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AI In Health And Beyond: What To Expect In 2025

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Artificial Intelligence is progressing quickly. From chatbots to generative AI content, the technology is being used in virtually every industry. And, as it enjoys more widespread use, it is becoming more advanced.

AI content is becoming more difficult to detect, and its use in data analysis is producing results across businesses and industries. In healthcare, as in most industries, AI is being used for everything from communication to automated data analysis and, in 2025, the industry will see greater innovation and improvements.

AI Improvements

The idea of artificial intelligence dates back to the automatons of ancient Greece, although the start of modern AI can be dated to the 1950s, especially Alan Turing’s imitation game (now known as the Turing Test). The technology has become prevalent in the past few years, though, as technology like smartphones and advanced processors have expanded artificial intelligence.

Today, the best AI apps for iPhone can generate AI voices and art. They can also, according to senior technology writer Alice Martin, be used to manage social media. As well as its benefits for personal use, AI is also a powerful tool used in the healthcare industry.

Improved Chatbot Communication

Chatbots can be used to answer quick questions and direct users to appropriate answers. Within the healthcare industry, these tools can be used to answer patient calls and direct the caller to the most appropriate ward or department.

As AI continues to develop, being trained by healthcare and communication specialists, it will be better equipped to deal with more complex enquiries. Although it is still some way off, AI could eventually be used to assist with diagnosis.

Administrative Assistance

As well as being used as chatbots for rapid responses to queries, AI can be deployed as virtual assistants. Virtual assistants are more advanced than chatbots and can manage calendars, arrange and rearrange meetings, and perform other tasks for healthcare professionals. They can also be used to book appointments, send follow-up letters, and offer more advanced features to patients.

Dealing With Data

AI is well-equipped to handle, read, and manipulate large volumes of data. This makes it especially useful for administrative tasks. As well as being able to work with patient data and health records, AI can aid in everything from patient applications to marketing and advertising. Patient data records must be accurate, and different departments and different organizations may hold different data on patients. This data needs to be amalgamated to provide the greatest benefits and assist in accurate diagnoses.

Marketing Prediction

Marketing is another area that relies on the use of large sets of data. It also uses predictive modelling and optimization, and these are areas where artificial intelligence is already well advanced. These marketing features can be used by healthcare institutions and private healthcare facilities, as well as pharmaceutical companies and manufacturers.

The health insurance industry will also benefit from more reliable and targeted marketing campaigns backed by predictive modelling.

Fraud Detection

Fraud is fairly commonplace within the healthcare industry and it is estimated that it costs the industry $250 billion a year or more. Typical fraud cases involve individuals fraudulently making claims against insurance, but they can also involve healthcare facilities and providers altering claims or submitting larger claims than are reasonable. Insurance companies invest large sums to try and identify and combat this type of fraud, and AI is positioned to help.

Machine learning algorithms are used to analyze the behaviors of individuals and healthcare providers. These algorithms can detect any anomalous activity, which may be indicative of fraudulent activity. AI can compare claims to previous claims by the same patient, as well as patterns established across the industry. With more data comes more accurate results, and 2025 is likely to see AI implemented in this way with greater frequency.

Improved AI Diagnostics

The healthcare industry has a wealth of diagnostic tools, with more tests regularly being introduced. Test results can include data provided by the patients themselves to medical imaging, blood tests, and more. Any one of these diagnostic tools can identify potential conditions.

When healthcare providers are looking at diagnostic information, they tend to look for very specific indicators, whereas AI can be used to highlight other, otherwise unseen, symptoms and signs. Various AI companies and specialists are looking at ways to improve AI diagnostics, and even Google is known to be advancing in this area of AI research.

Personalized Medication Plans

Medication plans are used in the treatment of various conditions and can require complex combinations of different types of treatment as well as various medications. AI can analyze patient responses to medication, as well as study treatment outcomes from other patients.

Using this information, AI can potentially develop more accurate and more effective medication plans, and so in real-time, while checking patient records for any potential issues. This also frees up time for healthcare providers to be able to meet with patients and receive diagnostic answers.

Predictive Analytics

Predictive analytics can be used throughout the patient journey, as well as in administrative roles within the healthcare industry. It can be used to predict potential outbreaks of illnesses or to predict the course of an individual’s illness. It can also be used to predict health and wellness epidemics that will sweep through nations, and then to use this and other information to devise action plans to help prevent the spread.

2025 is likely to see further moves into multimodal AI within healthcare. Multimodal AI means taking and using data from multiple sources. This will not only include diagnostic test results, but patient details from other sources.

Medical Claim And Insurance Assessments

Health insurance and medical claims are important components of the healthcare industry. Insurance underwriters use predictive modelling, taking into account patient data and previous health tests, to help determine the risks they pose.

To do this, they need to analyze large data sets related to applicants and the population as a whole. Machine learning algorithms use data that is updated in real-time to assess risks on the fly. AI can also be used to process medical claims and to identify likely fraud.

AI Regulations

AI is an emerging field. Some of the biggest companies in the world are working on their own AI solutions, and it is being implemented in various big industries, including healthcare. While this does mean that the technology continues to advance, it also means that patients and individuals need safeguarding.

As such, governments and government agencies are working on ways to implement safeguarding procedures and policies. 2025 is likely to see further AI regulation, and this will continue, especially as the technology becomes more advanced and as it is used to deal with highly personal information like medical records.

Conclusion

AI is a disruptive technology, and while it certainly isn’t a new technology, it has seen considerable jumps forward in the past few years. As well as being used in the development of different forms of content, it has found use in marketing, communication, and across a host of different industries and markets. Healthcare’s use of big data and its need for up-to-date analysis means that artificial intelligence continues to gain prominence within healthcare companies.

 

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Cancer

The most measured cancer in women’s health still decides half its cases without the measurement

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Breast cancer has more molecularly targeted options than any other tumour in women’s health. The evidence now shows that the limiting factor is no longer the drug, and no longer the science. It is the test – and the decision it is supposed to inform.

By Wolfgang Hackl, MD, OncoGenomX

A paradox worth sitting with

Hormone-receptor-positive, HER2-negative breast cancer is roughly 70 percent of female breast cancer, according to the National Cancer Institute’s SEER programme, and it has more approved biomarker-directed treatment options than any other subtype.

Yet in a 12,377-patient real-world cohort followed to March 2025 and reported at the San Antonio Breast Cancer Symposium, 51 per cent of women with ER-positive, HER2-negative metastatic disease had never once been tested for an ESR1 mutation – the marker that both ASCO and ESMO say to look for at progression.

That is not a science gap. It is an infrastructure gap, and it lands on women.

Breast cancer was the first solid tumour to be managed molecularly, and HER2, germline BRCA, PIK3CA, AKT1, PTEN, ESR1 and HER2-low expression have each since been added as a gate to a specific class of drug.

By any reasonable measure this is the best-equipped disease in women’s health. The delivery data tell a different story.

In an 8,049-patient analysis presented at ASCO, only 37 per cent of women received any next-generation sequencing between 2017 and 2021, and 92 to 93 per cent of that sequencing happened only after first-line therapy had already been chosen.

Community practice has improved – testing before second line rose from 9 per cent in 2018 to 69 per cent in 2024 – but in data through January 2025, nearly one-third of women still entered a second line untested, and the share of PIK3CA-mutant patients actually receiving a matched targeted therapy fell from 32 to 27 per cent in second line over the same period.

Testing is scaling. Converting a test into the right prescription is not.

Four ways the current test fails the woman in front of it

The first failure is timing.

A result arriving after the most valuable line of therapy has been committed cannot influence it – and on the ASCO figures above, that is the majority pattern, not an edge case.

The second is the specimen, and it is a structural double bind rather than a laboratory shortcoming.

SEER analysis shows bone is involved in 72.1 per cent of hormone-receptor-positive, HER2-negative disease at first metastatic presentation.

Bone is also the site where molecular testing fails hardest: in a PLOS ONE series of image-guided biopsies, 53.3 per cent of bone and 43.2 per cent of breast specimens were inadequate for sequencing; a 614-case series in the American Journal of Clinical Pathology traced 91 per cent of failures to insufficient DNA input; and routine strong-acid decalcification is known to degrade nucleic acids severely.

Blood does not rescue this. In a matched comparison of 5,780 tissue and 1,670 liquid profiles, PTEN loss appeared in 4.1 per cent of tissue but 0.2 per cent of plasma. Both routes fail in overlapping populations of the same women.

The third is reproducibility, and it now sits directly on top of drug access. HER2-low and HER2-ultralow categories decide eligibility for an effective antibody-drug conjugate, and they sit exactly where pathologists agree least.

In a 2026 Korean Society of Pathologists consensus study, seven pathologists reading 15 whole-slide sets reached unanimity in 5 of 15 cases; a nine-site local-versus-central rescoring exercise produced HER2-ultralow concordance of 43.3 per cent.

The same holds at the oestrogen receptor 1 to 10 per cent boundary. Add that the French ESME national cohort found hormone receptor or HER2 status changing between primary tumour and metastasis in 27.0 per cent of cases, and a quarter of women carry an unresolved biological conflict that is arbitrated case by case, invisibly, without an audit trail.

The fourth is conceptual, and it is the deepest.

Presence of a mutation is used as a proxy for activity of the pathway it sits in. In the pooled SAFIR02-BREAST analysis published in Nature Medicine, matched therapy on high-tier actionable targets produced an adjusted hazard ratio of 0.41, while matching beyond those tiers gave 1.15 – no benefit at all.

Precision is not binary. The quality of the match is itself the variable, and today’s report does not measure it.

The blind spot this readership should care about most

Invasive lobular carcinoma is 10 to 15 per cent of breast cancer and molecularly distinct: The Cancer Genome Atlas found CDH1 mutation in 63 per cent of lobular versus 2 per cent of ductal tumours, and a 2025 JAMA Network Open analysis showed PIK3CA and NF1 enrichment persisting in metastatic disease.

It is also under-measured, because lobular-enriched alterations are exactly the ones plasma detects worst, and under-studied: of 93 phase III and IV trial manuscripts reviewed in npj Breast Cancer, only 14.0 per cent documented lobular inclusion at all.

The outcome gap is measurable – in the 13,111-patient ESME database, lobular histology carried an overall survival hazard ratio of 1.17 in hormone-receptor-positive, HER2-negative disease.

A subtype that behaves differently, is measured worse, is studied less and does worse on the same treatment is not a rounding error. It is an unmet design requirement.

What the next generation of tests has to do

The failure chain above is specific enough to read as a specification. None of it requires a scientific breakthrough; all of it requires a different architecture.

  • Read mechanism, not only lesion – report whether the relevant biology is actually running, not only whether a licensed alteration is present. That distinction separated a hazard ratio of 0.41 from one of 1.15 in the same trial programme.
  • Treat pre-analytics as a design constraint, not a caveat. A test that needs ideal input will not reach the women who most need it. It has to work from archival material that already exists in every pathology department, and declare its limits rather than fail silently.
  • Condition interpretation on histology instead of averaging across it. Lobular and ductal disease must be allowed to yield different recommendations from the same molecular pattern.
  • Resolve the ambiguous zones by declared rule, not private judgement. Rules of precedence stated in advance, applied identically to identical inputs, versioned and auditable – that is what converts an interpretation into an accountable act.
  • Settle the endpoint with regulators first. A progression-free survival hazard ratio of 0.45 on a molecular trigger recently drew a 6-to-3 vote against clinically meaningful benefit from the US Food and Drug Administration’s advisory committee, while European regulators adopted a positive opinion on the same data.

Why this is a women’s health equity question

Three arguments make this more than a laboratory debate. The first is geography.

In a survey of 118 Italian institutions, 88.1 per cent could obtain PIK3CA analysis but only 57.6 per cent on site, and 46.6 per cent held no molecular accreditation; an NHS genomic hub audit found identical assays succeeding at rates between 68 and 81 per cent across referring centres.

Where a woman is treated determines what is knowable about her tumour, which makes a test built to run on ordinary archival material an equity instrument before it is a technical one.

The second is money, and payers are widely misread here.

Testing is not the cost driver: in the only comparable payer modelling available, from Ontario and in a different tumour type, it represented 1.0 to 2.4 per cent of total two-year cost, while the Journal of Managed Care and Specialty Pharmacy put first-line CDK4/6 inhibition plus endocrine therapy at 62,229 US dollars per patient per year in a Medicare population.

A BMJ Medicine analysis found additional Medicare spending on accelerated-approval cancer indications between 2012 and 2022 of 20.1 billion US dollars, 59.2 per cent of it going to indications with no demonstrated overall survival benefit – and breast cancer was the largest single contributor at 7.4 billion.

Meanwhile US coverage policy still requires that tissue profiling be infeasible before plasma profiling is reimbursed: payers fund the expensive half of precision oncology while restricting the cheap half.

The third is the patient, and it should settle the matter.

In a 2,662-patient real-world series in Breast Cancer Research and Treatment, progression-free survival fell from 16.3 months in first line to 9.1 in second and 6.2 in third; only 54.8 per cent of women reached a second line, 28.5 per cent a third and 7.0 per cent a fifth, and the median patient received two lines in total. A mis-selected first or second line therefore does not cost one interval.

It consumes a large share of everything that woman will ever receive.

For developers the same logic runs in reverse: industry analysis of clinical development success rates associates patient preselection with a likelihood of approval from phase I of 15.9 per cent, against 7.6 per cent without it.

The biology is largely known. The drugs are largely approved.

The money is already being spent – and a meta-analysis of 193 studies and 283,110 patients finds that 13.9 per cent of women treated for early breast cancer still recur at a distant site, 23.3 per cent of those beyond ten years.

What is not yet built is the layer that decides.

For an industry that has learned to ask who benefits from innovation and who is left out of it, that layer is where the next decade of value in women’s cancer care will be created – or quietly forfeited.

AUTHOR BIOGRAPHY

Wolfgang Hackl, MD, is an oncologist and the founder, Chief Executive Officer and Chief Medical Officer of OncoGenomX, a molecular diagnostics company in Allschwil, Switzerland, working on treatment-selection support in hormone-dependent breast cancer.

He has led cancer research, development and translational medicine programs for over two decades, and currently runs multi-site clinical validation studies with US Department of Veterans Affairs medical centers.

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Hormonal health

Major UK study could be a ‘game-changer’ for heavy periods and endometriosis

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A UK study will build a menstrual fluid biobank to help women get faster, better treatment for heavy periods.

Thousands of participants will provide menstrual fluid samples over three cycles using specially designed period pads. They will also use a daily tracking app and complete detailed questionnaires.

Researchers from the Universities of Exeter and Bristol will work with participants from two UK birth cohort studies, Children of the 90s and Born in Bradford.

Professor Gemma Sharp, of the University of Exeter, said that the study is set to be a ‘real game-changer’ for menstrual health research.

Sharp said: “We know that menstrual health is a key indicator of overall health, but a lack of high-quality data means it remains poorly understood and under-supported in healthcare.

“We also know that heavy periods can affect many aspects of daily life – for example, our recent research revealed an association between heavy periods, school attendance and lower GCSE attainment – so we urgently need new ways to support the millions of women affected by heavy periods more promptly and effectively.”

The CycleTrack study aims to create the world’s largest menstrual fluid biobank for people in their mid-30s.

By combining these samples with long-term health and genetic data, researchers hope to identify biological signals linked to differences in periods and related conditions.

Researchers hope the findings could support earlier diagnosis, better care plans and tools to identify risks including iron deficiency.

The study is part of The Missed Vital Sign, a programme led by Wellcome Leap that contributes to a broader global effort to reduce the time it takes a woman to receive effective treatment for heavy menstrual bleeding from five years to five months.

Up to 50 per cent of women worldwide experience heavy periods, which can significantly affect physical, emotional and social wellbeing.

Researchers say the work could also improve understanding of menstrual health more broadly and help inform future school and workplace guidance.

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Fertility

One week left to apply: W Accelerate with Merck KGaA and M Ventures

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Applications close 2 September at 12pm BST for W Accelerate with Merck KGaA and M Ventures, a fast-track programme offering startups, scaleups and spinouts in reproductive and maternal health direct access to decision-makers at one of the world’s leading reproductive health companies.

With a single application, innovators connect with Merck KGaA’s partnership team and investment professionals from M Ventures, Merck’s corporate venture arm.

Selected companies will be notified on 11 September and invited to pitch at W Accelerate in London, at One Hundred Shoreditch, on 5 October.

During the event, they will receive a private 30-minute session with Merck and M Ventures leadership, small-group guidance from regulation and investment specialists, an “Ask Merck Anything” roundtable, and access to a VIP networking reception.

Applications are open to companies working on breakthrough solutions across reproductive and maternal health, including fertility, endometriosis, adenomyosis, ovarian health, preeclampsia and pregnancy comorbidities.

Applicants can choose one of three lanes,  depending on whether they’re seeking strategic collaboration, investment, or both: Partnership Lane, Investment Lane, or Dual Lane. Direct-to-consumer and over-the-counter products are outside the programme’s scope.

Thang Vo-Ta, CEO & co-founder of Calla Lily Clinical Care and participant of a previous edition of W Accelerate with Merck Healthcare and M Ventures, said: “The opportunity to pitch directly to senior leadership at Merck and M Ventures sparked conversations that became the foundation of relationships leading to our eventual strategic collaboration with Merck. I’ve yet to see another event run with this level of excellence.”

For more information, visit W Group’s website: wplatform.co

Applications close 2nd September 2026, 12pm BST

W Accelerate event: 5th October 2026 at One Hundred Shoreditch, London (travel and accommodation not provided)

Apply here

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