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STAT+: Colombia wins a key court ruling over a compulsory license issued for an HIV medicine

A South American court upheld the steps taken by the Colombian government when it issued a compulsory license two years ago for an HIV medicine, a move that confirmed the legal framework for using such an approach in the future.

The Court of Justice of the Andean Community — a tribunal that settles trade, intellectual property, and labor disputes for Bolivia, Colombia, Ecuador, and Peru — also ruled that the Colombian government had properly justified the reasons for issuing a license and appropriately set an expiration date for its license.

“The court concluded that Colombia did not incur a breach of Andean regulations, since such measures are valid when there are reasons of public interest,” the health ministry said in a statement. “Colombia adequately complied with the obligation to determine the duration of the compulsory license” for the medicine, which is sold by ViiV Healthcare.

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How HIV-1 Develops Resistance to Broadly Neutralizing Antibodies

One of the most challenging aspects of combatting HIV-1 infection is that the virus continually evades neutralizing antibodies. However, one consequence of this is that a small percentage of people with HIV-1 (1-5%) develop rare, broadly neutralizing antibodies (bNAbs) that can neutralize a large fraction of global HIV-1 isolates. These broadly neutralizing antibodies are among the most promising new long-acting HIV treatments, offering the potential to forego traditional daily dose of antiretroviral drugs. Indeed, a recent trial found that participants who received a single dose of two bNAbs maintained a nearly undetectable viral load for up to 20 weeks, and a third did so for about a year.

Despite the known promise of bNAbs, the pathways through which the virus escapes these antibodies remain incompletely understood across diverse HIV-1 strains.

“Knowing how different strains of the virus respond to leading bNAb therapies will greatly improve our ability to anticipate whether a particular therapy will be effective for individual patients,” says Paul Bieniasz, PhD, professor at The Rockefeller University and an HHMI Investigator. “And if we can identify broadly neutralizing antibodies that the majority of strains have great difficulty escaping from, we can create more robust treatments.”

Now scientists have established the most comprehensive view to date of how HIV-1 can escape bNAbs. Using thousands of parallel viral selection experiments combined with bioinformatic analysis and experimental validation, the team discovered viral mutations that make HIV-1 strains resistant to two bNAbs: 3BNC117 and 10-1074.

This work is published in Nature Microbiology in the paper, “Diverse paths to broadly neutralizing antibody escape among HIV-1 strains.“

The researchers sought to investigate the relationship between different HIV-1 strains and bNAbs collected from HIV infected persons. Only a handful of resistance mutations have been identified in a limited number of viral strains. The researchers wanted to expand that number to represent global viral diversity.

“No one has attempted to do this at such a scale before,” said Theodora Hatziioannou, PhD, research professor at The Rockefeller University.

The team developed an approach that would allow them to study the mutational pathways to escape among 15 strains of HIV-1 sourced from around the globe. The goal was to pinpoint the mutations that were contributing to each strain’s propensity to develop resistance.

“We found that most viral strains can escape bNAb neutralization, but there’s substantial variation in the likelihood that they will and the mechanisms that enable it,” says Alex Stabell, MD, PhD, an infectious disease physician and clinical scholar at The Rockefeller.

Stabell devised a pipeline that began by growing large amounts of virus in cell culture. The bulk populations were used to seed thousands of parallel selection experiments with varying concentrations of bNAbs. Viruses that were able to spread in the presence of the bNAbs were isolated and sequenced. Custom bioinformatic processing gave a list of putative resistance mutations, which were subsequently experimentally validated for each viral strain.

Using this method, called RISC (resistance identification via selection and cloning), the team found more than 100 bNAb escape mutations across the 15 viral strains tested, dramatically expanding the known number. Surprisingly, they found that in most cases, a single amino acid change may be enough to confer resistance. That turned out to be true for 12 of the 15 viruses tested against the 3BNC117 antibody and for all nine tested against 10-1074.

“It was striking that it’s actually quite easy for most HIV strains to escape these special antibodies,” Bienasz says. “But it’s not true for all strains—a handful Alex worked with needed multiple amino acid substitutions or unusual ways to replicate in order to escape.”

“The genetic barrier to resistance was higher for these viruses,” Stabell adds. “One of the goals of therapy these days is not simply to have therapies that are transiently effective, but to have this high genetic barrier.”

They also identified a surprising number of mutations occurring outside the epitope on the viral envelope recognized by bNabs that target the CD4 binding site, such as 3BNC117. (10-1074 aims for a more mutable envelope target, which may help explain why it’s easier to escape.) “These were quite prominent and unexpected,” says Hatziioannou. “No one would have predicted these would affect bNAb sensitivity.”

In the future, the team will use Stabell’s method to identify to discover resistance mutations to other bNAbs as well as to combinations of them.

“HIV-1 mutates so fast and the diversity in the population is already quite enormous, so we’ve long known that a multidrug approach is the best course of treatment,” Hatziioannou says. “We hope to identify combinations that potentially raise the genetic barrier to resistance and are therefore more effective.”

The post How HIV-1 Develops Resistance to Broadly Neutralizing Antibodies appeared first on GEN – Genetic Engineering and Biotechnology News.

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Factors Predicting Poor Outcomes in Hypertrophic Cardiomyopathy Uncovered

Five factors predicting death or serious complications in hypertrophic cardiomyopathy, a heart condition where the heart muscle becomes abnormally thick, have been uncovered in a study led by the University of Virginia.

“Hypertrophic cardiomyopathy, with a prevalence of one in 500 in the U.S., is the most frequent cause of sudden cardiac death in young individuals,” explain lead author Christopher Kramer, MD, a researcher at University of Virginia Health, in JAMA.

“Although some patients remain asymptomatic, others develop effort intolerance, exertional angina, progressive heart failure, atrial and ventricular arrhythmias, and sudden cardiac death.”

There is some disagreement about how best to predict risk in patients diagnosed with this condition, which is inherited in 60% of cases, with different factors used for assessment in different places and current guidelines focusing on sudden cardiac death risk and not other serious adverse events such as the risk for heart failure.

This study enrolled 2,698 hypertrophic cardiomyopathy patients from 44 sites across North America and Europe between 2014 and 2017 and followed them for an average of 6.9 years. The participants underwent wide ranging tests on enrollment including cardiac magnetic resonance imaging with core laboratory analysis, genetic testing of 36 cardiomyopathy genes, blood biomarker analysis, and detailed clinical assessments. Patients with pre-existing implantable cardioverter defibrillators, often prescribed to patients with this condition to avert sudden cardiac death, were excluded.

Patients were reviewed once a year by telephone, with an average follow-up time of around seven years. Records were reviewed if events occurred during the study.

Overall, 117 events—death, nonfatal sustained ventricular arrhythmias requiring cardioversion or defibrillation, left ventricular assist device implant or heart transplant—occurred in 104 participants during the follow up period.

Five factors were significant predictors of a poor outcome. These included the extent of scarring on the heart measured by imaging, heart muscle size, and heart chamber size with all three predicting worse outcomes with greater measures. The other two factors were history of heart failure and higher levels of a blood protein marker of heart stress, NT-proBNP.

“Current risk prediction guidelines for hypertrophic cardiomyopathy are imperfect, as they predict only sudden cardiac death, and not heart failure or other fatal and nonfatal cardiac adverse events,” said Kramer in a press statement. “This study is a major advance in that it provides evidence that incorporating these additional assessment methods better predicts risk of adverse outcomes.”

The team plan to continue this work and to develop a risk score as well as to seek external validation from independent databases and researchers using similar measures of risk.

The post Factors Predicting Poor Outcomes in Hypertrophic Cardiomyopathy Uncovered appeared first on Inside Precision Medicine.

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Slow-Growing Breast Cancer Cells May Explain Why Relapse Happens Decades Later

Researchers at Garvan Institute of Medical Research have identified a previously underappreciated mechanism that may explain why some breast cancers return many years, even decades, after apparently successful treatment.

The study, published in Nature Communications, reveals that certain estrogen receptor-positive (ER+) breast cancer cells survive therapy not by entering complete dormancy, but by continuing to divide at an extraordinarily slow pace. These stealth-like cells can gradually form microscopic secondary tumors that remain undetectable for years before eventually triggering metastatic relapse.

The findings offer new insight into one of the most persistent challenges in breast cancer care: why relapse can occur long after patients are considered cancer-free.

The long shadow of ER-positive breast cancer

ER-positive breast cancer is the most common subtype of breast cancer and is typically treated with hormone therapies designed to block estrogen signaling. These treatments are often highly effective at eliminating actively dividing tumor cells.

However, ER-positive disease has a unique clinical problem: recurrence risk persists for decades.

Even after five to ten years of endocrine therapy, up to 30% of patients can eventually develop metastatic relapse. Once breast cancer spreads to distant organs such as bone, lung, or brain, the disease becomes largely incurable.

Traditionally, relapse has been attributed to dormant cancer cells—cells that enter a state of complete hibernation before later “waking up.” But the new study suggests this may not be the only pathway.

“We have become very good at treating primary breast cancer, but late relapses remain a major challenge,” said Liz Caldon, associate professor and senior author of the study.

Not dormant—just incredibly slow

The researchers discovered that some breast cancer cells never fully stop proliferating during therapy. Instead, they survive by drastically slowing their rate of division.

This subtle distinction may be clinically critical.

Rather than entering complete cellular arrest, these cells continue to grow at an almost imperceptible pace, allowing them to evade therapies that primarily target rapidly dividing cells.

“Instead, they survive by growing extremely slowly in the background, until a tiny speck becomes a pebble,” Caldon explained.

Over many years, these microscopic lesions, known as micrometastases, can gradually expand until they become clinically detectable or disrupt vital organs.

The work challenges a long-standing binary view of cancer persistence in which tumor cells are considered either actively proliferating or fully dormant. Instead, the findings support the existence of an intermediate “slow-cycling” state that may be particularly effective at evading treatment.

Isolating the slowest cancer cells

Studying these rare cells was technically difficult because of their exceptionally slow growth.

The research team spent years isolating and cultivating these populations in the laboratory. Once established, they introduced the cells into preclinical models to determine whether slow proliferation impaired metastatic potential.

It did not.

Despite dividing slowly, the cells retained the ability to migrate throughout the body and colonize distant organs such as bone and lung.

“It took years to isolate these specific cells because they were dividing so slowly, almost in defiance of how we typically expect cancer to behave,” said Kristine Fernandez, first author of the study.

“These cells were migrating to organs like the bone and lungs, proving that speed isn’t everything when it comes to metastasis.”

The findings reinforce a growing understanding in oncology that aggressive cancer behavior is not solely defined by rapid proliferation. Cellular adaptability and survival under therapeutic pressure may be equally important.

Rac1 emerges as a potential therapeutic target

After identifying the slow-growing cells, the researchers investigated what allowed them to survive.

The study pinpointed a signaling pathway centered on Rac1, a protein involved in cell movement, structural organization, and survival. Using advanced biosensor imaging, the team directly visualized Rac1 pathway activation inside live slow-growing cancer cells.

Inhibiting this pathway appeared therapeutically promising.

Experimental Rac1 inhibitors significantly reduced tumor size and tumor number in patient-derived breast cancer models.

This suggests that targeting Rac1-dependent survival programs could potentially eliminate slow-growing residual cancer cells before they evolve into clinically significant metastases.

Rethinking cancer relapse biology

The findings contribute to a broader shift in cancer biology away from viewing residual disease as uniformly dormant.

Instead, tumors may contain multiple survival states, including cells that persist through continuous but ultra-slow proliferation. These populations may be especially dangerous because they remain biologically active while escaping conventional therapeutic detection.

The work also raises important clinical questions about long-term endocrine therapy. Current treatment durations are largely standardized, yet some patients may harbor persistent slow-cycling tumor cells despite years of therapy.

“If we can understand the specific biology of these slow-growing cells, we might eventually be able to offer better ways to track whether a decade of hormone therapy is actually working and ultimately prevent recurrence,” Caldon said.

Toward preventing late relapse

The study’s implications extend beyond breast cancer alone. Slow-cycling drug-tolerant cancer cells have increasingly been identified across multiple tumor types, including melanoma, lung cancer, and leukemia.

By identifying a concrete signaling mechanism underlying this state in ER-positive breast cancer, the research provides a potential therapeutic entry point for preventing relapse before metastatic disease emerges.

The next challenge will be determining whether Rac1 inhibitors, or similar approaches targeting slow-cycling survival programs, can safely and effectively eliminate residual cancer cells in patients.

If successful, such strategies could fundamentally alter how clinicians approach long-term relapse prevention in breast cancer, shifting the focus from simply suppressing visible disease to actively eradicating the hidden cellular reservoirs that remain years after treatment ends.

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Asthma Drug Formoterol Shows Potential to Reverse MASH

Researchers at the Medical University of South Carolina (MUSC) have found evidence that the asthma medication formoterol may reverse metabolic dysfunction-associated steatohepatitis (MASH), a progressive fatty liver disease associated with obesity and type 2 diabetes that can lead to fibrosis, cirrhosis, liver failure, and liver transplantation. The research, published in npj Metabolic Health and Disease, arose unexpectedly as a result of findings on the use of formoterol in mouse models of diabetic kidney injury, which also showed that the mice had low levels of liver fat accumulation.

“Kind of unexpectedly, we found that the liver damage also reversed,” said senior author Joshua Lipschutz, MD, division director of nephrology and Arthur Williams Endowed Chair in nephrology at MUSC.

Based on this observation, the MUSC researchers initiated a study to find out whether the beta-2 adrenergic receptor pathway targeted by formoterol could influence metabolic disease in the liver as well as the kidney. According to the researchers, the connection between the diseases lies in shared metabolic dysfunction associated with type 2 diabetes relating to mitochondrial dysfunction and impaired energy metabolism.

To test the hypothesis, the team used a high-fat diet mouse model designed to mimic MASH. Mice fed the diet for 16 weeks developed liver steatosis and were subsequently treated with formoterol for four weeks. Testing of the mice after the four weeks of treatment found that steatosis was largely resolved as a result.

The evidence showed that formoterol increased mitochondrial biogenesis, a process that increases the number and function of mitochondria within cells.

“It looked like formoterol was rescuing the injury by increasing mitochondrial biogenesis,” Lischutz said. “It kind of revs up the mitochondria so they work better.”

The researcher noted that mice treated with formoterol had increased levels of PGC1α (a protein that helps control how cells produce and use energy) and electron transport chain proteins, along with an increase in mitochondrial proteins and lower lipid accumulation in liver tissue. Human HepaRG liver cells exposed to free fatty acids also showed reduced lipid accumulation and increased after formoterol treatment.

“The coordinated induction of oxidative phosphorylation and amino acid metabolism pathways suggests that formoterol may promote metabolic competence through non-lipid sources, including amino acids,” the researchers wrote.

While there were no approved drugs to treat MASH when the MUSC researchers initiated their study, current treatments still remain limited with resmetirom and semaglutide the only current approved therapies for this condition. Both medications have shown only limited efficacy in a subset of patients and have known side effects.

“All the current drugs for diabetic nephropathy only slow progression, but they don’t reverse the damage. This drug actually reversed the damage at the histologic, ultrastructural, and functional levels,” said Lipschutz.

Further, formoterol is already an approved and established medication that has been prescribed for year to treat both asthma and chronic obstructive pulmonary disease (COPD). Because its metabolic effects in humans and its safety profile has been detailed in its approval for these conditions, it could hasten approval for these other therapeutic uses.

“If you can repurpose something that’s approved and already being used safely, that’s kind of our dream as physician-scientists,” Lipschutz added.

Lipschutz and colleagues are currently conducting a clinical trial for the use of formoterol in chronic kidney disease (NCT07022418). Future research will focus on what dosing levels would be appropriate to use as treatment for CKD and MASH, whether inhaled delivery would be effective, and how durable the response to this potential treatment could be.

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STAT+: Trump pivots on kratom derivative 7-OH, floating approval for some forms

President Trump on Monday suggested the federal government could move to approve some forms of 7-OH, an opioid derived from the naturally occurring kratom plant.  

“We’re looking very seriously at natural 7-OH and getting that approved,” Trump said. 

It was not clear what Trump meant by “natural 7-OH.” Small amounts of the compound, shorthand for 7-hydroxymitragynine, occur naturally in kratom, which is increasingly used as a recreational drug and an unapproved pain treatment. While kratom is significantly less dangerous than potent synthetic opioids like fentanyl or prescription pain pills, it can still cause addiction and overdose. 

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STAT+: Medicare’s miss on Alzheimer’s drug spending

This is the online version of STAT’s weekly email newsletter Health Care Inc. Sign up here.

Did you know the U.S. Mint requires gold coins to be made with American-made gold, but instead it gets illegally mined gold that can be traced back to a Colombian drug cartel? Truly mind-blowing stuff from this New York Times investigation. Let me know what the health care angle is on that one: bob.herman@statnews.com.

It’s tough to make predictions, especially about the future

Two years ago, my old pal Rachel Cohrs Zhang and I reported how Medicare’s actuaries predicted the new Alzheimer’s drug Leqembi would cost the program $3.5 billion in 2025. It turns out that prediction was way off.

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Three things in AI to watch, according to a Nobel-winning economist

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

A few months before he was awarded the Nobel Prize in economics in 2024, Daron Acemoglu published a paper that earned him few fans in Silicon Valley. Contrary to what Big Tech CEOs had been promising—an overhaul of all white-collar work—Acemoglu estimated that AI would give only a small boost to US productivity and would not obviate the need for human work. It’s okay at automating certain tasks, he wrote, but some jobs will be perfectly fine.

Two years later, Acemoglu’s measured take has not caught on. Chatter about an AI jobs apocalypse pops up everywhere from Senator Bernie Sanders’s rallies to conversations I overhear in line at the grocery store. Some previously skeptical economists have gotten more open to the idea that something seismic could be coming with AI. A California gubernatorial candidate said last week that he wants to tax corporate AI use and pay victims of “AI-driven layoffs.” 

On the one hand, the data is still on Acemoglu’s side; studies repeatedly find that AI is not affecting employment rates or layoffs. But the technology has advanced quite a bit since his cautious predictions. I spoke with him to understand if any of the latest developments in AI have changed his thesis, and to find out what does worry him these days if not imminent AGI.

AI agents

One of the biggest technical leaps in AI since Acemoglu’s paper has been agentic AI, or tools that can go beyond chatbots and operate on their own to complete the goal you give them. Because they can work independently rather than just answering questions, companies are increasingly pitching agents as a one-to-many replacement for human workers.

“I think that’s just a losing proposition,” Acemoglu says. He thinks agents are better thought of as tools to augment particular pieces of someone’s work than something malleable enough to handle a person’s whole job.

One reason has to do with all the various tasks that go into a job, something Acemoglu has been researching in his work on AI since 2018. For example, an x-ray technician juggles 30 different tasks, from taking down patient histories to organizing archives of mammogram images. A worker can naturally switch between formats, databases, and working styles to do this, Acemoglu says, but how many individual tools or protocols would an AI require to do the same?

Whether or not agents will supercharge AI’s impact on jobs will come down to whether they can eventually handle the orchestration between tasks that humans do naturally. AI companies are in heated competition to prove that their AI agents can work independently for ever longer periods without making mistakes, sometimes exaggerating the results—but Acemoglu says many jobs will be spared from an AI takeover if agents can’t fluidly switch between tasks.

The new hiring spree

For years Big Tech has been offering staggering salaries to recruit AI researchers. But I asked Acemoglu about a different hiring spree I’ve noticed: AI companies are all building in-house economics teams.

OpenAI hired Ronnie Chatterji from Duke University in 2024 to be its chief economist and announced last year that Chatterji will work with Jason Furman—Harvard economist and former advisor to Barack Obama—to research AI and jobs. Anthropic has convened a group of 10 leading economists to do similar work. And just last week, Google DeepMind announced it had hired Alex Imas, an economist from the University of Chicago, to be its “director of AGI economics.”

Acemoglu has noticed colleagues getting snatched up for these roles too. “It makes sense,” he says: AI companies are well aware that public skepticism about AI, in large part due to job concerns, is growing. And they have strong incentives to shape the economic narrative around their technology (consider OpenAI’s latest proposal for a new era of industrial policy).

“What I hope we won’t get,” Acemoglu says, “is that they’re interested in economists just to further their viewpoints or further the hype.” That tension hangs over the emerging field of “AI economics”; it’s concerning that some of the most influential research about AI’s impact on work may increasingly come from the companies with the most to gain from favorable conclusions.

AI apps

I don’t think of AI as hard to use; most of us interact with it via chatbots that use plain language. But Acemoglu says we should consider how it compares with the sort of software that kicked off earlier tech transformations, like PowerPoint for slide decks and Word for documents. 

“Anybody could install these on their computer and get them to do the things that they want them to do,” he says. They spread accordingly. 

“We have not seen the development of apps based on AI that have the same usability,” he says. Even if anyone can chat with an AI model, it tends to take a while for the average worker to get practical and productive use out of it. That’s part of the reason why AI has not yet shown any seismic impact on the job market or the economy. One of the key signals Acemoglu is watching, then, is the creation of apps that make AI easier to use. 

But he acknowledges that for a while, we’re going to see all sorts of conflicting evidence about AI: anecdotes that college grads are finding the job market worse and worse, but no noticeable effect of AI on productivity, for example. “There’s a huge amount of uncertainty,” he says. And that’s the most telling thing about the AI economy right now: the certainty of the rhetoric alongside the uncertainty of everything else.

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No FDA permission, no problem: New flavored vape policy worries experts

The tobacco industry chalked up another win on Friday with a new policy announced by the Food and Drug Administration that gives what one expert called a “get-out-of-jail-free card” to some manufacturers illegally selling e-cigarettes and nicotine pouches.

The FDA has a significant backlog of applications from the makers of vapes and nicotine pouches seeking authorization to sell their products. Some have gone ahead and put their products on sale anyway while awaiting word from the agency. In the new guidance, first reported by the New York Times, the agency said it will not prioritize cracking down on illegal sales under two conditions.

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Brain-Controlled Hearing Aid Singles Out Voices in a Crowd

Scientists at Columbia University have developed a brain-controlled hearing technology that allows users to amplify the conversation they are focusing on while reducing other voices. Published today in Nature Neuroscience, this study marks the first time this kind of technology has been tested in humans. 

“We have developed a system that acts as a neural extension of the user, leveraging the brain’s natural ability to filter through all the sounds in a complex environment to dynamically isolate the specific conversation they wish to hear,” said Nima Mesgarani, PhD, principal investigator at Columbia’s Zuckerman Institute and associate professor of electrical engineering at Columbia’s Fu Foundation School of Engineering and Applied Science. “This science empowers us to think beyond traditional hearing aids, which simply amplify sound, toward a future where technology can restore the sophisticated, selective hearing of the human brain.”

While modern hearing aids can amplify human speech while suppressing background noise, they cannot separate and enhance specific voices when multiple people are speaking. This can make it difficult for users to concentrate on a specific conversation in everyday scenarios such as restaurants, classrooms, busy workplaces, and family gatherings.

The hearing device developed by Mesgarani’s team mimics the way the human brain can naturally identify and focus on a single speaker out of many within a crowd. Previously, the researchers had found a way of identifying which brain signals are linked to a specific conversation, by matching the timing of peaks and valleys of the brain waves to the sounds and silences of that conversation. They also identified distinct patterns of brain activity that indicate which conversation a person is focusing on and which one they are filtering out. 

In the current study, the scientists developed a machine learning algorithm that could examine the user’s brainwaves and identify which conversation they are paying attention to in real time, making that voice louder and others quieter to make it easier to listen to. This system was tested on epilepsy patients who already had electrodes implanted in their brains. The electrodes were used to measure the user’s brain activity as they focused on two overlapping conversations played simultaneously, and the algorithm automatically detected which conversation they were trying to focus on. 

“The results mark an important step toward a new generation of brain-controlled hearing technologies that align with the listener’s intent, potentially transforming how people navigate noisy, multi-talker environments,” said Vishal Choudhari, PhD, who led the development and evaluation of the system.

More research will be needed before minimally invasive wearable systems can integrate this kind of brain sensing technology with advanced audio processing capabilities, especially to ensure they can accurately decode conversations in real time and in real-world scenarios where multiple voices can be heard. 

“The central unanswered question was whether brain-controlled hearing technology could move beyond incremental advances, towards a prototype that could help someone hear better in real time,” said Choudhari. “For the first time, we have shown that such a system that reads brain signals to selectively enhance conversations can provide a clear real-time benefit. This moves brain-controlled hearing from theory toward practical application.”

The post Brain-Controlled Hearing Aid Singles Out Voices in a Crowd appeared first on Inside Precision Medicine.