Background: Large language models (LLMs) have gained increasing popularity in medical education, with evidence supporting their educational value when framed through the lens of cognitive load theory. Source-based LLMs, which explicitly ground responses in user-uploaded material via retrieval-augmented generation algorithms, may offer additional educational value by using student-developed materials to conceptualize new areas of learning within a familiar framework. This has applications for areas like medical education in dermatology, which could benefit from inclusive sources and enhanced education to alleviate health care gaps. However, no prior studies have examined whether the inclusion of student-authored notes alters the response characteristics of a source-based LLM when responding to medical questions. Objective: This study aims to conduct an observational, comparative performance evaluation study assessing the accuracy, response reproducibility, and intermodel response similarity of freely available LLMs on text-only step 1 dermatology questions, and to explore whether providing extensive student-generated notes to a source-based LLM alters these performance characteristics. Methods: In December 2024, 4 LLMs were evaluated: NotebookLM (NLM) with uploaded preclerkship study guides (NLM w/ Notes), NLM with an uploaded blank sheet of paper (NLM w/o Notes), ChatGPT-4o Mini, and Google Gemini 1.5 Flash. Each model completed 3 trials of 121 text-based United States Medical Licensing Examination (USMLE) step 1 dermatology questions from the AMBOSS question bank. They were evaluated for overall majority-consensus accuracy, accuracy by question difficulty, intertrial reproducibility, and agreement in answer choice selection between models. Differences were analyzed through a Cochran omnibus test and subsequent pairwise McNemar tests with Benjamini-Hochberg correction. Response reproducibility and intermodel agreement were analyzed through Fleiss κ statistics with 95% CI. Results: ChatGPT-4o Mini achieved the highest overall majority-consensus accuracy (102/121, 84.3%). NLM w/ Notes demonstrated the highest intertrial reproducibility (Fleiss κ=0.927, 95% CI 0.875‐0.978) and strong performance on lower-difficulty questions but comparatively reduced accuracy on higher-difficulty items. NLM w/o Notes exhibited significantly higher omission rates (38/363, 10.5% vs ≤7/363, 1.92% for other models) than other tested LLMs. Sensitivity analysis excluding omissions increased NLM w/o Notes’ accuracy from 66.9% (81/121) to 77.8% (77/99), matching NLM w/ Notes’ accuracy of 74.4% (90/121). Intermodel agreement was significantly higher between NLM w/ Notes and ChatGPT-4o Mini compared to NLM w/o Notes and Gemini 1.5 Flash. Conclusions: Provision of student-generated notes substantially increased response reproducibility in a source-based LLM, likely reflecting consistent retrieval of similar source excerpts across trials. However, note-grounding appeared to constrain performance on higher-difficulty questions, suggesting a retrieval-augmented generation algorithm retrieval error when question stems excluded characteristic “keywords” present in lower-difficulty items. The results highlight potential challenges of a student-level, cognitive load theory–grounded educational LLM that must deal with notes not curated by experts, balance source use and internal reasoning, and meaningfully appraise uploaded sources to assess a student’s individual learning gaps.
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Mental Illness Shows Context-Specific Genetic Effects
Many DNA variants linked with neuropsychiatric disorders (NPD) that do not code for proteins depend on neuronal activation, a study suggests.
The findings, in Science, highlight the power of cell stimulation to reveal context-specific “hidden” genetic effects in conditions such as schizophrenia.
They suggest that genetic regulation is not fully revealed by measuring gene expression alone.
Instead, gene activity—at least in the brain—may depend on context and the physiological state of neurons.
“Liang et al. demonstrate that the genetic processes that underlie neuropsychiatric disease are heavily determined by a dynamic physiological environment rather than by fixed cellular conditions,” said Biao Zheng, PhD, and Panos Roussos, PhD, from Icahn School of Medicine at Mount Sinai in New York, in a Perspective article accompanying the study.
They added: “To understand disease genetics, we might need to study the genome in motion and not at rest.”
Genome-wide association studies have revealed hundreds of genetic loci associated with mental illness, with more than 280 identified for schizophrenia alone.
But many of these DNA regions do not encode proteins and their impact is often subtle and difficult to detect.
To investigate further, Lifan Liang, PhD, from the University of Chicago, and co-workers studied gene expression and chromatin accessibility in single neurons derived from induced pluripotent stem cells collected from a hundred human donors.
The single-cell multi-omics study involved assessing transcriptional and epigenomic profiles before and after neurons were activated through potassium-induced depolarization.
The team found that much of the activity in regulatory DNA regions only became apparent with neuronal stimulation.
Both the number of detectable expression quantitative trait loci (eQTLs)—genetic variants associated with differences in gene expression—and chromatin accessibility QTLs (caQTLs)—DNA variants associated with differences in chromatin accessibility—rose after neuronal stimulation.
Shared and cell type-specific transcription factors worked together, possibly through regulatory cascades, to drive cell type-specific neuronal responses to stimuli.
eQTLs after stimulation had substantially weaker overlap with brain eQTL catalogs derived from postmortem tissue compared with eQTLs before stimulation.
This suggested that many relationships between regulatory DNA activity and gene expression become detectable only during neuronal activation and could be missed by traditional tissue-based studies.
A higher number of caQTLs were associated with neuropsychiatric disease compared with eQTLs, suggesting that disease-associated genetic variants could have detectable effects on regulatory DNA even when downstream changes in gene expression were not obvious.
Supporting this, chromatin accessibility and transcriptional responses to neuronal activation often occurred at different times.
Regulatory regions associated with genes that respond rapidly to neuronal stimulation often remained accessible after transcription subsided. By contrast, some late response genes exhibited accessible chromatin before their expression was induced.
When taken together, these observations implied that chromatin accessibility can be an indication of both prior and future transcriptional potential.
“We identified thousands of cell type–specific and activity-dependent quantitative trait loci for gene expression (eQTLs) and chromatin accessibility (caQTLs), helping prioritize NPD risk variants and genes that manifested functional effects only upon neuronal stimulation,” the researchers asserted.
They added: “Our work provides mechanistic insights on neuron subtype–specific activity-dependent gene regulation, substantially expanding the repertoire of context-specific causal variants and genes for NPD and other brain traits.”
The post Mental Illness Shows Context-Specific Genetic Effects appeared first on Inside Precision Medicine.
Another roadblock for DOJ campaign against trans health
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The emergence of the web data infrastructure layer for AI
AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstructured, which limits its use by AI models.
To understand this challenge, consider the foundation of the web itself. The web was not designed for the automated discovery and retrieval that new AI applications demand. Overcoming this inherent design constraint requires infrastructure.
The next frontier in AI may depend on a new web data infrastructure layer that can enable models to discover and map this ever-expanding digital realm. This layer must be able to navigate hundreds of millions of existing web domains and billions of new URLs created each week, delivering real-time information and overcoming technical barriers.
“The data suggests there’s far more data out there,” says Or Lenchner, CEO of Bright Data, a web data collection platform. “Think of the universe: It’s out there, but you don’t know what you don’t know.”
Enabling access to fresh, relevant, and trustworthy data
While early AI breakthroughs were driven by scaling training data and model size, organizations are now encountering a fundamental bottleneck: They need to keep pace with the dynamic, unstructured, and constantly evolving nature of web data in order to ground outputs in current and verifiable information. AI performance increasingly depends not just on model architecture but on a system’s compute, networking, retrieval, and data engineering capabilities—that is, the system’s ability to quickly and reliably retrieve data that is fresh, relevant, and trustworthy.
Traditional model training relies on snapshots of information collected at a particular point in time. Training AI on such static data is no longer sufficient. To track fluctuations such as competitor pricing, consumer sentiment, and market trends, companies need a constant feed of new information, pulling data in real time along with relevant context. Their infrastructure must therefore be able to handle millions of simultaneous interactions across websites that vary by geography, language, format, and access rules.
“If it can’t retrieve real-time information, it lacks context,” Lenchner says. “In a business setting, that’s not acceptable anymore. Stale answers lead to bad decisions and disappointed consumers.”
Speed is not merely a matter of convenience; it’s a matter of necessity. Today’s organizations operate in environments where prices, inventory, markets, security threats, and customer behavior change continuously. Delayed data retrieval can reduce the usefulness of an otherwise sophisticated model.
Using live, high-quality web data can also reduce AI hallucinations because the model has a more relevant knowledge base. This builds user trust. In fact, one survey found that 56% of AI practitioners said businesses need access to real-time web data to improve trust in AI outputs. To ensure the model runs efficiently and effectively, the information must also be pared down to the appropriate essentials.
Despite the introduction of retrieval-augmented generation (RAG), where models pull in external data at the moment of a query, many AI systems still struggle to deliver outputs that are current, contextually relevant, and trustworthy in operational settings. According to Gartner, 60% of AI projects that are not supported by AI-ready data—accurate, structured, organized, and contextualized—will be abandoned by the end of the year.
This is because large-scale retrieval alone does not solve the problem. As Lenchner puts it, “You need to retrieve data at scale, but also in real time. Latency becomes an issue because of the end user who is waiting for the output.”
Accessing fresh, AI-ready data at scale introduces technical and structural challenges. In practice, many enterprise systems combine public web retrieval with APIs, licensed datasets, and proprietary internal data in their AI applications. Integrating these fragmented sources into a timely and usable knowledge layer requires specialized capabilities. Some research has found that 97% of AI organizations depend on real-time web data infrastructure, but 90% feel boxed in by various restrictions. Companies are increasingly developing technical approaches to navigate these constraints.
Lenchner draws this metaphor: “Think of the trained model as intelligence and relevant data as knowledge. A powerful intelligence layer sitting on top of a hollow knowledge layer is like a genius who knows nothing—useless in practice. Intelligence and knowledge have to come together.”
The promise of new infrastructure
A new layer of web data infrastructure can address this developing need for stronger AI inputs by enabling discovery of data, real-time access, and tailoring to a specific context. As Lechner describes it, “It’s all about collecting data at scale, super-low latency, without being blocked.”
Rather than relying on increased computing power, this type of platform emulates human browsing behavior to access available content and transform raw code into structured data feeds. It can work with websites that might not interact with traditional scraping tools, such as those heavy in JavaScript, or with aggressive antibot software.
As Lenchner explains, “It’s basically having infrastructure that can mimic a web user with identifying information—IP address, location, and 1,000 more parameters. And at scale. Think of doing that 80 billion times a day for millions of websites. And every single time, you are looking exactly as the website expects you to look.”
Of course, continuous retrieval introduces new data governance challenges. To address them, platforms can enforce strict compliance protocols aligned with global privacy frameworks, such as the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). They can also be limited to openly accessible, public information, avoiding paywalls or private logins. Any networks used can be vetted and consent-based, and incentives can be provided to owners of IP addresses. In this way, systems can be designed to comply with tightening regulation.
Such complex capabilities do not come easy. “When this is critical infrastructure for a company,” Lenchner says, “doing it in-house becomes a full-time engineering problem that competes with the actual AI work.” Addressing this complexity requires organizations to commit significant resources, leading many to seek specialized platforms designed specifically for data retrieval, orchestration, and observability.
Infrastructure for the real world
Real-time data retrieval is changing what AI systems can do inside organizations. For example, a retail company can use public information to enable a dynamic pricing engine, and global brands can track trademark infringements.
As the ecosystem matures, organizations that invest in this emerging data infrastructure layer will be better positioned to build AI systems that are more responsive, reliable, and aligned with real-world conditions—AI systems that can continuously adapt using current web data. Over time, the distinction between AI models and the infrastructure that feeds them may even begin to disappear.
As Lenchner says, “The world is changing. And everything that is happening in the world is being uploaded to the public web. The amount of new data that is being generated is growing and accelerating.”
To learn more from Bright Data, read the Data for AI 2026 report.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
Stripe, Anthropic, and OpenAI are backing an effort to stop respiratory infections
The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles.
Now the payment company Stripe, founded by brothers Patrick and John Collison, says it will fund a new $500 million nonprofit whose goal is preventing both the common cold and the flu. Its eventual aim is to get rid of respiratory viruses altogether.
The new organization, called Intercept, will use grants and investments to back prevention approaches, including vaccines, as well as large-scale air-cleaning systems for schools, offices, and other public spaces.
In addition to Stripe, other funders include Anthropic, Flu Lab, and the OpenAI Foundation, as well as Bill Gates and several traders at the quantitative investing fund Jane Street Capital, according to an Intercept spokesperson.
“I think we treat respiratory infections as a minor nuisance, but have really underweighted the burden that they impose on society,” says Nan Ransohoff, the Stripe executive leading the initiative along with Charlie Petty, a venture capitalist who joined Stripe this year. On average, people spend 5% of their lifetime fighting a cold or the flu, according to Ransohoff.
Despite that, drug companies put relatively little effort into preventing colds. Part of the problem is that the sniffles are caused by more than 200 different viruses, according to the American Lung Association, with rhinoviruses being the most common culprits. There are so many that it typically doesn’t pay to try to stop any one of them with a vaccine. “When pharma companies look at it, it’s not as attractive as other things they could work on,” says Ransohoff. “So it hasn’t attracted the resources.”
Stripe previously organized a $1.8 billion program called Frontier to encourage the development of carbon removal technology, as a way of countering climate change. Ransohoff says removing carbon from the atmosphere and getting rid of respiratory viruses are similar in that each is “technically possible” but they “lack commercial incentives.”
The concept for Intercept took shape after Ransohoff started talking to David Veesler, a structural biologist and vaccine designer at the University of Washington, who argued that it’s possible to come up with broad countermeasures that work against many viruses at once.
“He effectively sort of nerd-sniped me,” Ransohoff says of Veesler. “He convinced me that this is technically possible. He also helped me understand that some of the reasons that this hasn’t been done before was sort of an incentive problem.”
Veesler says the growing tool kit available to scientists includes RNA drugs, antibodies, and computational protein design. For instance, one idea is to engineer virus-grabbing proteins that people could spray in their nasal passages, to catch viruses before they cause infection.
“Most people just accept these viruses as a fact of life, and that got us thinking: Do we have to accept it?” says Veesler. “The more we thought about it, the more we realized that many of these problems have not been worked on with modern technologies.”
The project takes inspiration from efforts to fight the covid-19 virus, where Veesler’s group was among those involved in the speedy development of vaccines, antiviral drugs, and antibodies.
According to Ransohoff, Intercept’s advisors will include Peter Marks, a former top FDA official, as well as Moncef Slaoui, the pharmaceutical executive who led the US coronavirus vaccine effort, Operation Warp Speed.
A key challenge for Intercept will be coming up with ways to counter many viruses at one time. That accounts for the interest in air-cleaning technology, such as using strong ultraviolet light to inactivate viruses. The idea, the group says, is to remove them from the air in the same way municipalities remove impurities from the water supply before it’s piped to people’s homes.
The US funds about $6.5 billion a year in virus research through the National Institute of Allergy and Infectious Disease, or NIAID. But that agency’s budget hasn’t grown in recent years, leaving more room for private philanthropy.
And Stripe’s Collison brothers have become some of the most reliable philanthropists in viral research. After giving away “fast grants” to help labs during the covid-19 pandemic, they later joined other donors who committed $650 million to establish the Arc Institute in Palo Alto, California, which has developed AI models for biological research.
“The diversity of viruses is just too large and seems daunting, so people don’t even try,” says Veesler. “I’m happy that someone is ready to help scientists, not accepting the status quo, and doing something different.”
Drug Targets LDL Receptor Pathway to Control Cholesterol
Cholesterol-related heart disease remains the leading cause of death worldwide, and while doctors have more tools than ever to treat it, many patients still can’t achieve safe cholesterol levels or can’t tolerate the side effects of available medications. Researchers at the University of California (UC), San Diego, School of Medicine have now uncovered a hidden biological pathway, dependent on a protein known as Ral, which explains why high-cholesterol diets steadily chip away at our body’s ability to clear harmful low-density lipoprotein (LDL) cholesterol from the blood. The team‘s preclinical study, including tests in mice, also identified a drug candidate already proven safe in humans that could potentially target the pathway.
“We’ve known for a long time that a high-cholesterol diet reduces the liver’s ability to clear cholesterol from the blood, but we didn’t fully understand why,” said Alan Saltiel, PhD, professor of medicine at UC San Diego School of Medicine and director of the UC San Diego/UCLA Diabetes Research Center. “This new discovery explains a critical piece of that puzzle.” Saltiel is senior author of the researchers’ published paper in Nature, titled “Dietary cholesterol activates a Ral-dependent pathway driving LDLR turnover,” in which they concluded, “Together, our findings reveal a Ral-dependent signalling pathway as a key regulator of LDLR turnover and cholesterol homeostasis.”
Disruptions in cholesterol homeostasis are closely linked to an increased risk of atherosclerosis and cardiovascular disease (CVD), the authors wrote. “Elevated low-density lipoprotein cholesterol (LDL-C) significantly contributes to CVD by promoting the formation of atherosclerotic plaques in arteries.”
The liver is the main organ involved in removing cholesterol from the blood so it can be broken down and used elsewhere. This is done through LDL receptors (LDLRs), which sit on the surface of liver cells and act like docking stations, grabbing LDL cholesterol from the bloodstream and pulling it inside the cell for processing. “LDLRs have a crucial role in the uptake of LDL-C from the circulation by hepatocytes,” the investigators continued. The more LDL receptors on liver cells, the more cholesterol gets cleared from the blood, which is why most cholesterol-lowering drugs, such as statins or PCSK9 inhibitors, work by preserving or increasing the number of these receptors. However, the team noted, such treatments have their limitations. “The molecular switches that coordinate LDLR trafficking and turnover in response to nutritional cues, including high dietary cholesterol, remain poorly defined.”
The new research, carried out in mice and in human cells, reveals a previously unknown mechanism that quietly works against the cholesterol removal process, slowly reducing the number of LDL receptors and contributing to high blood cholesterol. The team found that this process begins when a protein called Ral—which Saltiel has previously studied in fat cells—is activated by high dietary cholesterol. “We describe here a previously unrecognized role for Ral signaling in orchestrating LDLR cellular trafficking and lysosomal routing in hepatocytes under chronic cholesterol stress,” the team stated.
Their studies showed that the more Ral is activated, the fewer LDL receptors remain available to clear cholesterol from the blood. This depletion process ultimately relies on a lysosomal protease enzyme called cathepsin A (CTSA). They further explained, “Ral engages the endocytic RalBP1–REPS1 complex to promote LDLR internalization and lysosomal routing, where LDLR is degraded by the lysosomal protease cathepsin A (CTSA).”
The researchers also found that blocking CTSA with a selective small molecule inhibitor (SAR164653) was enough to stabilize LDL receptors and dramatically lower circulating LDL cholesterol in mice. “Pharmacological inhibition of CTSA activity increases hepatic LDLR function and improves cholesterol clearance, offering a potential new therapeutic strategy for hypercholesterolaemia and cardiovascular disease,” they stated.
“There’s still a real need for new cholesterol-lowering options, since some people can’t get to safe levels even with the drugs we have now,” said Saltiel. “This new pathway we discovered is completely separate from anything that existing drugs target, so it gives us a new opportunity to fill that gap.”
After a fundamental biological breakthrough, it typically takes significant additional research to find drugs that target it. However, in this case, a CTSA inhibitor has already been through the early stages of drug development, with the initial goal of treating heart failure. While it was eventually shelved for strategic reasons, the drug had previously advanced to a Phase I clinical trial, where it was successfully tested for safety.
This discovery suggests that the investigational drug is already ready for testing in a Phase II trial for high cholesterol. “Luckily, there’s an experimental drug sitting on the shelf that’s already been shown to be safe in humans,” said Saltiel. “We hope to test whether this might be effective by conducting a clinical trial, which could potentially bring a new treatment option to patients much sooner than would have been expected.”
The post Drug Targets LDL Receptor Pathway to Control Cholesterol appeared first on GEN – Genetic Engineering and Biotechnology News.
Leveraging Self-Reporting in an Existing e-Cohort to Identify Clinically Relevant Mitral Valve Prolapse: Pilot Questionnaire Study
Background: Mitral valve prolapse (MVP) is a common valvulopathy associated, in a minority of cases, with heart failure, severe mitral regurgitation (MR), and sudden arrhythmic death. Digital tools hold promise for faster and more efficient recruitment of study participants into a large-scale MVP Registry. Objective: This study sought to evaluate the feasibility of surveying participants in an existing e-cohort to identify and clinically characterize MVP cases based on self-reporting and to recruit them in an MVP Registry at the University of California, San Francisco. Methods: We surveyed Northern Californian participants of the Health eHeart Study, a large e-cohort using the Eureka digital research infrastructure, about a prior diagnosis of MVP. MVP-positive respondents were asked to provide relevant medical records to confirm their eligibility and were invited to enroll in an MVP Registry if evidence of MVP was confirmed. A follow-up survey was sent after 1 month and after 5 years to collect data about clinical outcomes, including arrhythmias and the need for mitral valve repair. Results: The survey was delivered to 5746 participants, and 520 completed responses were collected. A prior diagnosis of MVP was self-reported by 16.3% (85/520) of respondents. Echocardiograms were obtained from 51.8% (44/85) of participants, and evidence of MVP was confirmed in 32.9% (n=28) of individuals, all of whom joined the registry. Participants with more severe MR had a higher number of correct responses regarding both MVP (odds ratio [OR] 10.58, 95% CI 3.58‐63.04; <.001) and MR diagnosis (OR 4.86, 95% CI 2.11‐16.14; =.002). Longitudinal data were available from most patients through responses to a follow-up survey sent 1 month and 5 years later (18/28, 64.3% and 17/28, 60.7% of MVP confirmed respondents, respectively). Among the patients with electronic health records available, 75% (3/4) had a correct self-reported diagnosis of arrhythmia. Conclusions: e-Cohort methods with self-reported clinical data can be used to prescreen candidates for a research study of MVP. These methods can rapidly identify and retain, among many cases of benign MVP, the minority with clinically relevant presentations such as significant MR and ventricular arrhythmias. These cases may be missed, especially when asymptomatic, by small-scale clinic-based recruitment or family screening methods.
First-in-Human Stem Cell Therapy Trial for Huntington’s Disease Begins at UCI Health
The world’s first in-human embryonic stem cell-derived clinical trial for Huntington’s disease has launched at UCI Health, the clinical arm of the University of California, Irvine. The Phase Ib/IIa trial will evaluate the safety of hNSC-01 neural stem cells derived from embryonic stem cells delivered to the brain by a specialized neurological mapping and targeting stereotactic system.
Huntington’s disease is a fatal, progressive genetic disorder that gradually destroys brain cells. It usually begins between the ages of 35 and 50 with symptoms that include involuntary movements, difficulty thinking and planning daily tasks, and mood changes such as depression. If successful, this therapy could prolong independent living and significantly reduce long-term care costs.
“This clinical trial highlights the important role that an interdisciplinary academic and clinical team together with the HD families, plays in advancing medicine,” said Leslie M. Thompson, PhD, professor of psychiatry and human behavior at UC Irvine. “We are grateful to our patients and their incredible families for their bravery to provide hope for others with very few options.”
The first patient received the intervention at UCI Health Irvine (home to Orange County’s first adult bone marrow/stem cell transplant and cellular therapy program) in May. A second patient is scheduled to receive the intervention in July.
“The first patient intervention went very well. To date, they haven’t reported any serious adverse events,” said Ravi Rajmohan, MD, UCI Health neurologist. “This trial may help us move one step closer to a future with available treatments that could potentially slow the progression of Huntington’s disease.”
The therapy, hNSC-01, uses pluripotent neural stem cells derived from embryonic stem cells, which were manufactured through the UC Davis GMP facility. In animal studies, the cells have been shown to protect existing brain cells, replace lost cells, rebuild impaired brain circuits, release helpful proteins, such as brain-derived neurotrophic factor (BDNF), and reduce harmful protein accumulations that damage brain cells. The stem cells were also shown to be safe over long periods in mice.
The clinical trial will enroll 21 people ages 18 to 65 with early-stage Huntington’s disease. Twelve participants will be enrolled into a Phase Ib dose-escalation group and nine in a Phase IIa expansion group.
The stem cells are implanted during a roughly six-hour surgical procedure done under general anesthesia. While lying face down in an MRI scanner, the patient receives stem cells implanted directly into the striatum deep in the brain, using a purchased proprietary therapy-enabling platform for navigation and surgical delivery. Damage to the striatum, which is responsible for motor control, decision-making, motivation and more, causes Huntington’s disease symptoms. Subjects will be closely monitored for safety as well as preliminary signs of potential benefit.
The clinical trial is made possible by a $12 million grant from the California Institute of Regenerative Medicine (CIRM), and the trial is coordinated through the UC Irvine Alpha Clinic.
The post First-in-Human Stem Cell Therapy Trial for Huntington’s Disease Begins at UCI Health appeared first on GEN – Genetic Engineering and Biotechnology News.
STAT+: U.S. health spending rose sharply in 2025, thanks to GLP-1 use and more care
Americans are seeing their doctors, getting hospital procedures, and filling prescriptions more frequently than economists and budget experts anticipated. Weight loss drugs, in particular, have morphed into their own special category of spending and are pushing budgets across the country to their limits.
Combining an increased amount of care with the country’s high baseline of prices has resulted in the health care system taking up more of the economy, new data show — findings that again reflect people’s widespread discontent with how unaffordable health care has become.
The country spent $5.7 trillion on health care in 2025, a 7.3% increase from 2024, according to the latest government figures published in the journal Health Affairs on Wednesday. That amounted to almost $16,500 per person.
BIO 2026: CEO Calls for U.S. Biotech Urgency and International Competitiveness
SAN DIEGO — Biotechnology is entering one of the most transformative periods in its history. But, according to Biotechnology Innovation Organization (BIO) CEO John Crowley, outdated regulations, rising development costs, and global competition threaten to slow progress unless policymakers act.
At the 2026 BIO International Convention in San Diego this week—which drew “roughly 20,000 attendees,” according to the organizers—Crowley outlined a vision for the future of biotechnology centered on accelerating clinical research, embracing artificial intelligence, and maintaining U.S. leadership in a rapidly evolving global bioeconomy.
The grassroots gauntlet
Crowley’s personal journey as a father shaped his path into biotechnology. In the late 1990s, two of his children were diagnosed with a rare form of muscular dystrophy. He left Bristol-Myers Squibb’s marketing department to co-found a biotechnology company with an Oklahoma academic researcher over scientific progress.
The struggle to get funding was immense. Crowley reflected on his first BIO convention in 2000 amidst the excitement of the Human Genome Project: “I came and there were tens of thousands of people partnering as there is today, still a quarter of a century later. Being the 31-year-old CEO of a small startup in Oklahoma City with no money, literally nobody signed up to meet with me and nobody accepted my meeting request.”
Crowley recalled going to the main stage, where a gentleman, rendered quadriplegic through a horse accident, came out on the stage and said, “Biotechnology—it’s a great big word that just means hope. It’s my hope that someday I can hold my wife’s hand on the beach or throw a ball to my kids.”
Crowley, empty-handed, returned to Oklahoma City and was able to scrounge up the funds for his startup, Novazyme Pharmaceuticals, which was ultimately funded by home equity loans and credit card advances to develop rare disease treatments. Just one year later, Novazyme was acquired by Genzyme Corporation for $225 million.
The experience engrained in Crowley two main concepts: first, developing therapeutics doesn’t always start in big pharma but, rather, often has grassroots origins; second, and relatedly, it’s an almost impossible battle for anyone outside of big pharma to fight.
“That’s the way so much of our science happens,” Crowley said. “It comes out of great universities, and it’s a scientist and entrepreneur—and increasingly, families, patients, and patient advocates—leading the way and going through the whole journey, running that gauntlet of making medicines.”
Modernizing clinical trials and accessible AI
To achieve the vision of maximizing the development and reach of biotechnology, Crowley identified a handful of problems, including the need to change the current system of clinical trials. Crowley praised the FDA’s new “Project Trailblazer” initiative to modernize experimental therapy human testing. He argued that clinical trials have become excessively burdensome and costly, limiting innovation and delaying patient access to new treatments.
Over the past year, Crowley and BIO have worked with regulators and industry stakeholders to identify development bottlenecks. “The FDA needs to continue to be the gold standard of the world,” he said, while emphasizing that modernization is necessary to make the agency a stronger “beacon of innovation.” BIO has proposed several reforms, including measures designed to streamline trial approvals and improve the efficiency of regulatory review.
Describing recent discussions among BIO’s board of directors, which includes executives from both major pharmaceutical companies and small biotechnology startups, Crowley said there were two major strategic topics that emerged that dominated the conversation: China and AI.
For AI, the question wasn’t about whether it could revolutionize biotechnology; rather, it had to do with making AI capabilities accessible to companies of all sizes. Crowley noted a major disparity. “Our biggest companies have the resources and the focus to think about AI. They’ve got hundreds or more people focused on this. Our small companies don’t have those resources,” he said.
Crowly continued, “It’s also a challenge because in our industry we would work on such long timelines, and it’s hard for an entrepreneur and biotech of a small or a mid-sized company who’s invested years to get to…starting Phase III, and all of a sudden you’ve got this massive disruptive technology. That’s exactly what AI is going to be.”
The solution, according to Crowley, is for BIO to be at the forefront to enable the rapid implementation of AI into drug development paradigms, clinical trials, and the regulatory review process.
Challenging China
Crowley’s most stressed point was that the United States must remain competitive against growing international rivals, particularly China. “Drug development has just gotten too costly and burdensome, and it takes too much time,” said Crowley. In this [global] bioeconomy where we need to compete and outcompete countries like China, these are reforms that are needed.”
He characterized biotechnology as a matter of national security and argued that the United States should treat the industry as a strategic asset. While supporting bipartisan efforts in Washington to strengthen domestic biotechnology capabilities, he cautioned against policies that could create unintended consequences or limit access to potentially life-saving technologies.
“The world is a better, safer, healthier, and more prosperous place when the United States and its allies continue to lead in biotechnology,” Crowley said.
China has identified biotechnology as a strategic priority through multiple national development plans and has invested heavily in scientific infrastructure, manufacturing capacity, and research capabilities. Crowley argued that the most effective response is not isolation but improving the competitiveness of the U.S. innovation ecosystem.
Crowley repeatedly returned to what he described as “man-made problems” holding the industry back. While scientific challenges will always exist, Crowley said barriers such as complex regulations, insufficient research funding, delays in patient access, and rising out-of-pocket healthcare costs are obstacles that policymakers can address. “We can’t come to this convention and cure every cancer,” he said. “But if we get together with policymakers and lawmakers, we can pretty quickly solve a lot of these man-made problems if we have the will.”
50 years down, 50 years ahead
As biotechnology celebrates more than 50 years of innovation, Crowley argued that the industry’s future will depend not only on scientific breakthroughs but also on its ability to modernize the systems that govern how those breakthroughs reach patients.
“I hope you see, when you’re here at this convention, that it captures that entrepreneurial spirit,” said Crowley. “It has to be grounded in great science and research, and it’s an exciting time to be in biotech, not just reflecting about all our successes and our many failures and challenges along the way in 50 years and looking out in the months, years, and next 50 years about what biotechnology can do to extend and enhance life and to alleviate an enormous amount of human suffering.”
With advances in gene editing, genomic medicine, artificial intelligence, and cell therapies accelerating simultaneously, Crowley believes the next era of biotechnology could surpass anything seen before—provided the industry can remove the barriers standing in its way.
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