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Study shows CHLOE AI’s role in advancing reproductive health research

By Published On: September 12, 2023
Study shows CHLOE AI’s role in advancing reproductive health research

Fairtility, the transparent AI innovator powering reproductive care for improved outcomes, has announced the highlights of a new study published in Nature’s Scientific Reports. 

The study, focused on blastocyst morphometric parameters’ impact on implantation potential, highlights how Fairtility’s transparent AI decision support technology, CHLOE, can support academic research in the field of assisted reproductive technologies.

The study, entitled An artificial intelligence algorithm for automated blastocyst morphometric parameters demonstrates a positive association with implantation potential, was led by Professor Iris Har Vardi, director of Fertility and IVF Lab at Soroka University Medical Center and senior lecturer at Ben Gurion University in the Faculty of Health Sciences. Har Vardi also serves as a scientific advisor to Fairtility.

Automatic measurements of blastocyst morphometrics. (a) A day-5 blastocyst with trophectoderm (TE) and inner cell mass (ICM) cells. (b) The same embryo with markings. Blue represents the hand drawn segmentation around the outer part of the TE cells, excluding the area occupied by the zona pellucida. Green represents the ellipse that best fits around the segmented ICM pixels in the least-squares sense. Red represents the diameter of the embryo.

The study included 608 transferred blastocysts that were selected using morphokinetics and Gardner criteria. Retrospectively, researchers deployed CHLOE to automatically assess four morphometric parameters: blastocyst size, inner cell mass (ICM) size, ICM-to-blastocyst size ratio and ICM shape.

Researchers found that blastocyst size had a significant positive association with implantation such that with every 1 μm increase in blastocyst size, there was a relative increase in the odds of implantation by 2.1 per cent.

Applying CHLOE to assess these parameters retrospectively, was possible due to CHLOE’s advanced, consistent and automated assessment.

These capabilities enable researchers to study various events, biomarkers, timing and ratios objectively that were previously not possible, providing new insights for treatment decisions and opening up tremendous opportunity for more research to advance the field.

“CHLOE’s AI algorithms enabled us to measure various embryo components automatically with higher accuracy and speed than us, the embryologists,” explained Professor Har Vardi.

“As a researcher and a clinical embryologist, AI provides a powerful new tool and opens endless possibilities to further explore basic science and clinical parameters.

Professor Iris Har Vardi, director of Fertility and IVF Lab at Soroka University Medical Center and senior lecturer at Ben Gurion University 

“This research highlights the potential for enhanced blastocyst selection in the IVF process using AI technology, which offers great promise for improving the effectiveness and personalisation of reproductive healthcare.”

Researchers can utilise CHLOE to further their understanding of embryo and oocyte development that may enhance current workflows, protocols and practice of reproductive health care.

Eran Eshed, co-founder and CEO of Fairtility, said: “Our mission at Fairtility is to advance and improve reproductive care through CHLOE, our AI powered software platform.

“We promote this in clinical settings through our product offerings and in academic settings to advance the science and understanding of reproductive health.

“We can leverage AI technologies to elevate care in clinics, and ensure researchers continue to advance our understanding to improve patient care in the long term.”

CHLOE is currently being used in tens of clinics around the world. Clinicians utilise CHLOE EQ for automated embryo quality assessment in IVF, CHLOE OQ to support oocyte assessment for fertility preservation, egg donation and in IVF decision making, and CHLOE KPI for clinical and operational performance monitoring.

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