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The Jerusalem Post

First-ever AI tech to detect risk for hundreds of genetic diseases

 
 Artificial intelligence continues to advance the world of medicine (photo credit: SHUTTERSTOCK)
Artificial intelligence continues to advance the world of medicine
(photo credit: SHUTTERSTOCK)

Israeli startup Identifai uses groundbreaking AI to analyze maternal blood samples, identifying genetic risks in a 9-week-old fetus with unmatched accuracy through full genetic sequencing.

Every year, 140 million babies are born worldwide, with 6–8% considered at risk of developing hereditary genetic conditions linked to parental genetics. Amniocentesis, the current standard for detecting such conditions, is highly accurate but invasive, carrying risks for both mother and fetus. In recent years, non-invasive prenatal tests (NIPTs) analyzing maternal blood have become an alternative, though they identify only a limited range of conditions, primarily Down syndrome and a few other chromosomal anomalies.

Founded in 2021, Identifai set out to revolutionize early detection of fetal genetic diseases by leveraging the research of Prof. Noam Shomron, a world-leading expert in genetics and bioinformatics at Tel Aviv University. Together with Dr. Tom Rabinowitz, Identifai developed AI/ML technology capable of separating maternal and fetal DNA fragments from a maternal blood sample, enabling, for the first time, complete genetic sequencing of the fetus.

This technology can identify mutations down to a single DNA base from billions, vastly expanding the scope of detectable hereditary genetic diseases. After analyzing the maternal blood sample, the system generates a comprehensive report for parents, gynecologists, fetal medicine specialists, and geneticists, detailing the likelihood of the fetus carrying or developing specific genetic conditions. Decision-making regarding the findings remains solely with the parents and medical professionals.

 Eyal Miller, Identifai's CEO (credit: Moran Nissim)
Eyal Miller, Identifai's CEO (credit: Moran Nissim)

Identifai’s technology has already gained global recognition. A study conducted in collaboration with Rabin Medical Center was featured on the cover of Prenatal Diagnosis, the leading journal in the field. The research involved 18 pregnant women and their partners, identifying abnormal genetic conditions with 100% accuracy compared to amniocentesis results.

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Eyal Miller, Identifai’s CEO, stated: “Our unique technology has the potential to redefine the prenatal testing market, currently valued at over $6 billion annually and projected to exceed $19 billion by 2030. Identifying hundreds of genetic conditions in fetuses with unparalleled precision will expand the market to hundreds of billions, including early intrauterine surgeries and late-stage diagnostics when amniocentesis is no longer an option. Moreover, our solution is accessible, convenient, and suitable for populations avoiding amniocentesis due to cultural, medical, or legal constraints.”

Following the success at Rabin Medical Center, Identifai is conducting another trial in the U.S. at Columbia University Medical Center, with results pending. Additional trials at seven leading U.S. medical centers are expected to begin within months, providing valuable documentation and validation. Concurrently, the company is negotiating with major U.S. corporations that may adopt its technology as a service for their clients. Identifai plans to launch its product commercially in 2025.

Miller emphasized the role of collaboration in the company’s success:“Identifai exemplifies the power of academia-industry partnerships. Prof. Shomron’s research uncovered the ability to isolate fetal DNA fragments from maternal blood, and we harnessed AI and ML technologies to transform this discovery into a market-changing product.”

Identifai has raised $6.5 million to date from early-stage health-tech investors, including eHealth Ventures, Shizim VC, and private investors, alongside grants from the Israel Innovation Authority. The company employs 15 people at its Tel Aviv headquarters.

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