Alife Health Receives FDA Clearance for AI-Powered Embryo Assessment

New tool gives fertility clinicians an adjunctive data-driven layer of insight for one of IVF's most critical decisions, supported by a multi-center randomized clinical trial

SAN FRANCISCO, May 28, 2026 /PRNewswire/ -- Alife Health, a digital health company advancing fertility care through artificial intelligence, today announced that its product Embryo Predict has received clearance from the U.S. Food and Drug Administration (FDA). The clearance covers the use of Embryo Predict to help fertility specialists evaluate and select embryos for transfer during in vitro fertilization (IVF), one of the most consequential decisions in the IVF process.

IVF is one of the most emotionally and financially demanding medical journeys a person can take, with patients in the U.S. undergoing an average of three cycles before a successful pregnancy. A significant factor is the complexity of choosing which embryo to transfer. Published research found a 34.6% disagreement rate among fertility specialists selecting the top embryo for transfer, rising to 44% when patients had three or more embryos to choose from[1]. Even among the most experienced clinicians, this evaluation has remained largely a matter of individual judgment.

Embryo Predict uses artificial intelligence to analyze images of each embryo and generate an AI score. The AI draws on patterns learned from thousands of embryos and their outcomes across clinics, geographies, and patient profiles worldwide. It integrates with the microscopes and imaging systems already in use in fertility labs, with no new hardware required.

The FDA clearance was supported by a prospective, randomized, multi-center clinical trial, that was conducted at seven leading centers across the United States. The trial enrolled 440 patients across seven U.S. clinics and evaluated the use of AI-assisted embryo selection compared to standard evaluation alone.

"Six years ago, we set out to put IVF's wealth of clinical data to work in a way the field had never seen before. Today, that work is validated," said Melissa Teran, CEO and co-founder of Alife Health. "This clearance reflects years of rigorous clinical research and the trust of the clinicians and institutions who partnered with us. For the first time, the collective insight from thousands of embryos and outcomes around the world is available to every embryologist, at every transfer decision."

"As the field of reproductive medicine advances, we have a responsibility to bring the most rigorous, evidence-based tools into our labs. Alife's Embryo Predict does exactly that. It layers AI-driven insight onto the clinical expertise already in the room, giving embryologists adjunctive AI information for one of the most consequential decisions in a patient's IVF journey, " said Alison Bartolucci, Ph.D., HCLD, Chief Scientific Officer at First Fertility.

Embryo Predict is indicated to analyze images of Day 5, 6, and 7 blastocyst-stage embryos that have been deemed suitable for transfer by the embryologist. The device provides adjunctive information to aid in the assessment of blastocysts when there are multiple embryos deemed suitable for transfer or freezing based on standard morphological assessment.

Embryo Predict also holds CE Mark under the European Union Medical Device Regulation and is now commercially available across the U.S., Europe, and the U.K.

ABOUT ALIFE HEALTH

Alife Health is a digital health company advancing fertility care through artificial intelligence. The company develops AI tools for IVF clinicians and labs, including Embryo Predict, its AI-powered adjunctive embryo selection tool; Schedule Predict, a scheduling optimization tool; and Success Predictor, a patient-facing family planning tool. Alife's mission is to bring consistency, efficiency, and data-driven decision support to every stage of the IVF process. The company is based in San Francisco, California. To learn more, visit alifehealth.com.

MEDIA CONTACT

Jamie Gray, [email protected]

REFERENCES

1. Barash OO, et al. Clinical evaluation of a machine learning model for embryo selection. Fertil Steril. 2023. doi:10.1016/S0015-0282(23)00824-5.

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SOURCE Alife Health