The study, published in Fertility and Sterility, demonstrates Alife Health’s commitment to building scientific evidence for the application of artificial intelligence to improve IVF outcomes.
Today, researchers at Alife Health, a fertility technology company building artificial intelligence (AI) tools designed to improve in-vitro fertilization (IVF) outcomes, published data on embryo prioritization using AI technology. The study, published online in Fertility and Sterility, was conducted in collaboration with partners at some of the world’s leading fertility clinics, including Shady Grove, Boston IVF, Ovation Fertility, Cornell, IVF Florida, and RSC Bay Area.
In IVF, mature eggs are collected and fertilized by sperm in a lab to create embryos. Evaluation and selection of an embryo to transfer to a patient’s uterus is one of the most important steps. Currently, embryos are prioritized for transfer on the basis of genetic testing and a morphological grading system, where the grade is assigned by an embryologist. While morphological grading systems have been around for many years and have achieved widespread adoption, they are prone to inter- and intra-user variability. AI, or more specifically deep learning, has the potential to systematically analyze the morphological characteristics for embryos deemed suitable for transfer, combine it with patient-specific factors, and rank and prioritize embryos for transfer.
“AI is one of the technologies with enormous potential to transform the way we grade and prioritize embryos,” says Boston IVF CSO, Denny Sakkas, PhD. “It can theoretically help us identify subtle features that may not always be obvious to the human eye, reduce the subjectivity and biases we see routinely, and help standardize embryo scoring across embryologists and IVF laboratories, leading to an improvement in pregnancy rates.”
In this study, a new and generalizable deep learning model for ranking blastocyst-stage embryos was evaluated based on retrospective data from 11 different IVF clinics in the United States and over 8,000 blastocysts. The AI model was compared to manual grading in terms of overall and per-site pregnancy rates, and was visually inspected to understand what structures of the embryo the model is focusing on. Researchers specifically addressed sources of bias relating to the type of microscope used and the presence of foreign objects in the images such as holding micropipettes. These retrospective findings will need to be confirmed with additional clinical studies.
“These promising early results put us one step closer to delivering technology that can improve the efficacy of IVF for all patients,” says Alife Health CEO and Founder, Paxton Maeder-York. “Alife is working to empower clinicians with AI enabled tools to offer precision medicine in fertility, ultimately leading to better outcomes and more personalized care.”
Alife Health will continue to conduct additional clinical studies to validate the performance of this model and impact on pregnancy rates to obtain marketing authorization from FDA. This technology is currently investigational.
