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CardMedic and LanguageLine announce app integration

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CardMedic, the digital platform transforming clinician and patient communication, has announced a major integration with LanguageLine Solutions, the global leader in on-demand interpretation.

The partnership brings one-click access to live, professional video and audio interpreters in more than 240 languages directly within the CardMedic app.

The integration will help clinicians deliver safe, inclusive, and human-centered care at the point of need.

Dr Rachael Grimaldi, co-founder and chief medical officer of CardMedic said: “Our mission is to remove barriers that stand in the way of safe, compassionate care.

“This integration with LanguageLine gives clinicians fast and reliable access to professional interpreters alongside all of CardMedic’s inclusive tools, making communication more effective and equitable than ever before.”

CardMedic’s digital app breaks down language, cognitive, and sensory barriers, providing clinicians with instant access to multilingual and multimodal tools that support patients across a wide range of communication requirements.

With LanguageLine’s trusted interpreter network now embedded into the platform, CardMedic becomes the only solution of its kind to combine prewritten clinical content, AI powered accessibility tools, and live interpretation in one seamless workflow.

CardMedic was quickly developed during the COVID 19 pandemic in response to urgent communication breakdowns caused by masks and PPE.

Since then, it has grown into a comprehensive healthcare language support platform, used across NHS trusts in the UK and expanding internationally into the United States.

Designed in collaboration with clinicians and refined through real patient feedback, the app is simple to use, fast to deploy, and built to fit within clinical workflows across acute, emergency, and routine care.

With the new integration, healthcare staff can connect to a live LanguageLine interpreter within seconds, directly inside the CardMedic app.

Whether a conversation starts with a multilingual script or with an AI powered sign language avatar, clinicians can now escalate immediately to human interpretation with no disruption to care.

The experience includes intelligent language selection, optional department code support, and device flexibility.

Early feedback from NHS and US health systems points to faster decision making, improved patient understanding, and reduced delays.

CardMedic’s AI is guided by a clinician in the loop model that ensures all content is accurate, culturally sensitive, and accessible at a 6 to 8-year reading level. The platform complies with GDPR, is tested to minimise bias, and is designed to complement human interpreters rather than replace them.

The result is a flexible, ethical, and scalable communication solution that strengthens understanding, safety, and trust across diverse patient populations.

CardMedic has been cited in NHS England’s 2025 Patient Safety Healthcare Inequalities Reduction Framework and supported by key innovation programs including the NHS Innovation Accelerator, Clinical Entrepreneur Programme, MassChallenge, and Texas Medical Center Innovation.

As healthcare systems continue to focus on reducing disparities, CardMedic’s all in one platform is uniquely positioned to support scalable, equitable care across urgent and planned settings.

Simon Yoxon-Grant, president and CEO of LanguageLine Solutions said: “When a clinician can connect with a patient in their own language, it affirms the patient’s right to be heard.

“We’re proud to work with CardMedic to deliver that kind of access at the point of care.”

Looking ahead, CardMedic is developing personalised interpretation pathways, digital consent support, and communication tools for underserved communities.

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Early PET scan could chemo response in aggressive breast cancer – study

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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.

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Femtech World reveals startup of the year shortlist

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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.

OvartiX is doing something that has never been done before: building a drug discovery engine purpose-built for women’s health.
Its lead programme, OVX001, targets medically induced menopause – a condition affecting young female cancer patients who undergo chemotherapy or radiotherapy.
These women are cured of cancer but enter menopause overnight.
There is currently no approved drug to prevent it. OVX001 is designed to change that, preserving 80–95 per cent of ovarian follicles during treatment without compromising anti-tumour efficacy.
Behind the science is the OmiXX platform: the first ML-driven drug discovery tool built specifically for female physiology, using proprietary ovarian cellular models and human multi-omics data.

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.

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Gestational diabetes increases risk of type 2 diabetes – even at normal weight, study finds

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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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