Fertility
Future Fertility partners with Japan’s leading IVF provider, Kato Ladies Clinic

Future Fertility, a Toronto-based health technology company specialising in AI-powered fertility insights, has entered the Japanese market through a new commercial partnership with Kato Ladies Clinic — a globally recognised leader in IVF research and advancing clinical fertility care.
The collaboration marks Future Fertility’s first partnership in Japan and reflects growing global demand for technologies that bring greater objectivity and personalisation to fertility care.
Kato Ladies Clinic will integrate the company’s AI-powered oocyte (egg) quality assessment tools into its clinical workflows, with the aim of supporting more informed treatment planning and patient counselling across IVF and egg freezing cycles.
“At Kato Ladies Clinic, we are committed to advancing fertility care through innovation while maintaining a strong focus on individualised, patient-centred treatment,” said Keiichi Kato, chief executive officer.
“Partnering with Future Fertility enables us to integrate objective, data-driven insights into our clinical approach and better support our patients in making informed decisions.”
Future Fertility’s platform analyses images of oocytes using artificial intelligence trained and validated on a dataset of more than 650,000 unique oocyte images.
The technology is already in use at more than 300 clinics across more than 35 countries, helping clinicians better understand the developmental potential of individual eggs and provide patients with more personalised insight earlier in their treatment journey.
From Research Collaboration to Clinical Adoption
The partnership between Future Fertility and Kato Ladies Clinic began as a scientific research collaboration in 2024, marking the first use of AI-powered oocyte quality assessment in Japan.
The collaboration not only validated the technology in a new patient population and across diverse clinical protocols — including minimal stimulation cycles —but also resulted in a peer-reviewed publication in Reproductive BioMedicine Online (RBMO) and a poster abstract presentation at ESHRE 2025.
The joint research explored how AI-derived oocyte quality scores relate to early embryonic development and overall treatment outcomes. In a retrospective study conducted at Kato Ladies Clinic, researchers analysed nearly 2,800 mature oocytes across more than 1,300 ICSI cycles, linking image-based assessments of egg quality to key developmental milestones.
The study demonstrated that lower AI scores were associated with reduced fertilization rates, delays, and abnormalities in early embryo development, increased developmental errors, and lower-quality blastocyst formation.
Notably, the researchers also found that cumulative oocyte scores were a stronger predictor of live birth outcomes than the number of eggs retrieved — underscoring the importance of assessing egg quality alongside quantity.
“Our collaboration with Future Fertility has demonstrated how artificial intelligence can uncover meaningful biological differences between oocytes that were previously difficult to quantify,” said Kenji Ezoe, senior scientist.
“Bringing this technology into routine clinical use is an important step toward translating research into improved patient outcomes.”
Future Fertility’s VP of clinical embryology & scientific operations, Jullin Fjeldstad, noted that the findings provide important clinical validation.
“Our joint research with Kato Ladies Clinic has shown how AI-based oocyte assessment can be directly linked to numerous embryo development outcomes, from fertilization through early developmental milestones and blastocyst formation,” she said.
“We are excited to see this work translated into clinical practice.”
Growing Demand for Fertility Care in Japan
The partnership comes at a time when demand for fertility treatment in Japan continues to rise.
The country performs over 450,000 fertility treatment cycles annually, making it one of the largest markets globally. Delayed childbearing and evolving societal trends have also contributed to increasing interest in egg freezing.
As patients seek more clarity and personalization in their care, tools that provide earlier insight into reproductive potential are gaining traction.
“Entering the Japanese market with a partner like Kato Ladies Clinic is a significant step forward for our global commercial strategy,” said Rafael Gonzalez, Future Fertility’s VP of global sales & strategy.
“It reflects the growing demand for technologies that support more transparent, data-driven fertility care across diverse healthcare systems.”
Expanding a Global Footprint
Founded in 1993, Kato Ladies Clinic is known for its pioneering work in natural and minimal stimulation IVF and has long been a leader in clinical innovation in Japan.
For Future Fertility, the partnership represents both a geographic expansion and a continuation of its broader mission to bring AI-driven insights into routine fertility care.
“We are proud to partner with Kato Ladies Clinic, a globally respected leader in IVF and a pioneer in reproductive medicine in Japan,” said Future Fertility’s CEO, Christy Prada.
“This partnership represents an important milestone as we expand into Asia and continue our mission to bring objective, personalised insights into fertility care worldwide.”
Future Fertility develops AI-powered tools designed to generate personalised insights across the fertility journey.
Its flagship oocyte assessment technologies analyse egg images to provide objective, individualised measures of egg quality, supporting treatment planning, patient counselling, and clinical decision-making in egg freezing and IVF, while also enabling more data-driven approaches to donor egg distribution and quality assurance.
As fertility care continues to evolve, collaborations like this one are helping shape a new standard — one that emphasises earlier insight, greater transparency, and more personalised decision-making for patients navigating increasingly complex reproductive journeys.
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Fertility
AI could transform ovarian care through personalisation, study finds

AI could transform ovarian care by personalising cancer and fertility treatment, but more clinical validation is needed before routine use.
A systematic review and meta-analysis found AI models showed high diagnostic accuracy for ovarian cancer when combining data such as ultrasound scans and blood test results.
Across 81 studies, AI models correctly identified ovarian cancer in around nine out of 10 cases, with pooled rates of 89 to 94 per cent.
They were also highly accurate at ruling out ovarian cancer when it was not present, with specificity of 85 to 91 per cent.
The analysis also found that explainable AI tools could predict complete surgical cytoreduction in advanced ovarian cancer.
Complete surgical cytoreduction means removing all visible cancer during surgery, which can be an important goal in treatment planning.
The tools achieved a pooled AUC of 0.87. AUC is a measure of how well a model distinguishes between different outcomes, with higher scores showing stronger performance.
In reproductive medicine, AI algorithms helped physicians optimise ovarian stimulation protocols and predict follicular growth during IVF.
Ovarian stimulation is the use of hormones to encourage the ovaries to produce eggs, while follicles are the small sacs in the ovaries where eggs develop.
The review found AI could reliably model ovarian response in IVF with a pooled AUC of 0.81.
However, researchers said challenges remain in translating promising research findings into routine clinical practice.
They identified substantial variation across studies, driven by retrospective study designs, variable AI systems and a lack of standardised validation.
Only 22 per cent of analysed studies reported prospective, multicentre external validation, where models are tested forward in time across multiple healthcare settings.
The authors called for rigorous validation to help close the gap between research and routine clinical practice, alongside standardised methodological and reporting frameworks, smooth integration with clinical workflow and robust governance to support responsible and ethical AI use.
They concluded: “Artificial intelligence is a transformative force in the management of ovarian conditions.
“In gynaecologic oncology, AI enhances every phase of care, from early detection and accurate diagnosis to prognostic stratification and surgical planning.”
In reproductive medicine, AI personalises ovarian stimulation and refines the diagnosis of heterogenous endocrine disorders such as PCOS.
PCOS, or polycystic ovary syndrome, is a hormonal condition that can affect periods, skin, weight and fertility.
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