Embryo AI

IF A WOMAN (or non-female-identifying person with a uterus and visions of starting a family) is struggling to conceive and decides to improve their reproductive odds at an IVF clinic, they’ll likely interact with a doctor, a nurse, and a receptionist, not an AI specialist. They will probably never meet the army of trained embryologists working behind closed lab doors to collect eggs, fertilize them, and develop the embryos bound for implantation.

One of embryologists’ more time-consuming jobs is grading embryos—looking at their morphological features under a microscope and assigning a quality score. Round, even numbers of cells are good. Fractured and fragmented cells, bad. They’ll use that information to decide which embryos to implant first.

It’s more gut than science and not particularly accurate. Newer methods, like pulling off a cell to extract its DNA and test for abnormalities, called preimplantation genetic screening, provide more information. But that tacks on additional costs to an already expensive IVF cycle and requires freezing the embryos until the test results come back. Manual embryo grading may be a crude tool, but it’s noninvasive and easy for most fertility clinics to carry out. Now, scientists say, an algorithm has learned to do all that time-intensive embryo ogling even better than a human.

In new research published today in NPJ Digital Medicine, scientists at Cornell University trained an off-the-shelf Google deep learning algorithm to identify IVF embryos as either good, fair, or poor, based on the likelihood each would successfully implant. This type of AI—the same neural network that identifies faces, animals, and objects in pictures uploaded to Google’s online services—has proven adept in medical settings. It has learned to diagnose diabetic blindness and identify the genetic mutations fueling cancerous tumor growth. IVF clinics could be where it’s headed next.

“All evaluation of the embryo as it’s done today is subjective,” says Nikica Zaninovic, director of the embryology lab at Weill Cornell Medicine, where the research was conducted. In 2011, the lab installed a time-lapse imaging system inside its incubators, so its technicians could watch (and record) the embryos developing in real time. This gave them something many fertility clinics in the US do not have—videos of more than 10,000 fully anonymized embryos that could each be freeze-framed and fed into a neural network. About two years ago, Zaninovic began Googling to find an AI expert to collaborate with. He found one just across campus in Olivier Elemento, director of Weill Cornell’s Englander Institute for Precision Medicine. by Megan Molteni, April 4, 2019

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Anthony Brown

Anthony Brown

Attorney and Advocate at Time For Families
Who am I? On the deepest level, I am blessed. I have an amazing partner, who I have known since 1989 and been married to since 2004. I am the donor dad of two beautiful daughters who have two moms who are equally amazing. My husband and I have expanded our family through surrogacy and have a seven-year old son. I have had three careers (acting, massage therapy and the law) and I am still discovering myself. I am the Board Chair of Men Having Babies. The one thing I know for sure is that life is about trusting your instincts. Family is an instinct.
Anthony Brown