A mother in New York State who claims to oppose vaccines because of her Catholic faith lost an emergency appeal to the Supreme Court of the United States (SCOTUS) this week—though Justices Samuel Alito and Neil Gorsuch said they would have granted her application. For now, the woman’s kindergarten-aged son must be vaccinated to attend school.
For a child bursting with energy, few things are more fun than hurtling through a bouncy castle, launching into the air, and ping-ponging between every surface. But that childhood buoyancy will quickly deflate when it turns out those surfaces are smeared with a hypervirulent, multidrug-resistant pathogen.
That was the horrifying reality for a community in Ireland in fall 2025. Neighbors had gathered for an afternoon of merriment, complete with a barbecue, a sweets station, and three bouncy castles. Officials estimate that about 120 people joined the festivities, and around half of them were children and teens. Within a day, some children began developing signs of an infection. In all, 48 children in the community developed aggressive skin and soft-tissue infections.
Of the 48 cases, 33 were treated by their regular doctor, and 15 sought emergency care. Four children ended up being hospitalized. Luckily, all of the children recovered. The results of the outbreak investigation were reported this week in the journal Eurosurveillance.
Argonne researchers study the movement of dust particles from concrete surfaces during a simulated radiological contamination scenario, measuring how pedestrians and moving cars affect the spread of the particles.
Every year, MIT Technology Review puts together a list of some of the brightest and best young minds working across science and technology. Our 35 Innovators Under 35 are the ones to watch—people whose research and technical work stands to shape the future of their fields.
This year, the list includes nine people who are transforming biotech. And this week, I’m going to give you a taste of some of the very cool stuff five of them are working on, which includes lifesaving innovations and groundbreaking “age reversal” tech.
1. Preventing maternal deaths
Let’s start with Paschal Kija, a 28-year-old who has developed a device to treat postpartum hemorrhage—a dangerous birth complication that contributes to around 29% of maternal deaths in his home country, Tanzania. The Mkanda Salama (“Safe Wrap” in Swahili) is easy to use and costs just $70. A study found that it stopped postpartum bleeding in 73% of women within 20 minutes.
2. Making brain electrodes inspired by Japanese art
For decades, scientists have been developing, testing, and implanting brain electrodes. These devices are literally inserted into people’s brains, so while they can help us understand brain activity and treat various neurological disorders, it’s not totally surprising that they can also cause a bit of damage. Xiao Yang, 34, is working on ultra-small electrodes, which she hopes will have less of an impact on surrounding brain tissue. Her electrodes are flexible, too—in fact, they look a lot like actual neurons.
Yang is also creating sheets of electrodes to study brain cells in the lab. Inspired by kirigami—the traditional Japanese art of cutting paper to form three-dimensional shapes—she’s created a sheet of electrodes with a honeycombed structure shaped like a spiral basket. And she’s already using it to study brain cells.
3. Developing an all-new treatment for baby KJ
In 2024, Kyle “KJ” Muldoon Jr. was born with a rare and potentially fatal genetic disorder. Sarah Grandinette was a member of a team that developed an entirely new, personalized treatment for him—a gene-editing therapy essentially designed to correct a genetic misspelling.
Grandinette, who is now 26, created cells with KJ’s genetic variant and used them to screen gene-editing approaches; then she tested potential medicines in mice and monkeys. KJ ultimately got his first dose of the resulting treatment when he was about seven months old. He responded well and was eventually discharged from hospital. He’s “doing pretty great,” she says.
4. Reversing the aging process to treat eye disease
The buzziest tech in longevity right now centers on reprogramming—attempts to rewind the age of cells by resetting them to a more embryonic-like state. In a study published in 2020, Yuancheng (Ryan) Lu (now 34) and his colleagues showed that a reprogramming therapy reversed vision loss in aged, blind mice. Now an almost identical version of that therapy is being tested in people with eye disease. Life Biosciences, the company developing the drug, dosed its first volunteer in June.
5. Using AI to design new viruses
Last year, Samuel King used a generative AI model to come up with new genetic blueprints for bacteriophages—teeny viruses that can infect bacteria. Once he had those blueprints, he printed them out as strands of DNA. In experiments, he found that those AI-designed viruses could create new copies of themselves, burst out of bacterial cells, and infect other nearby bacteria. Viruses aren’t alive, but King, 27, hopes that AI-designed life forms might one day be used to make drugs or soak up pollution.
You can read more about these innovators, and the others on the biotech list, here.
This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.
Fears that modern electronic devices may harm children are nothing new. Gadgets with screens of any size have long been allegedly melting, rotting, and/or corrupting the brains of youths for decades. However, a medical case report published this week offers a new and alarming way our digital doodads may cause physical harm.
In BMJ Case Reports, two UK doctors, Mara Znagoveanu and Edward Artley, report the case of a boy who came to an emergency department with alarming marks on his abdomen. The marks were described as being in a patch about 15 centimeters (6 inches) wide, made of flat, reddish-brown "interlacing lines forming irregular circles and a lace-like morphology." A picture of the marks is here.
Mysterious marks
The boy, whom they described only as being in "mid-childhood," was not in any pain, and the rash was not warm to the touch or tender. He and his parents said they couldn't think of any recent injuries or trauma that might explain the marks. He was otherwise healthy, hadn't recently been ill, and had no systemic symptoms, such as fever or fatigue. Everything about the boy's health, growth, and medical history looked normal.
The entrance of major AI companies into healthcare is a meaningful and welcome development, accelerating the technical foundation available to the industry.
Their models are increasingly capable of processing long clinical records, interpreting complex terminology, comparing documentation against evidence and generating coherent summaries from large volumes of information. For clinicians, operators, and administrative teams who spend significant time searching through fragmented data, these advances are helping reduce cognitive burden and make high-value information easier to access.
But healthcare leaders should not confuse model capability with operational capability.
Healthcare’s administrative challenges are caused by fragmented information, fragmented workflows, and fragmented accountability, not a lack of information. The industry has spent decades investing in systems that capture activity: electronic health records, billing platforms, payer portals, scheduling systems, call center platforms, and analytics applications. Each system records something important. But few were designed to reason across the full chain of decisions that determines whether patients get timely access, clinicians have the right documentation and providers are reimbursed appropriately.
This is the problem that AI must now confront.
Revenue cycle is becoming one of healthcare AI’s proving grounds
The revenue cycle is the process healthcare providers use to get paid for care — from scheduling and registration through coding, billing, payer follow-up, and payment collection.
It is unusually suited to rigorous AI deployment because it combines high transaction volume, complex reasoning, structured and unstructured data, measurable outcomes, and significant operational variation. It also sits at the intersection of financial performance, patient access, and administrative workload.
A single claim can be influenced by patient insurance information, clinical documentation, coding rules, payer-specific policies, prior authorization requirements, medical necessity criteria, and many other data sources and operational processes. A breakdown in any one of those areas can create downstream consequences weeks or months later.
This is why generic automation has often fallen short.
Traditional robotic process automation works well when workflows are stable and rules are predictable, but healthcare administration is neither. Payer requirements change. Documentation expectations evolve. Exceptions are common and often material.
Large language models improve part of the equation, extracting meaning from narrative text, summarizing records and supporting reasoning over complex documentation. But when used alone, they inherit important limitations. They may produce plausible outputs without sufficient traceability. They may lack awareness of local workflow constraints. They may miss payer-specific history or context that determines whether an action is likely to change an outcome.
Why foundation models will become necessary but insufficient
The major AI firms are solving real technical problems for healthcare.
Better context windows make it easier to process longitudinal records. Stronger reasoning improves the interpretation of complex clinical scenarios. Better multimodal capabilities may eventually help connect text, imaging, structured data, and clinical signals in more useful ways. Safer model behavior and healthcare-specific tuning will continue to improve adoption.
These capabilities will make healthcare work faster, more consistent and easier to navigate. But they will not, on their own, solve deep-rooted administrative complexity.
Much of healthcare’s operational knowledge does not live in general medical literature, coding manuals, or public payer guidance. It lives in the accumulated experience of what actually happens after decisions are made. For example:
Why does one appeal strategy outperform another?
Which documentation gaps are most likely to cause reimbursement delay?
How does a specific payer respond to a particular clinical argument?
These insights are behavioral, operational, and longitudinal. They emerge from years of transactions, outcomes, exceptions, and human judgment.
As foundation models become more capable, access to baseline healthcare knowledge will become less differentiating. Most leading systems will be able to interpret ICD-10 codes, recognize medical terminology, summarize payer policies, and reason over public clinical criteria. The durable advantage will come from how organizations combine that model intelligence with proprietary operational data, structured knowledge, workflow context, and governance.
The technical shift: From automation to orchestration
Agentic orchestration turns foundation model understanding into coordinated action — intelligence that can follow work across systems, apply the right rules, adapt when something changes, and keep learning from what happens next.
A prior authorization workflow, for example, may require retrieving clinical documentation through fast healthcare interoperability resources (FHIR) APIs, mapping patient history to payer criteria, identifying missing evidence, generating a submission packet, routing exceptions to a specialist, monitoring payer response, adjusting patient care pathways, and learning from the outcome.
This type of workflow requires coordination. It also requires guardrails: regulatory requirements, privacy standards, clinical policies, coding rules, payer criteria, and organizational risk thresholds. One promising approach is hybrid architecture that combines LLMs with structured knowledge bases, symbolic logic, reinforcement learning, and deterministic validation layers.
At Ensemble, this is the design principle behind EIQ, our revenue cycle intelligence engine. EIQ brings together operational activity, clinical documentation, payer behavior, and reimbursement outcomes into a continuously learning intelligence layer that’s integrated with the hospital’s electronic health record (EHR). It supplements the system of record with a system of intelligence, designed to connect information and surface actions most likely to improve outcomes.
EIQ uses a neuro-symbolic approach that combines LLMs and custom small language models with rules-based reasoning. That architecture is built on one of the most robust datasets in healthcare, informed by more than a decade of award-winning operational performance, transaction history, payer behavior, and operator decision-making. The language models help interpret information and generate human-readable outputs. The symbolic layer represents policies, rules, payer requirements, and workflow constraints so the system can apply guardrails, make reasoning steps more traceable and recommend actions that fit the specific operational context.
What the next decade will reward
The contribution of major AI firms to healthcare will be significant. Their models will become faster, safer, more capable, and more accessible.
But the next decade of healthcare AI will be defined by integration, not model capability alone.
The organizations that create the most value will be those that connect models to governed data, operational workflows, domain expertise, human oversight, and measurable outcomes. They will understand that healthcare intelligence cannot live in a separate interface. It has to exist inside the decisions that shape access, documentation reimbursement, and patient experience.
This content was produced by Ensemble. It was not written by MIT Technology Review’s editorial staff.
Labor Day is in the rearview mirror, kids are back to school, and a squall of pumpkin spice is upon us. It's that time again to prepare for the equally inevitable respiratory virus season with annual vaccines.
With fervent anti-vaccine activist Robert F. Kennedy Jr. as the country's top health official, it might seem like the rollout of this year's shots could be a disaster. For instance, one of Kennedy's first actions as health secretary last year was to obliterate an ad campaign for flu shots amid a particularly deadly flu season. As we head into this fall, the Centers for Disease Control and Prevention's vaccine advisory committee—which normally sets vaccination recommendations and insurance coverage for the shots—is nonfunctioning. A federal judge ruled in March that the anti-vaccine allies Kennedy installed on the panel were illegally appointed and unfit to serve. All their changes to vaccine policy have been temporarily voided. And meanwhile, Kennedy spent last week trying to obscure the number of babies who died from measles so far this year (it was two, including a newborn).
Big picture
Despite all of that, the fall vaccine effort is looking like it will likely be somewhat smooth, potentially unremarkable even. The Food and Drug Administration has approved updatedflu and COVID-19 shots for this season. Those shots have already begun arriving at pharmacies—in case your pharmacy hasn't already sent you multiple texts and reminders. While there are still some snags for access, it seems like it will be a lot like last year's fall vaccine rollout.
Cofertility manages the costs of egg freezing and storage, in exchange for half the batch. One young client became suspicious of the arrangement—and started to investigate.
Yuancheng (Ryan) Lu is obsessed with aging. And with eyes. As he steps outside the Whitehead Institute in Cambridge, Massachusetts, his aviator glasses darken automatically in the sun. Age-related blindness runs in his family. A great-aunt in China, the story goes, was killed crossing a road because she couldn’t see oncoming traffic. And Lu’s own 23andMe test came back with a mutation for macular degeneration, a top cause of vision loss in old age. Exposure to bright sunlight is another risk factor—thus the shades. “They protect me,” he says. “Plus, they look cool.”
Lu, 34, works on gene therapies to prevent age-related vision loss. “I think the eye is a really unique system to study aging and rejuvenation,” he says. “I could give a whole presentation.” Pushing up my reading glasses, I lean in to listen.
Lu is behind one of the coolest results in rejuvenation science—and in eye research. In 2018, while earning his PhD at Harvard Medical School, he used an age-reversal technique called reprogramming to repair the optic nerves of mice. He crushed the nerves, blinding the animals, and then injected the cells with a gene therapy meant to restore them to a youthful state. Sixteen days later, the nerves were growing back, their axons showing up through a microscope as spidery orange filaments.
As hype around age reversal swirls, Lu has been busy in the lab searching for what he calls “the next generation of rejuvenation therapies.”
The head of that lab, the longevity scientist David Sinclair, remembers when Lu texted him the pictures: “He asked me, ‘What do you see here?’ And I said, ‘I see the future.’” Later tests carried out in a box with rotating bars of light showed the mice were tracking the changes. They could see again.
This year, nearly the exact genetic therapy Lu created for mice entered human clinical trials. On June 9, the startup Life Biosciences, which Sinclair cofounded and in which Lu owns a small stake, announced it had injected the treatment into the eye of a person with glaucoma. The trial has been big news. A headline in the New York Times suggested the technology could “change humanity.” Posters on X gushed, with one declaring that “the fountain of youth is here.”
“It’s remarkable that what he developed as a student is now going into humans,” says Sinclair of the treatment, now called ER-100. “It’s barely even changed since he built it.”
Reprogramming refers to an age-restoring process that takes place inside an embryo. It’s why babies are born young, not old: The DNA they’ve inherited from their parents has been scrubbed and reset. In 2006, Japanese researchers showed they could cause the process to occur in the lab by introducing just four key genes, known by the acronym OSKM. Add these to a cell from a 100-year-old and it will turn into a stem cell that acts as if it was plucked from an embryo.
That’s powerful stuff. But we don’t want to turn people into blobs of stem-cell protoplasm. Lu figured out a way to control the effect. He trimmed the list of genes to just OSK—leaving out M, for Myc, the one most likely to cause dangerous changes like cancer. His extra flash of insight was that reprogramming could be tested on the optic nerve; the eye is particularly accessible.
Lu’s result, published in Nature in 2020, helped set off an investment rush. Since then, US tech billionaires have placed huge bets on private companies like Altos Labs and NewLimit to explore reprogramming and anti-aging medicine. The day I spoke with Lu, he’d spent the morning meeting with the business magnate Zhong Shanshan, one of China’s richest people.
Still, as hype around age reversal swirls, Lu has been notably absent from the public conversation. He’s been busy in the lab searching for what he calls “the next generation of rejuvenation therapies.” With a sigh, Lu describes the grueling effort over the last six years to understand what OSK really does. The treatment remains toxic to many cell types, and he says it’s becoming obvious that different factors drive aging in each kind. This year, for example, he identified a gene responsible for protecting the retina from damage by free radicals—the main cause of age-related macular degeneration.
While Sinclair, his former boss, believes humans could live to be 200, Lu disagrees. There’s just too much that goes wrong as we age. His work with OSK, he says, was more a proof of concept than a silver bullet. But it did change the conversation. “Six years ago, you couldn’t talk about rejuvenation. We didn’t use that word—there was pushback,” Lu tells me. “But I think people have accepted the concept that you can really reverse molecular age.”
A six-week-old baby girl in Lancaster, Pennsylvania, died from measles, the county coroner confirmed to local press on Friday.
Stephen Diamantoni, a Republican elected coroner in 2007, told Lancaster Online that the baby died at home. "I believe it was the 18th of August," he said.
He also noted that the baby had a genetic condition called Amish lethal microcephaly, in which babies are born with unusually small heads and underdeveloped brains. The condition is caused by a mutation in the SLC25A19 gene, which codes for a protein involved with energy-producing enzymes in the mitochondria and is thought to be important for brain development. About 1 in 500 babies in the Old Order Amish population of Pennsylvania is born with the condition. Infants with the disorder only survive for about six months.
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