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Israeli startup AiVF’s can identify genetic characteristics in embryos

The AiVF multi-module integrated platform combines AI, computer vision, and big data and is in use at a number of European clinics.

AiVF’s leading team. L-R Professor Daniel Seidman, MD., Daniella Gilboa Prof. Dan Ariely/ Photo Eyal Toueg

Israeli startup AiVF’s study shows that non-invasive AI analysis using artificial intelligence-based computer vision technologies, can identify genetic features in embryos.

“This breakthrough scientific research concluded that AiVF’s platform can automatically and reliably determine an embryo’s ploidy status i.e., whether it is genetically suitable, with no invasive biopsy (PGT-A) or spent media analysis. A truly contactless PGT-A,” said Daniella Gilboa, CEO, and Co-Founder of AiVF.

AiVF groundbreaking scientific paper evaluated the efficacy of EMA, AiVF’s integrated multi-module platform that blends artificial intelligence, computer vision, and big data. It was showing for the first time that genetic features of embryos may be retrieved using revolutionary AI-based computer vision technology.

The study, which was presented this week at the prestigious ESHRE (European Society of Human Reproduction and Embryology) annual conference, conducted at AiVF, that specializes in artificial intelligence (AI) technology for digitizing IVF (In Vitro Fertilization) clinics. The company researchers collaborate with researchers led by Dr. Marcos Meseguer of Valencia, Spain’s world-renowned IVIRMA clinic.

An image of an embryo

Today, physicians and embryologists frequently evaluate the embryo’s genetic makeup using an invasive procedure called PGT-A, which is gaining popularity globally, particularly in the United States. PGT-A determines the genetic status of embryos to select the best embryo for transfer and increase a patient’s likelihood of a successful pregnancy. PGT-A is performed by biopsying each embryo, time-consuming and difficult micromanipulation that risks damaging the embryos and preventing them from implanting effectively in the uterus.

The current research is based on a retrospective analysis of 2,500 embryos with PGT-A results, 1,000 of which were euploid (genetically normal) and 1,500 of which were aneuploid (genetically defective). In addition, the study evaluated the efficacy of AiVF’s integrated multi-module platform that blends AI, computer vision, and big data.

According to the study, EMATM detected substantial differences between aneuploid and euploid embryos during the first five days of embryonic development. Aneuploid embryos were significantly more likely than euploid embryos to reach each developmental milestone later, and the time gaps between developmental milestones were also significantly longer in aneuploid embryos.

“These results take many days to generate,” Meseguer explained, “as a result of the genetic analysis, which requires patients to freeze all their embryos and delay infertility treatment.” Prof. Daniel Seidman, co-founder of AiVF and a study participant, remarked that “for the first time, AI-based technology will radically revolutionize the way IVF is performed globally by giving an objective and precise strategy for increasing live birth rates.”

The study is another milestone for AiVF, which announced in April that its technology had been granted a CE Mark, paving the way for its use in clinics across Europe. AiVF, founded in 2018, now houses the world’s largest library of embryo images and patient data. Currently, the company is awaiting FDA approval.

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