Thiruvananthapuram: Keralam Health Minister K Muraleedharan on Monday said an expert team of the department would investigate alleged irregularities in the construction of isolation wards in 88 constituencies in the state after the Covid-19 pandemic.
Muraleedharan said the wards, built at a cost of around Rs 1.8 crore each, were of little use to the public as they lacked basic facilities.
He was replying to a submission in the state assembly by Congress MLA V P Sajeendran, who represents Kunnathunad, alleging that the isolation wards were sanctioned by former state Health Minister Veena George and describing the project as a “loot”.
Sajeendran demanded that a Special Investigation Team be constituted to probe the alleged irregularities and that the two agencies involved in setting up the wards be blacklisted.
“The officials responsible should be punished, and it should be investigated whether George had any role in the matter,” he contended.
The minister said the government had decided to set up modern isolation wards in 88 constituencies at a sanctioned cost of Rs 250 crore. The project was intended to help the state deal with future outbreaks of communicable and infectious diseases.
He said a Thrissur-based agency was awarded the contract to construct the wards at a cost of around Rs 1.38 crore each, while the Kerala Medical Services Corporation Limited (KMSCL) was tasked with procuring equipment at approximately Rs 44 lakh per ward.
“Of the 88 wards, work on only 55 was completed. They were also inaugurated in phases. As of October 2026, 33 of the 55 wards had been handed over to hospitals, while the remaining 22 had been made operational with the assistance of Kerala Infrastructure Investment Fund Consulting Private Limited (KIIFCON),” the minister said.
Muraleedharan further said none of the 55 completed wards could be used to accommodate or treat patients.
“Additionally, the buildings themselves have several problems. The wards lack air-conditioning and toilet facilities, civil works remain incomplete, and fans cannot be installed on the ceilings,” he claimed.
With around Rs 1.83 crore spent on each ward, none of the completed facilities was fit for accommodating patients. An expert team headed by the Principal Secretary, Health, has therefore been constituted to investigate the matter, Muraleedharan said.
For years, genomics remained largely confined to research settings and specialised laboratories. As it enters routine clinical practice, hospitals face a different challenge: how to adopt it at scale while keeping it clinically relevant, financially sustainable, and accessible to patients. At the India Precision Health & Genomics Leadership Summit 2026, hosted by Thermo Fisher Scientific in association with The Economic Times, a panel discussion on The Hospital Business Case for Genomics Application took place.
The panel brought together Varun Sharma, Chief Strategy Officer, Sir Ganga Ram Hospital; Dr Shuchin Bajaj, Founder Director, Ujala Cygnus Hospitals; Dr Bishnu Panigrahi, Group Head, Medical Strategy and Operations, Fortis Healthcare; and Tom Berkovits, Commercial Director, Clinical Sequencing Division, Asia Pacific & Japan, Life Sciences Solutions, Thermo Fisher Scientific. Dr Shashikant Pawar, Chief Operating Officer, Kokilaben Dhirubhai Ambani Hospital, moderated the session.
Beyond the laboratory
For Varun Sharma, genomics represents more than a diagnostic technology. “I look at it as a structural force,” he said, describing genomics as a development capable of influencing the entire continuum of care, from prevention and early detection to treatment, follow-up and disease management.
As hospitals invest in genetic expertise, bioinformatics capabilities and data-driven decision-making, clinical pathways themselves begin to evolve. Treatment becomes more precise, care models change and, ultimately, hospital economics change as well. One of the most significant shifts, he argued, will be in how hospitals engage with patients.
“The moment today you have a patient, you are organised around an event or an episode. Five to ten years, this episode economics of a hospital will move towards engagement economics,” he said.
Genomics opens the possibility of continuous engagement through risk assessment, predictive screening, surveillance and long-term monitoring. In oncology, where a large share of cancers in India continue to be detected at advanced stages, earlier diagnosis could lower treatment costs while improving outcomes.
Sharma also challenged healthcare leaders to look beyond conventional financial metrics when evaluating genomics investments. “Don’t look at it from an ROI perspective. Look at it from a value on investment (VOI) perspective,” he said.
Investing with local realities in mind
For Dr Shuchin Bajaj, the discussion around genomics looks very different when viewed from smaller towns and underserved regions. Bajaj argued that before discussions on affordability and accessibility can begin, healthcare providers often face a more basic challenge: availability. In many communities, access to advanced genomic services is limited. Even where such services are available, they must be appropriate for the population they serve. He questioned whether broad genomic testing necessarily improves clinical decision-making in every setting.
“Building volume and aggregation is the first thing we need to do if it has to be successful in a country like ours,” Bajaj said.
Rather than replicating expensive infrastructure across multiple facilities, he suggested that regional hubs could aggregate samples and expertise while allowing patients to remain closer to home. Such models, supported by appropriate payer structures and cross-subsidisation where required, could make genomic services more scalable.
Measuring impact, not volume
As genomic testing becomes more widely adopted, Dr Bishnu Panigrahi argued that hospitals need a clear framework to evaluate success. He proposed four areas for assessment: clinical utility, operational efficiency, patient impact and economic value. The starting point is whether genomics actually changes patient care.
“Does it help you in identifying the right drug to give, the right dose to give, and your treatment modality?” he asked.
Operational efficiency should extend beyond laboratory turnaround times to include the entire pathway from test ordering to clinical action. How quickly genomic findings influence treatment decisions is often more meaningful than testing speed alone.
Few areas to evaluate the value of genomics are improvements in patient survival, reduced recurrence rates and better overall disease management.
“It is not how many tests that you do, but whether the test that you did had a positive impact on the outcome for the patient,” he said.
According to Panigrahi, testing can be centralised or outsourced where appropriate. Clinical decision-making cannot. He reminded the need for India-specific genomic databases and evidence as continued dependence on Western datasets will limit the full potential of precision medicine in the country.
Lessons from global adoption
Drawing on international experience, Tom Berkovits said successful genomics programmes tend to be embedded within broader healthcare systems where testing, treatment and outcomes are closely connected. “They’re managing not only the patient and the patient outcome, but they’re managing the treatment as well,” he said.
In many countries, testing and treatment are funded through separate budgets. Berkovits pointed to examples such as countries in South America, where pharmaceutical companies collaborated to fund testing programmes in areas where reimbursement mechanisms were insufficient.
He also encouraged hospitals to look beyond sequencing alone. “Everybody needs to get better at biobanking, at keeping specimens, and then being able to interrogate those samples and ask further questions down the track,” he said.
As technologies such as proteomics, spatial biology and single-cell analysis continue to advance, hospitals that preserve samples and build local data repositories will be better positioned to generate insights relevant to their own patient populations.
The real challenge ahead
As the discussion drew to a close, Dr Shashikant asked the panelists to identify the biggest hurdle preventing hospitals from scaling genomic testing from hundreds to thousands of patients. Talent emerged as the dominant concern. Sharma said the challenge is not technology but the shortage of trained professionals needed to support scale. Dr Bajaj pointed to two barriers: aligning skilled human resources and securing greater acceptance from insurers, many of whom have yet to support reimbursement models for genomic testing.
Dr Panigrahi summed that growth depends on having the right people in the right roles, backed by accountability and ownership rather than passion alone. Tom echoed concerns around shortages across the genomics workforce, from pathologists to lab technicians, while also highlighting the need for wider education among patients and clinicians to build awareness and confidence in genomics beyond oncology.
Disclaimer: The views and opinions expressed in this content are those of the speaker ( except for Tom Berkovits who participated as a Thermo Fisher Scientific representative) and do not necessarily represent an endorsement, promotion, or official position of Thermo Fisher Scientific India or reflect any views of Thermo Fisher Scientific India. This content is intended for educational purposes only and should not be considered medical advice. The information discussed may not be applicable to all patients or situations. Healthcare professionals should use their own clinical judgment and consult relevant guidelines before making any medical decisions.
Disclaimer: The above content is non-editorial, and TIL hereby disclaims any and all warranties, expressed or implied, relating to it, and does not guarantee, vouch for or necessarily endorse any of the content.
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The Delhi High Court on Monday declined to grant PepsiCo permission to continue manufacturingbeverages containing the “energy drink” label. But the court asked a single-judge bench to explain why it had denied the company that relief.
A division bench of Acting Chief Justice Nitin Wasudeo Sambre and Justice Sanjay Sharma was hearing PepsiCo’s appeal against an October 6 order that allowed the company to sell its existing stock of Sting Energy and Adrenaline Rush but barred it from manufacturing fresh products with the “energy drink” tag.
During the proceedings, PepsiCo’s senior counsel argued that while the single judge had protected the company from any action over the FSSAI directive, it did not allow the company to continue manufacturing beverages under the same label.
The counsel also pointed out that similar relief had been granted to another beverage company in a different case involving Red Bull.
The division bench, however mentioned that it would not examine the merits of the dispute at this stage, considering the fact that PepsiCo’s request for confirmation of interim relief was still pending before the single judge.
“What is in operation is an ad-interim relief in the matter,” the court observed.
The bench noted that the October 6 order did not give specific reasons for preventing PepsiCo from manufacturing products with the “energy drink” label, especially when similar permission had been granted in the Red Bull case.
“We are prima facie of the view that the single judge has not recorded any specific reasons for not permitting the petitioner in the matter of manufacturing with the label ‘energy drink’, which otherwise was permissible in (the Red Bull case),” the bench said.
It directed the single judge to record the reasons within a week so that the division bench could consider the issue.
“We deem it appropriate to relegate the matter to the single judge with a direction that for observations in paragraph 13 of the order dated 6.10.2026, let there be reasons recorded so as to enable this court to deal with the issue,” the court ordered.
Meanwhile, counsel for the FSSAI opposed PepsiCo’s appeal, arguing that it was not maintainable.
The dispute began after the food regulator directed PepsiCo to remove the “energy drink” descriptor from its beverages and instructed food safety officers across the country to seize products containing the label.
PepsiCo argues against the directions before the Delhi High Court. On October 6, the single judge granted the company interim protection from coercive action and allowed it to clear its existing stock of beverages labelled as “energy drink”.
However, the court stopped short of allowing fresh manufacturing under the same label, prompting PepsiCo to approach the division bench.
As of now, PepsiCo can continue to sell its existing stock under the protection granted by the court, but the restriction on manufacturing new products with the “energy drink” label remains in place.
Pennsylvania’s Franklin County reported a measles-associated death on Monday, bringing the state’s death toll from the infectious disease to six.
The 39-year-old woman had several underlying health conditions, including a recent history of measles that had been treated with medication, the coroner’s office said in a statement.
The office said her death, investigated on Saturday, met the Pennsylvania Department of Health’s definition of a measles-associated death.
The coroner’s office did not release further details, citing privacy concerns.
The state health department did not immediately respond to Reuters request for comment. According to the Pennsylvania Office of Administration’s 2026 holiday schedule, the offices were closed on Monday for Indigenous Peoples’ Day.
Pennsylvania’s health department previously reported more than 1,000 cases and five deaths related to measles as the state continues to grapple with a rapidly growing outbreak.
However, the US Centers for Disease Control and Prevention has confirmed only two measles-related deaths nationwide, amid a disagreement between Pennsylvania Governor Josh Shapiro and US Health Secretary Robert F. Kennedy Jr. over how such deaths are defined.
The CDC has shifted to using mortality data from the National Center for Health Statistics (NCHS) for its national measles death count, moving away from reliance on state health departments – drawing scrutiny.
The agency has said it is working with state epidemiologists on a standard definition for measles-related deaths. The agency said its death count could change as additional information becomes available and reviews are completed.
Measles is a highly contagious viral disease but can be prevented with the measles, mumps and rubella vaccine, which is about 97% effective after two doses.
New Delhi: The Food Safety and Standards Authority of India (FSSAI) is considering formulating regulations specific to the ecommerce ecosystem, including quick commerce platforms and cloud kitchens, after cracking down on packaged foods and beverages, alcoholic beverages and retail stores, its chief executive Rajit Punhani said.
“We’ve had stakeholder consultations with ecommerce and quick commerce players. We’re planning to amend the regulation so that consumers know the manufacturing date, expiry date and batch number of products they’re ordering,” he told ET in an interview.
The regulator has also started inspections of dark stores of quick commerce firms and cloud kitchens, he said. While platforms often mention a product’s shelf life, consumers may not know the actual expiry date or batch number of products before placing an order.
The government has been examining complaints accusing quick commerce platforms such as Blinkit, Zepto and Swiggy Instamart of failing to display product information, including expiry, best-before and use-by dates.
The Legal Metrology (Packaged Commodities) Amendment Rules 2017 requires mentioning ‘best before’ or ‘use by’ date, month and year’ on food packets. The Central Consumer Protection Authority, after reviewing complaints received through the National Consumer Helpline, sent notices to ecommerce firms in 2024, directing them to display the manufacturing and expiry dates on packs. No regulation was passed at the time amid resistance from platforms.
Companies argued it was difficult to display detailed information, including expiry, best-before and use-by dates and batch numbers, for hundreds of thousands of grocery items. Pushback and pressures from Big Food “don’t keep me awake at night”, Punhani said, responding to a question on whether there was lobbying from large MNCs, especially on front-of-pack labelling for packaged food. It is “unethical for food companies to mislead consumers on labelling”, said the IAS officer and IIM-Bangalore alumnus.
“We are doing nothing wrong; we are just implementing the regulations,” he said. “So, we expect, especially big companies, to lead the way in following the regulations. They should be the first to not make misleading claims to consumers or misleading ads. We expect them to be the role models for the smaller companies and startups.”
The FSSAI in recent months issued notices to more than 150 food and beverage makers, including Nestle, PepsiCo, Dabur, ITC, Ferrero, Danone, Red Bull and Abbott, on issues ranging from incorrect and misleading labelling claims about ingredients to non-compliances on labelling. “It’s not that there are large numbers of violations; they are very few in terms of percentage,” Punhani said.
The regulator is actively moving towards implementing front-of-pack labelling for packaged food, more than a decade after making the initial proposal that faced resistance from global and Indian packaged foods makers and multiple litigations. In a recent affidavit filed at the Supreme Court, FSSAI proposed red, hexagonal front-of-pack warning labels, displaying the amount of nutrients such as sugar, salt and saturated fat in the contents, and is awaiting the court’s decision to take the next step.
His focus, Punhani said, was on enforcement. This involved strengthening of the state-level machinery. “I don’t see (state) food commissioners under pressure,” he said.
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In a notice issued last week, NMC advised all medical colleges and med institutions to appoint a patient safety nodal officer and set up a dedicated patient safety committee or cell to monitor safety practices, review incidents and recommend corrective action.
Experts said medical errors are preventable lapses causing harm, ranging from wrong drugs or dosages and infections due to unsterile equipment to bedsores.
The estimate was cited in a May 8 communication from additional director general of health services, which flagged the need to strengthen patient safety practices across medical colleges & hospitals.
The proposed cells will cover 11 domains, including medication and surgical safety, blood transfusions, medical devices, lab and diagnostic procedures, hospital-acquired infections, antimicrobial resistance, vaccine and injection safety, and facility safety.
The committees will be responsible for facilitating the reporting and analysis of patient safety incidents, near misses and high-risk events. They will identify gaps in systems, recommend corrective and preventive measures.
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New Delhi: People with long Covid, where symptoms persist after recovery from an acute Covid-19 infection, may have distinct differences in the mix of bacteria living in their mouths and lungs, research has shown.
The differences in the lung microbiome are linked to respiratory symptoms, as well as the cognitive and digestive problems known to occur in long Covid, researchers said.
The findings, published in the European Respiratory Journal, may contribute towards understanding why some people develop long Covid and point to new ways to treat the condition, they said.
“Prior studies have shown some changes in the gut microbiome with long Covid, but Covid is a lung disease and so it makes sense to look to see if the lung microbiome is changed in long Covid,” lead author Daniela Alferes de Lima Headley from the University of Dundee, UK, said.
“We know that millions of people worldwide are still affected by long Covid and its cause is still unknown. Long Covid affects multiple organs. The microbiome is important to maintain health throughout the body, so it is a strong candidate for something that may contribute to long Covid,” she said.
The study examined 771 people treated for Covid-19 at one of 38 UK hospitals between February 2020 and March 2021.
The participants were divided into four groups based on how bad their symptoms were five months after being discharged from hospital, ranging from ‘very severe’ with serious physical, mental, and cognitive impairments to ‘mild’, with few symptoms and good recovery.
Six months after hospital discharge, samples were collected from patients’ mouths through saliva and from their lungs through sputum. DNA sequencing was used to identify the microbes present.
By analysing the variety and quantities of microbes and comparing them with patients’ symptoms, researchers found that people with very severe long Covid had marked differences in their oral and lung microbiomes compared with those who did not have severe long Covid.
The results also revealed differences linked to specific symptoms, including reduced lung function, in which the lungs cannot hold as much air as normal or air cannot flow in and out as easily.
The researchers also found differences in the mouth and lungs microbiome between people with varying neurocognitive symptoms — including ‘brain fog’, difficulties with memory, attention and concentration — and gut symptoms, including pain, nausea, diarrhoea and loss of appetite.
Among the changes associated with long-Covid symptoms, was an over-abundance of bacteria that produce lactic acid, which was also linked to signs of inflammation found in samples of patients’ blood.
Lead researcher James Chalmers, chair of respiratory research at the University of Dundee, UK, said, “People who had the worst symptoms five to six months after Covid infection had big changes in the microbiome in their mouth and lungs.”
“We also found that changes in the airway microbiome were linked not just to lung problems, but also to symptoms like brain fog and gut symptoms, suggesting the lung microbiome could have effects on health more broadly,” he said.
U.S.-based digital health startups raised $3.7B across 114 deals in Q3 2026, bringing 2026’s year-to-date (YTD) total to $11.1B across 358 deals (projected to surpass $14.8 billion by year-end).
Capital continues to consolidate into larger checks across fewer companies: the 2026 YTD average deal size climbed to $31.0M, up from $29.5M in 2025 and $20.6M in 2024.
Rock Health’s 15-Year Market Review Analyzes $140B in Capital and Q3 2026’s Flight to Deployable Value
Marking its 15th anniversary and the 15th annual Rock Health Summit, digital health venture fund and advisory firm Rock Health released its Q3 2026 Market Update: Crystallizing Fifteen Years of Digital Health. The report pairs venture funding, M&A, and public-market tracking with a 15-year retrospective featuring founding pioneers, venture capitalists, and health system executives.
The central takeaway reflects a maturing, disciplined asset class: while total venture funding has normalized from pandemic peaks into sustained annual totals exceeding $10 billion, capital is consolidating into larger checks and fewer companies. Concurrently, enterprise buyers have abandoned point-solution experimentation in favor of architectural consolidation, shifting competition from speculative software builds toward proven implementation and deployable value.
Q3 2026 & Year-to-Date Venture Capital Benchmarks
Digital health financing across the first nine months of 2026 demonstrates consistent capital concentration:
Quarterly Capital Inflow: U.S.-based digital health startups secured $3.7B across 114 funding rounds in Q3 2026.
Year-to-Date Volume: YTD 2026 funding reached $11.1B across 358 deals, tracking toward an annualized projection of $14.8B (roughly 12 times the total invested in 2011).
Expanding Average Check Size: Capital is concentrating into fewer, higher-conviction bets, with the 2026 YTD average deal size expanding to $31.0M, up from $29.5M in 2025 and $20.6M in 2024.
Steady Strategic M&A: The sector logged 45 M&A transactions in Q3 2026, bringing the YTD exit total to 164 deals—tracking closely alongside 2025’s post-2021 high-water mark of 172 transactions through Q3.
Muted Public Listings: Public markets have remained largely quiet with no new listings since HeartFlow in August 2025, though several mature digital health leaders continue evaluating paths to liquidity.
15-Year Sector Arc: 2011 vs. 2026
The retrospective contrasts the infancy of the sector in 2011 with the enterprise reality of 2026:
Capital Availability: In 2011, early digital health investment resembled a fragmented market where founders had to defend the category itself; only 35 venture-backed digital health companies were tracked through August 2011, and the entire year totaled $1.2 billion across 96 deals (with 84% of entrepreneurs bootstrapped). Today, over 3,200 venture-backed companies have raised $2M or more.
Lowering Barriers to Build: Early founders had to build custom infrastructure from scratch. Modern founders start “floors higher,” assembling tech stacks in months using pre-built APIs for claims adjudication, insurance verification, EHR integration rails, virtual clinician staffing networks, and AI foundation models.
The Buyer Transition: Health systems have shifted from skeptical “dabblers” conducting isolated pilots to C-suite-driven architectural transformations. Health systems are actively terminating unintegrated point solutions to construct unified digital operating environments.
“In 2011, we saw less convergence between healthcare and technology, with few accelerators and talent oriented around the category,” noted Sean Duffy, Co-Founder and CEO of Omada Health. “My advice to founders is: make sure you’re really clear on the why. Building anything worth building is extremely difficult, and so much of success comes down to grit and not giving up.”
Four Structural Themes Defining the Next Era of Digital Health
Insights from the report’s industry pioneers and venture leaders highlight structural transitions across four key areas:
From “Digitization” to “Addition by Subtraction”: The first wave of digital health simply transferred analog paperwork onto computer screens, often worsening clinician burnout. The current wave focuses on removing cognitive load and administrative friction—such as ambient clinical scribes, automated prior authorization, and predictive capacity orchestration.
The New Moats in an “Easy-to-Build” Environment: Because generative AI and commoditized APIs make assembling software faster and cheaper, building a feature no longer creates a sustainable barrier to entry. Future competitive moats rely on enterprise implementation depth, tight EHR/workflow integration, clinical validation, and a willingness to absorb operational or regulatory liability.
Navigating the Illiquid Exit Runway: While venture funding has stabilized, liquidity remains constrained. With public markets demanding consistent profitability and M&A yielding mixed outcomes, late-stage companies must continuously evaluate private recapitalizations, dual-track M&A, and public readiness rather than waiting for speculative IPO windows to reopen.
The Re-Emergence of Hybrid Consumer Models: Early direct-to-consumer (D2C) health models suffered from high customer acquisition costs, episodic demand, and low lifetime value, prompting a widespread pivot toward B2B/employer channels in 2017. In 2026, the consumer has returned to the center: 57% of adults now track health metrics digitally and 46% own a wearable, forcing traditional payers, health systems, and B2B2C platforms to compete on seamless consumer-grade user experiences.
Jay Anders, MD, Chief Medical Officer at Medicomp Systems
Healthcare software colleagues of mine often describe a recurring discussion they have with their outsourced development teams. They recount that when they try to explain the difference between a billing diagnosis and a clinical diagnosis, the engineers on the other end deliver a common platitude: “a diagnosis is a diagnosis.”
That answer is defensible in ordinary English. In healthcare data, however, it is wrong in a way every team that accepts it inherits. The formal name of the “diagnosis” system is the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Statisticians created it in 1893 to count causes of death, and around 1938, leaders suggested that the codes might be useful to health insurers. Medicare then tied hospital reimbursement to those codes in 1983, and the rest is history.
Accordingly, I have started referring to ICD-10 as a billing category rather than a diagnosis code. Colleagues tell me the phrasing sounds pedantic, but we have all witnessed what has happened due to this lack of differentiation. Software analysts carry the loose usage into product requirements documents, data dictionaries and integration specifications. Developers then build software that treats a category as though it were a clinical finding. We are all suffering the consequences of asking a statistical instrument to carry the complexity and nuance within clinical meaning.
Grouper or Splitter?
The vocabulary distinction reminds me of when clinical informaticists once asked each other whether they were groupers or splitters. Groupers gather related conditions under a shared heading, while splitters separate them down to the specific entity. The people who built the ICD chose grouping because a statistical classification exists to produce comparable counts across whole populations. Grouping is what makes an epidemiological instrument work, but a clinical one fail.
Conversely, clinical care has continued to split because treatment now turns on distinctions a single code cannot carry. One example is ICD-10 code G60.0, hereditary motor and sensory neuropathy. Coders assign that single category to Charcot-Marie-Tooth disease (CMT) and to its near relatives alike. Yet researchers have now linked more than 100 genes to CMT alone, and dozens of clinically distinct diseases are filed under that heading, each with its own inheritance pattern and treatment path. A claim clears on G60.0 without difficulty, while a physician reading G60.0 learns almost nothing.
Maintainers cannot resolve this by adding codes. They added 487 new diagnosis codes in the fiscal year 2026 update, which all offer important detail. Even so, a larger classification system is still a classification system rather than a clinical vocabulary.
Where Therapy Already Split
Pharmaceutical manufacturers have already committed to the splitter’s position, a decision their product names record. Anyone watching evening television will hear a run of medications ending in -mab or -nib. Chemists apply the first stem to a monoclonal antibody engineered against a single protein, the second to a small molecule built to inhibit a specific kinase.
Eventually, however, even these naming conventions were not specific enough. In October 2021, the World Health Organization retired the -mab stem and replaced it with four stems because manufacturers had exhausted the available names. Concurrently, the FDA endorsed greater specificity through new drug approvals. Personalized medicines accounted for roughly 36% of new therapeutic molecular entities in 2025, the sixth consecutive year they exceeded a third of new approvals. Therapy is now chosen at the level of a protein, while the diagnosis pointing toward it is still recorded as a bucket.
Compiling the Confusion
AI-software vendors have supercharged the vocabulary problem operationally through ambient documentation. These solutions listen to a visit, infer a diagnosis and produce an ICD-10 code. That code is then treated as the diagnosis because that is the word everyone uses. Independent testers have measured the best general-purpose models at roughly 50% to 59% accuracy on medical coding. Consequently, a model that cannot determine the specific condition selects the broader code, presenting the clinician with a settled answer that is likely less accurate and certainly less informative.
Unfortunately, many vendors also group the alternate phrasings listed beneath a code as synonyms for it, which might be acceptable for billing, but is misleading for care. Several of those phrasings name distinct diseases with different genetics and different treatment. With only the category recorded, every downstream clinician may need to conduct their own time-consuming and costly investigation to arrive at a real diagnosis.
Writing the Distinction Into Systems
On a macro-level, fixing the problem must involve everyone in healthcare consistently differentiating ICD-10 codes as billing categories, both when speaking and writing. On a micro-level, software analysts should also distinguish the billing category and the clinical diagnosis as separate data elements. Similarly, evaluation teams should ensure a clinically specific diagnosis exists alongside the code captured in a way that a downstream platform can access and interpret it.
Until then, however, an evidence-based clinical knowledge layer can be integrated into electronic health record systems to import the specific diagnosis in the free text as a computable concept already mapped to its billing category, so both are recorded.
As a result, reimbursement is unaffected, but, more importantly, the next clinician then sees the clinical explanation alongside the code. So, in the past, when G60.0 (hereditary motor and sensory neuropathy) alone reported almost nothing, the additional detail now helps the clinician understand the type of hereditary neuropathy present to inform their decisions, potentially avoiding repetitive testing or ineffective therapies. The patient then receives the right treatment sooner, one that may never have been pursued if the condition remained obscured behind a vague label.
About Jay Anders, MD
Dr. Jay Anders serves as the Chief Medical Officer of Medicomp Systems, where he plays a pivotal role in product development and acts as a liaison to the healthcare community. He champions the use of technology to empower clinicians, rather than hinder them.
Medical device regulatory and certification platform Scarlet raises $50M in Series B funding round led by Headline, with participation from new investor Notion Capital and existing backers Atomico, Creandum, Kindred Capital, and Entrepreneurs First; Nancy Xiao McLaughlin, Partner at Headline, joins Scarlet’s Board of Directors.
Targets an acute regulatory bottleneck in digital health innovation: machine learning teams can train and validate an AI diagnostic model in weeks, yet legacy certification bodies typically subject developers to 12 to 18 months of review for initial market clearance, followed by six to eight months of administrative delay for minor algorithmic updates.
Operates as a government-designated certification body: out of the approximately 52 notified bodies designated under the European Union Medical Device Regulation (EU MDR), Scarlet is the only one exclusively specialized in software and artificial intelligence, built to support agile, iterative continuous deployment (CI/CD) pipelines.
Triple-Designated Statutory Authority
Unlike regulatory consulting firms or compliance software platforms that merely format submission documents, Scarlet operates as a formal, government-designated statutory auditing and certification body. Among the roughly 52 officially designated certification bodies under the European Union Medical Device Regulation, Scarlet is the sole entity purpose-built and designated exclusively for Software as a Medical Device and artificial intelligence.
The company also holds formal statutory designation from the UK Medicines and Healthcare products Regulatory Agency to issue UKCA markings for medical software, alongside accreditation under the U.S. Food and Drug Administration’s Third-Party Review Program, which authorizes Scarlet to conduct substantive regulatory reviews of eligible 510(k) premarket notifications. Founded in 2021 by former Babylon Health AI engineers James Dewar and Jamie Cox, the company spent its initial three years in rigorous collaboration with international regulatory agencies to secure full formal accreditation before issuing its first commercial certificates.
Scarlet replaces manual, paper-heavy regulatory dossiers with an AI-enabled certification operating system designed for agile software sprints. Medical device manufacturers upload clinical evaluation reports, verification and validation data, risk management files, and software architecture artifacts in any format. Scarlet’s ingestion layer parses and correlates technical documentation against international harmonized standards.
Technical assessments are conducted by specialized software and clinical AI reviewers who evaluate machine learning architectures, training and testing distribution shifts, and cybersecurity controls with software-native speed. Every audit finding, validation trace, and conformity decision is systematically evidenced within an immutable audit trail, providing competent authorities and regulatory bodies with full visibility into the technical reasoning behind certification decisions.
Operating on a recurring enterprise subscription model, Scarlet covers ongoing post-market surveillance, mandatory annual quality management system audits, and continuous product changes. This framework enables manufacturers to clear bi-weekly model iterations and algorithmic updates without filing duplicative, multi-month re-submissions.
Enterprise Client Roster and Market Validation
Scarlet’s AI-native assessment platform serves leading digital health enterprises, consumer giants, acute health systems, and high-volume clinical AI providers. In scaled consumer health, it powers regulatory certification for Flo Health, the women’s health application supporting over 500 million downloads. Across diagnostic and clinical specialties, the platform evaluates algorithmic oncology software such as skin cancer detection specialist Skin Analytics, as well as acute enterprise imaging infrastructure for U.S. radiology platform DeepHealth.
Public institutional care infrastructure is represented by deployments with NHS England, while clinical voice and agentic documentation platforms include ambient scribes Heidi Health and Tandem, both of which recently completed nine-figure Series B financing rounds. The operational advantage of this agile framework is reflected in deployments like digital physiotherapy platform Flok Health, which utilizes Scarlet to deploy validated clinical updates to its regulated medical device twice per month—an iteration velocity previously unachievable under legacy European Notified Bodies.
Capital Allocation and Global Expansion Strategy
The $50 million Series B injection will be deployed to broaden Scarlet’s international footprint and engineering capabilities. Geographically, the company is establishing dedicated operational hubs across the United States and the Asia-Pacific region to support cross-border software-as-a-medical-device clearance pipelines.
Scarlet will also expand its internal roster of specialized machine learning auditors, bio-engineers, and regulatory clinicians. Furthermore, the company plans to broaden its certification portfolios to cover emergent multimodal foundation models, autonomous diagnostic agent frameworks, and generative clinical reasoning tools.
