News
New technology for assisted reproduction could reduce time to pregnancy
The technique has the potential to reduce the time and treatment cycles needed to achieve pregnancy through IVF
A new technology could make it possible to classify the quality of embryos faster and twice as accurately as expert embryologists.
The technology, developed by the Institute for Bioengineering for Catalonia (IBEC), uses imaging and AI to analyse the metabolism of embryos and oocytes obtained through IVF in order to decide which are most likely to implant in the uterus and reach full-term.
The technique promises to reduce the time and treatment cycles needed to achieve pregnancy through IVF, minimising the emotional and financial burden on patients.
According to researchers, the method, called METAPHOR, generates 3D images that reveal the colours present in the embryo in a non-invasive way. Certain naturally fluorescent compounds in the embryo’s metabolism are also key to processes, such as cellular respiration or nutrient consumption, making METAPHOR a “reliable” way to monitor the embryo’s health.
“This new technology will help to increase the probability of success in assisted reproduction processes, reducing the so-called ‘time to pregnancy’ and the economic and psychological burden on patients,” said Samuel Ojosnegros, principal investigator at IBEC and leader of the study.
A paper, published in PNAS, describes how, in studies with mice, the researchers using the method were able to double the success rate in selecting viable embryos compared to embryologists using traditional microscopy.
In addition to embryo analysis, the technique has been shown to be “highly accurate” in analysing oocyte metabolism, allowing the most suitable oocytes to be selected for IVF.
The researchers compared oocytes from young and older females and showed that METAPHOR system discriminated between young and non-young oocytes with 96 per cent accuracy and was able to predict which would develop into viable embryos with over 80 per cent accuracy.
Anna Seriola, senior researcher in the Ojosnegros group and author of the study, said: “We are able to assess the loss of oocyte quality associated with the loss of fertility with age.
“We look for so-called ‘molecular signatures’, characteristics of the cells that are associated with this loss of fertility, such as the distribution of mitochondria.
“From this information, we can predict which oocytes will develop and which will not. This would be a breakthrough in the management of fertility donation and preservation.”
The technological basis of METAPHOR uses AI methods to analyse metabolic images obtained by hyperspectral microscopy, explained Albert Parra, a researcher in the Ojosnegros group and first author of the study.
“Using hyperspectral microscopy, we acquire hundreds of images containing complex information of many mixed metabolites from embryos and oocytes.
“To analyse them, we trained an AI tool capable of analysing and classifying these images in a few minutes.”
Researchers are currently fine-tuning the technology to evaluate human embryos and have established a spin-off company to bring the technology to assisted reproduction clinics in the coming years.
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An early PET scan after one cycle of chemotherapy may help predict how aggressive breast cancer responds to treatment, a study suggests.
Research led by The Institute of Cancer Research, London and King’s College London suggests that an early scan taken after one cycle of chemotherapy could help predict how well a patient’s cancer will respond to treatment.
The study focused on patients with triple-negative breast cancer (TNBC), an aggressive form of the disease in which cancer cells lack receptors for the hormones oestrogen and progesterone, as well as the HER2 protein.
Patients with TNBC are usually treated with chemotherapy prior to surgery. While many respond well, residual disease at surgery, typically around six months later, is associated with a significantly poorer prognosis. Identifying people sooner who are unlikely to respond remains a major clinical challenge.
The research explored whether using PET imaging shortly after treatment begins, rather than relying only on MRI scans later in the treatment process, could provide earlier insight into how a patient’s cancer is responding. Twenty-two patients were recruited, with fourteen undergoing FDG-PET scans before treatment and after the first cycle of chemotherapy.
The findings, published in Clinical Cancer Research, showed that changes seen on PET scans after just one cycle of chemotherapy were strongly associated with subsequent response, including whether there was no detectable cancer, known as a complete response, by the end of treatment. Importantly, early PET response showed stronger associations with treatment outcomes than standard mid-treatment MRI scans in this study.
Being able to identify patients who are not responding well at an early stage could allow clinicians to adjust treatment sooner or consider alternative approaches. These findings may also support future strategies to better tailor treatment intensity to individual patients.
The study also compared two types of PET tracers, FDG and FLT, to determine which was most suitable. While both met the study’s technical criteria, FDG-PET was selected for further evaluation due to its better image quality, greater consistency and wider use in clinical practice.
The research also explored how imaging changes after just one cycle of chemotherapy relate to the body’s immune response to treatment. Biopsies taken before and after the first cycle of chemotherapy showed that an increase in immune cells within the tumour was strongly associated with both early PET changes and improved treatment outcomes.
The researchers emphasise that these findings now need to be validated in larger studies. Future work will aim to confirm these results in broader patient groups and explore more accessible imaging approaches, such as ultrasound, alongside PET and MRI.
Sheeba Irshad, professor of cancer immunology at King’s College London and lead of the Breast Cancer Now KCL Research Unit, said:
“In patients who had PET scans both before treatment and after the first cycle, we found that this early scan could predict whether they were likely to achieve a complete response by the end of treatment. These findings highlight the potential of early imaging to guide treatment decisions, and now need to be validated in larger, modern clinical trials.”
Andrew Tutt, professor of breast oncology at The Institute of Cancer Research, London, said:
“Research that helps us determine early who is already benefitting from standard neoadjuvant chemotherapy and who might benefit from clinical trials to find better treatments is vital. This study shows that FDG-PET may have great value in this regard. We hope to be able to design studies that further investigate and validate these findings.”
The study was supported by funding from King’s College London and Guy’s and St Thomas’ NHS Foundation Trust, Breast Cancer Now, Cancer Research UK, and Guy’s and St Thomas’ Charity.
We are excited unveil the three finalists competing for one of the Femtech World Awards’ most coveted honours: the Startup of the Year Award, sponsored by Future Fertility.
This award celebrates an early-stage company making a bold impact in women’s health through innovation, vision and execution.
The winner will be announced at our virtual ceremony on 19 June, with the decision made by a representative from category sponsor Future Fertility.
Congratulations to the shortlist and thank you to everyone who entered or nominated.
Startup of the Year Shortlist
Hello Inside is the first women’s health AI company to turn daily metabolic signals into outcomes women feel and healthcare systems reimburse.
Women’s health has long been under-researched, and current AI benchmarks fail on women’s health questions roughly sixty percent of the time.
Hello Inside built the architecture to close that gap.
Across four years and 12,000+ validated metabolic profiles, three in four women improve at least one symptom within ninety days.
They lose four kilograms in three months, moving from overweight into the healthy range. In a clinical study with Alisa Vitti’s Flo Living, 91.9 per cent reduced PMS burden within sixty days.
U-Ploid is an early-stage biotechnology company tackling one of the most fundamental challenges in fertility care: the sharp, age-related decline in egg quality that limits outcomes across IVF and egg freezing.
While much of the field focuses on improving assessment and selection, U-Ploid is developing a first-in-class therapeutic approach designed to improve egg quality itself by addressing the biological causes of age-related chromosomal errors.
Supported by strong preclinical evidence and now advancing into human studies, U-Ploid combines scientific rigour, regulatory discipline and long-term vision to help redefine what is possible in fertility care.
Gestational diabetes is a strong risk factor for future type 2 diabetes, even in women with normal pre-pregnancy weight, according to a study at the University of Gothenburg.
The researchers call for earlier testing and better follow-up.
“Our results show that gestational diabetes functions as a kind of stress test for the body’s ability to manage blood sugar, and identifies women with a greatly increased risk of future type 2 diabetes”, said Jon Edqvist, PhD and affiliated to research at the University of Gothenburg, and operating room nurse at Sahlgrenska University Hospital.
Gestational diabetes is a special type of diabetes that can affect pregnant women.
The condition is defined as elevated blood sugar levels, without previously known diabetes. Treatment involves self-monitoring of blood sugar, advice on lifestyle habits and, if necessary, medication.
Identifying gestational diabetes is important because the disease increases the risk of complications such as preeclampsia, the need for a cesarean section and high birth weight for the baby.
Those who have had gestational diabetes are also at higher risk of later developing type 2 diabetes.
In the current study, published in eClinicalMedicine, researchers now show that gestational diabetes is a strong indicator of future risk of developing type 2 diabetes, even in women with normal weight before pregnancy.
Elevated risk even with normal weight
The study is based on data from the Medical Birth Registry on just over 1.15 million first-time mothers in Sweden, who gave birth between 1987 and 2019. 16,870 women with confirmed gestational diabetes were compared with age-matched women without the diagnosis. The median follow-up period was nine years.
The results show that women with a BMI of 35 and above, i.e. severe obesity, had an almost tenfold increased risk of developing gestational diabetes compared to women with normal weight.
The risk of subsequent type 2 diabetes also increased with higher BMI, but it was significantly increased even with normal weight, which the researchers describe as particularly worrying.
More follow-up and more studies
The researchers behind the study welcome the recently updated recommendations on gestational diabetes in Sweden, where a higher proportion of pregnant women at increased risk are expected to be offered testing earlier in pregnancy, and if necessary, interventions.
“Diagnostics and care of gestational diabetes have looked very different in different parts of the country,” said Annika Rosengren, professor at the University of Gothenburg.
“There is a need for both improved follow-up after gestational diabetes, and more studies that investigate how such follow-up affects future health and prognosis”
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