy screening in human embryos

The optimal goal of IVF is a single healthy baby. Embryo viability assessment based on time-lapse imaging can improve embryo selection; however, the relationship among viability, implantation and chromosome content (ploidy) is still under investigation. Pre-implantation genetic screening (PGS) is useful to diagnose ploidy, but it is invasive to the embryo and limited to specialized laboratories.

The objectives of this project are to (1) examine whether embryo viability markers from time-lapse imaging correlate with ploidy, implantation and live birth, and (2) leverage validated computer vision technology toextract the relevant parameters and develop a non-invasive automated method for aneuploidy screening. This will be a retrospective study of 100 patients undergoing IVF, time-lapse imaging to the blastocyst stage, trophectoderm biopsy with PGS as recommended by a reproductive endocrinologist, and embryo transfer. Embryo imaging data will be evaluated for a distinct set of time-lapse parameters shown to predict viable blastocyst formation [1-3] and ploidy at the 4-cell stage (including a novel fragmentation parameter detectable by computer vision tracking algorithms) [4]. The parameters will be automatically extracted and evaluated against various endpoints, including: ploidy, implantation, clinical pregnancy, ongoing pregnancy, multiple pregnancy and spontaneous miscarriage. In order to monitor outcomes for transferred embryos, maternal serum will be collected at 9 weeks of gestation for free fetal DNA fingerprinting.

A non-invasive, automated aneuploidy screening tool may help patients improve the odds of bringing home one healthy baby. This study will also advance basic science, improve clinical decision trees for embryo selection, and assist embryologists in their clinical workflow by reducing the need for manual image analysis.

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