08/14/2026  |  Moe Alsumidaie  |  The Clinical Trial Vanguard

https://www.clinicaltrialvanguard.com/article/article-deep-dive/ai-clinical-decision-support-is-everywhere-the-evidence-base-is-not/ 

Imagine a site coordinator at a large academic medical center pulling up a patient’s chart in the middle of a Phase 3 oncology trial. Before she can complete her standard assessment, an AI-powered clinical decision support alert fires: elevated sepsis risk, recommended intervention, confidence score of 87%. She hesitates. The alert is generated by a vendor tool deployed hospital-wide — not validated against the specific patient population enrolled in her trial, not listed in the protocol, and not mentioned anywhere in the IND. She acts on it anyway, because the system is woven into the EHR workflow and declining the recommendation requires a three-click override that the nursing staff has been quietly skipping for months. The resulting intervention changes the patient’s concomitant medication profile. The deviation goes undocumented. The data gets locked.

That scenario is not hypothetical. According to a 2024 survey cited by Dialog Health, 71% of US hospitals now report using predictive AI integrated directly into their EHRs — up from 66% in 2023. These systems generate risk scores, flag deteriorating patients, recommend treatments, and shape clinical workflows in real time. They are present in the rooms where trials are running. And the clinical trial infrastructure built around GCP, protocol compliance, and data integrity has almost no coherent framework for handling them.

The central tension of this moment is not that AI decision support tools are unproven. Some of them work. The problem is that the evidence machine required to validate, monitor, and regulate these tools at scale simply cannot keep pace with the speed of commercial deployment.

The Regulatory Gap Is Already Showing
The FDA has been trying to get ahead of this. In April 2023, the agency published its Draft Guidance on Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence and Machine Learning-Enabled Devices — a document that acknowledges, implicitly, that AI systems are not static. They drift. They update. Their performance in the real world degrades relative to the conditions under which they were initially validated. The guidance asks sponsors to pre-specify how their AI will change and how those changes will be monitored. Reasonable in theory. Operationally ambitious at a scale that the agency itself is struggling to resource.

The FDA’s own enforcement record is beginning to show the consequences of that lag. On April 2, 2026, the agency issued what is believed to be the first warning letter directly tied to AI misuse, targeting Purolea Cosmetics Lab for deploying AI agents to generate cGMP documents — including drug product specifications and master production records — without adequate human review or validation of the AI outputs. The cited violation: failure to validate the AI system before relying on it for critical manufacturing decisions. The principle generalizes directly to clinical trial operations. If you are using an AI tool to support clinical decisions in a trial setting, and you cannot demonstrate that the tool was validated against a population and context comparable to your enrolled subjects, you have a protocol compliance problem with a data integrity wrapper around it.

What makes the Purolea warning letter significant is not its subject matter. It is its logic.

The FDA is signaling that reliance on AI outputs, without traceable validation, constitutes a GCP-equivalent failure — regardless of whether the tool was designed for manufacturing, clinical care, or trial operations. Sponsors running studies at sites where hospital-deployed AI tools are woven into standard workflows need to understand that those tools are now part of their regulatory exposure, whether or not they appear in the protocol.

When the Evidence Catches Up — Partially
There is at least one data point that shows what rigorous AI decision support evaluation looks like when it is done properly. A trial published in Nature Medicine followed over 9,600 patients across 16 primary care clinics in Kenya, testing a generative AI tool called “AI Consult” that was integrated into an EMR and provided real-time diagnostic and treatment suggestions to clinicians. The study found measurable improvements in clinician decision quality — not just process efficiency, but actual clinical decision accuracy. That is a meaningful result, and the trial design deserves credit: prospective, site-controlled, with a defined primary endpoint tied to clinical outcomes rather than user satisfaction scores.

But the Kenya trial also illustrates the limitation of the current evidence base. It was conducted in a specific resource-constrained setting, with a specific EMR, at 16 clinics, in one country. The moment you try to generalize that finding to a US academic medical center running a sponsored oncology trial across seven sites in four states, you are extrapolating well beyond the validation envelope. That extrapolation is happening every day, in procurement offices and hospital C-suites, without the clinical evidence infrastructure to support it.

The performance degradation literature makes the stakes clearer. A study published in New England Journal of Medicine AI, using a UK cardiac surgery dataset collected from 2012 to 2019, found that five machine learning models — including XGBoost and Random Forest — exhibited measurable performance drift over time as the underlying patient population and practice patterns shifted. Models that were accurate under 2012 conditions became demonstrably less reliable by 2019 without retraining. This is not a software engineering problem. It is a continuous evidence generation problem. And continuous evidence generation requires trial infrastructure, monitoring protocols, and regulatory oversight that the current system was not designed to provide.

What Sponsors Must Actually Do
The common assumption in the sponsor community is that AI decision support tools are the hospital’s problem — procured and deployed by health systems, governed by those health systems, and therefore outside the sponsor’s GCP obligations. That assumption is wrong, and it will generate CRLs.

Consider the operational reality at most multi-site trials today. A sponsor contracts with a CRO that monitors a network of sites. Those sites are embedded in health systems that have independently deployed AI tools across their clinical workflows. The AI alert that fires in the EHR during a protocol visit does not know it is operating inside a clinical trial. It fires because the patient meets a risk threshold. The site coordinator either acts on it or overrides it. Either action can affect trial data. Neither action is currently captured in most data management plans, protocol deviation logs, or risk-based monitoring frameworks.

The interoperability layer compounds this. Research published in AI (MDPI) on the FHIR-RAG-MEDS system demonstrates that HL7 FHIR-integrated AI can pull patient-specific data and generate guideline-concordant recommendations with impressive accuracy in controlled conditions. But “controlled conditions” in a research paper and “conditions present at Site 14 in rural Ohio” are not the same environment. FHIR standardization is incomplete across real health systems, meaning AI tools at different sites within the same trial may be operating on structurally different data inputs — generating non-comparable recommendations that systematically bias the treatment experience across arms without leaving any audit trail.

Sponsors who want to get ahead of this need to take three concrete steps before the next site activation. First, add an AI environment assessment to your site feasibility questionnaire — explicitly ask which AI-powered clinical decision support tools are active in the EHR, what patient populations they cover, and whether they generate alerts that could affect enrolled subjects’ care. Second, work with your medical monitor to define a protocol deviation category for AI-influenced clinical decisions, with a threshold for what requires documentation. Third, if your protocol is being run in a therapeutic area where AI tools are already commercially deployed — sepsis, cardiac risk, readmission prediction — consider adding a site-level AI tool inventory as an ongoing monitoring deliverable, reviewed at each co-monitoring visit.

The CMS 2024 Final Rule, effective January 1, 2024, allows Medicare Advantage plans to use AI to approve claims without human oversight — which means the financial incentives for health systems to deploy more AI, faster, are now structurally embedded in reimbursement. Sites will not slow AI deployment to accommodate trial governance timelines. The tools will proliferate regardless. The question facing every sponsor and CRO is whether their trial infrastructure will adapt before the FDA starts issuing 483 observations that explicitly reference AI-influenced data.

Back to that site coordinator with her finger hovering over the override button. She is not making a bad decision. She is making the only decision her workflow allows, inside a system that was designed for efficiency, not for the evidentiary requirements of a Phase 3 trial. The protocol says nothing about the AI alert. Her supervisor says nothing about the AI alert. The monitoring plan says nothing about the AI alert. When the data lock comes and the FDA reviewer pulls the audit trail, the intervention will be there, the concomitant medication change will be there, and the rationale will be missing — because no one in the trial’s governance structure ever asked the question that the evidence base is only beginning to force into view.

References

1. Nature Medicine — “AI decision support is scaling-up fast — can the evidence keep up?”
2. Dialog Health — “AI Healthcare Statistics: Hospital Trends in the US, 2024”
3. U.S. FDA — “Artificial Intelligence in Software as a Medical Device,” including April 2023 Draft Guidance on Predetermined Change Control Plans
4. GMP Compliance — “Use of AI Agents Leads to the First FDA Warning Letter Relating to AI,” April 2, 2026
5. University of Birmingham — “AI clinical support tool improved clinician decisions in real-world primary care trial,” 2026
6. PMC / NEJM AI — “Performance Drift in Machine Learning Models for Cardiac Surgery Risk Prediction,” UK dataset 2012–2019
7. MDPI AI — “FHIR-RAG-MEDS: HL7 FHIR and LLM Integration for Clinical Decision Support”
8. Super Lawyers — “Understanding Your Rights: Guardrails for AI in Medicare Coverage Decisions,” CMS 2024 Final Rule

08/14/2026  |  Black Doctor

https://blackdoctor.com/lecanemab-alzheimers-drug-clinical-trial/ 

Sally Osmer jumped at the chance to be treated with the cutting-edge Alzheimer’s drug lecanemab.

Osmer has a family history of the disease and was diagnosed with early-stage Alzheimer’s at age 74. She didn’t notice any problems at first, but imaging and genetic testing confirmed the diagnosis.

“When I got the diagnosis, it was pretty devastating,” she said in a news release. “The prospect of having a slow decline but being physically healthy is very frightening. We were fortunate to catch it early, and I was pleased to begin treatment.”

Osmer is one of hundreds of patients who’ve shown that the new Alzheimer’s drug is as safe in the real world as it was in the clinical trials that led to its approval in July 2023, a new study says.

Some experts were concerned that lecanemab (Leqembi) would cause swelling and bleeding as it flushed toxic amyloid proteins from patients’ brains.

“There’s been a lot of fear about this medication, especially around brain swelling and bleeding,” said lead researcher Dr. Andrew Liu, an associate professor of neurology and pathology at Duke University School of Medicine in Durham, North Carolina.

Real-world results show that the drug’s safety and effectiveness among patients aligns closely to results from clinical trials, researchers said.

“What we found is that, in the real world, with careful selection and close monitoring, approximately 80 percent of patients are able to remain on lecanemab for at least one year,” Liu said in a news release. “Importantly, most treatment-related side effects resolve over time without the need for additional medications or hospitalizations.”

What the Study Found
For the study, researchers tracked 230 patients treated with lecanemab at Duke between 2023 and 2025. The patients all had early Alzheimer’s disease or mild memory impairment.

Results showed that 79 percent of patients who started the treatment were able to continue it for more than a year. The 21 percent who dropped the drug did so mostly due to side effects.

About a quarter of the patients (24 percent) developed Amyloid Related Imaging Abnormalities (ARIA), signs of brain swelling or bleeding that show up in MRI scans.

Osmer has now completed more than a year on lecanemab, without any serious side effects.

“It’s been very uneventful in terms of side effects,” she said.

Osmer said the treatment has provided a great deal of reassurance in her day-to-day life.

“I have dealt with a lot of anxiety about my current life and the future,” she said. “Being on lecanemab definitely gives me a sense of hope and a promise for a better future than we’ve assumed about Alzheimer’s in the past.”

Researchers found that people carrying the Alzheimer’s disease risk gene APOE4 were about four times as likely to develop ARIA.

However, seven other common tests could not reliably predict who would develop ARIA while taking lecanemab, researchers said.

The team currently is working on an AI-driven imaging tool intended to help detect subtle ARIA changes earlier and more consistently in brain scans.

“Cerebral amyloid angiopathy (CAA), a condition characterized by silent buildup of amyloid in the brain’s blood vessels, is present in over 50 percent of all Alzheimer’s patients, and is one of the mechanisms thought to underlie ARIA,” senior researcher Dr. P. Murali Doraiswamy said in a news release. He’s a professor of psychiatry and behavioral sciences and medicine at Duke.

“Our study highlights the urgent need to develop better tests to predict who will develop serious ARIA and to know when it is safe to resume treatment,” Doraiswamy said.

Researchers did emphasize that lecanemab does not cure Alzheimer’s disease or reverse symptoms, but can slow its progression.

“This is about buying time in a disease that takes it away,” Liu said. “And our real-world experience shows that with careful risk-benefit assessments, time can be gained by many patients.”

What the Real-World Results Mean for Black Patients
Black Americans face a disproportionate burden of Alzheimer’s disease and related dementias. Yet Black patients have historically been underrepresented in Alzheimer’s research and clinical trials. When researchers conduct clinical trials for Alzheimer’s to evaluate new treatments, it’s important for them to understand whether they work as expected across populations ultimately receiving them.

Real-world studies can help researchers identify how treatments perform in broader patient populations, but they don’t answer whether every population has equal access to the treatment.

Why Representation in Alzheimer’s Clinical Trials Matters
Representation matters at every stage of clinical trials for Alzheimer’s disease:

• Who gets studied: Clinical trials need participants from diverse racial and ethnic backgrounds to understand if and how the Alzheimer’s drug might work differently.
• Who gets diagnosed: A patient can’t benefit from an Alzheimer’s treatment if the disease isn’t identified early enough to consider treatment.
• Who gets treated: Even after FDA approval, patients — especially Black patients — may encounter barriers involving specialists, testing, insurance coverage, transportation, infusion centers, and follow-up monitoring.

The study data on lecanemab is particularly relevant because the treatment is intended for people with early Alzheimer’s disease, making timely diagnosis and evaluation important.

What This Means for People Considering Alzheimer’s Clinical Trials
Participating in an Alzheimer’s clinical trial can be beneficial for some individuals. If you’re thinking about joining one, use this checklist as a guide to find the right trial for you:

• Ask what Alzheimer’s drug is being studied.
• Ask what the eligibility criteria are.
• Ask what patient monitoring looks like — such as visits, scans, cognitive testing, or other procedures.
• Ask about risks and benefits of participating.
• Ask what happens after the trial.

08/14/2026  |   Laurel Oldach/Max Barnhart  |  c&en (Chemical&Engineering News)

https://cen.acs.org/biological-chemistry/biotechnology/human-trial-chemogenetic-brain-therapy/104/web/2026/08 

Chinese researchers are testing DREADDs, a gene therapy to turn down neuronal activity, in the clinic

“Stunned silence.”

That’s how Bryan Roth of the University of North Carolina School of Medicine described the mood at a US National Institutes of Health Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative meeting in Bethesda, Maryland, this week when he told fellow attendees about at least seven clinical trials in China that are testing chemogenetic therapies in humans.

Twenty years ago, Roth developed the chemogenetic technology the trials are using, which is based on a group of proteins called “designer receptors activated by designer drugs,” or DREADDs. Designer drug is a bit of a misnomer in this case; the receptor being used in the Chinese trials responds to a small-molecule drug, clozapine, used to treat schizophrenia. But the designer receptor is much more sensitive to the drug than any human receptor, binding to it with picomolar affinity.

A researcher can introduce the gene encoding the receptor protein to a small group of neurons using a viral vector. Then, when the receptor is expressed and binds to the drug, it suppresses neuronal signaling in those cells and any brain circuits they belong to.

Dirk Trauner, a biochemist at the University of Pennsylvania who works on optogenetics, a related technology, says that DREADDs offer “a more precise knife” that, theoretically, could have reduced side effects compared with other approaches. Small molecules targeting endogenous receptors can have off-target effects when those receptors are expressed in other parts of the brain or when the molecules trigger closely related receptors; in contrast, DREADDs appear only where they are introduced.

The designer receptors have become a widespread research tool in neuroscience, where they have enabled researchers to alter brain circuits’ activity. But until now, they have not been used in the clinic.

“Over the years, folks have approached me to commercialize the technology, but there were all these barriers,” Roth says. “I think nobody wanted to take the risk.”

About 2 months ago, a rumor about designer proteins being introduced to treat brain diseases sent Roth and a postdoctoral scholar looking in clinical trial databases in the US and China. They found seven studies, which investigate intractable epilepsy, Parkinson’s disease, and neuropathic pain.

For several of the diseases in question, the therapy of last resort is to remove a portion of the brain, Roth points out. Chemogenetic treatment might avoid that, though if the treatment ended up having unwanted side effects, trial patients might seek relief through surgery after all.

Three of the DREADD trials use an adeno-associated virus as a vector to deliver the chemogenetic therapy. Gene therapies using viruses, such as these, carry the risk of serious, sometimes fatal immune reaction. Several people died recently in early-stage gene therapy trials in China. But Roth points out that six of the studies appear to have begun some months after the first epilepsy trial began, suggesting that investigators might have started after getting some indication that the gene therapy may be safe.

Jacques Carolan, a neuroscientist at University College London who was at the BRAIN Initiative meeting, posted on X on Friday, “If we needed more evidence that China is ahead in neuro, this is it.”

C&EN has reached out for comment to the investigators of record on the clinical trials.

According to Roth, the study with the greatest potential focuses on trigeminal neuropathic pain, which can be debilitating enough that it is a risk factor for suicide. “If that trial is successful, then it opens the way basically to circuit-based therapeutics for virtually all neuropsychiatric diseases,” he says.

08/14/2026 | Saúde Digital News

https://saudedigitalnews.com.br/14/08/2026/inteligencia-artificial-acelera-o-desenvolvimento-de-dispositivos-medicos-e-ja-integra-a-rotina-de-78-dos-medicos-brasileiros/ 

Technology is also reshaping research and development processes

While much of the debate regarding artificial intelligence in healthcare focuses on patient care, an equally significant transformation is taking place behind the scenes of innovation. Today, algorithms play a role in medical device development from the initial research stages, helping researchers design, simulate, test, and refine technologies even before the first prototypes are built. They can also anticipate risks, reduce development steps, and accelerate processes that previously relied exclusively on laboratory or clinical testing.

This transformation is already engaging regulatory bodies. In 2025, the U.S. Food and Drug Administration (FDA) published a draft guideline titled *Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations*. This was the first comprehensive guideline addressing the full development lifecycle of AI-enabled medical devices.

The publication outlines recommendations for the development, documentation, validation, and monitoring of these technologies throughout their entire lifecycle—from model conception to post-market surveillance—reflecting a new approach to evaluating devices capable of continuous evolution.

In Brazil, the Federal Council of Medicine published Resolution No. 2,454 in February 2026. This resolution regulates the use of artificial intelligence in medicine and establishes standards for AI-supported medical practices, aiming to foster technological development and the efficiency of medical services in a safe, transparent, and ethical manner. Advances in research are proceeding in parallel with the growing adoption of AI by healthcare professionals. This is according to the study "Overview of AI Use in Healthcare: Physician and Patient Perspectives," conducted by the Afya Research & Innovation Center in partnership with the Conexa Research Center, which surveyed 551 physicians and 511 patients.

78% of Brazilian physicians already use artificial intelligence in clinical practice, primarily for drug research, clinical decision support, and staying up to date with scientific developments.

From research to patient: AI accelerates innovation even before the first prototype

Long before the final product is reached, artificial intelligence is already part of engineering and applied research. Computational models analyze vast amounts of data, simulate thousands of scenarios in just a few hours, and allow for the virtual testing of different configurations prior to manufacturing the first prototypes. This expands teams' analytical capabilities, reduces development stages, and steers experimental studies toward the most promising alternatives.

According to Prof. Dr. Luciana Almeida-Lopes—a researcher, president of the Nupen Foundation, and consultant for the DMC Group—this shift significantly expands research teams' capabilities. "Artificial intelligence does not replace scientific research or clinical studies. It accelerates extremely complex stages of development, allowing researchers to explore a far greater number of possibilities before the first prototype is even built."

From behind the scenes to clinical practice

The advances achieved during development are already beginning to be felt in clinical practice. In some cases, AI can assist in defining therapeutic parameters, reducing variability in equipment settings, and supporting clinical decision-making—always backed by scientific validation and professional oversight.

"Artificial intelligence can organize a massive volume of information and transform it into support for clinical practice." "The benefit lies in making complex processes more consistent and predictable, while preserving the professional's central role in determining the course of action," highlights Luciana.

Smart devices require a new regulatory logic

The incorporation of artificial intelligence also changes the logic behind medical device development. Unlike conventional technologies, AI-based systems can evolve over time, incorporating new evidence and improvements whenever technical validation and regulatory backing are in place.

This characteristic requires a shift in perspective for the industry and regulatory bodies, which must now monitor not only the device's initial approval but also its performance throughout its entire lifecycle. "The challenge isn't getting the algorithm to learn more. It’s ensuring that every evolution of the technology remains backed by scientific evidence and maintains the same safety standards expected of any medical device," the expert explains.

This shift helps explain the publication of the new FDA guideline, which expands the regulatory focus to cover the entire device lifecycle and reinforces aspects such as data quality, traceability, documentation, and continuous monitoring.

The future depends as much on solid evidence as it does on robust algorithms.

As artificial intelligence advances, the quality of the data used to develop these technologies becomes increasingly important. Representative and scientifically validated clinical datasets are crucial for reducing bias, enhancing algorithm reliability, and ensuring consistent device performance across diverse patient profiles.

This evolution mirrors a broader shift in the relationship between healthcare professionals and artificial intelligence. Trust in the technology grows when it serves as a support tool, while clinical judgment and decision-making responsibility remain in human hands. This is also the likely path for the next generation of medical devices, as Dr. Luciana points out.

"In medicine, every innovation must answer the same question: does it improve patient care? Artificial intelligence accelerates the journey to that answer, but it is ultimately science—underpinned by clinical evidence and regulatory validation—that determines which technologies are truly safe and effective," she concludes.

08/14/2026 | Isabella Tardelli Maio/Giovanna Vitor | Le Monde Diplomatique Brasil

https://diplomatique.org.br/movimento-antivacina-politica-desinformacao-e-desafios-a-saude-publica/ 

The narratives used to justify refusing vaccination are diverse, and the decline in vaccination coverage has raised concerns among public officials, health professionals, and society at large. What factors contribute to the strengthening of the anti-vaccine movement, considering its historical trajectory, contemporary methods of dissemination, and its impact on public perception regarding vaccination?

Introduction

According to research conducted by the Laboratory for the Study of Information Disorder and Public Policy (DesinfoPop/FGV, 2025), Brazil accounts for 40% of all anti-vaccine content circulating in Latin America and the Caribbean. This figure is particularly significant given the observed drop in vaccination coverage in recent years and prompts reflection on the factors contributing to rising vaccine hesitancy and the spread of vaccine-related disinformation. The survey indicates that, over the last decade, the country has been responsible for the circulation of more than 580,000 pieces of anti-vaccine content within online communities.

The narratives used to justify refusing vaccination vary widely. The study identified claims linking vaccines to alleged risks such as "sudden death," "poisoning," "autism," and even alterations to human DNA. Generally, this content relies on information taken out of context, misinterpretations of rare adverse events, or claims lacking scientific backing. Despite this, such content reaches a substantial audience and contributes to shaping negative perceptions regarding immunization. The mapping conducted by the researchers analyzed over 81 million messages published between 2016 and 2025 across 1,785 digital communities spanning dozens of countries[1].

Although vaccine resistance is not a new phenomenon, the expansion of digital social networks and the growing circulation of misinformation have given the problem a new dimension. In Brazil, this process took on specific characteristics during and after the COVID-19 pandemic, as scientific debates became heavily intertwined with political and ideological disputes. In this context, understanding the rise of the anti-vaccine movement and its impact on vaccination coverage is crucial for formulating health communication strategies and strengthening public immunization policies.

International context: the origin and reconfiguration of anti-vaccine movements

Since ancient times, various techniques have been developed to combat diseases and reduce their impact on populations. However, immunization via vaccination is a relatively recent practice in human history. Broadly speaking, vaccination involves introducing an antigen into the body to stimulate the immune system to produce defenses against a specific infectious agent. In the case of smallpox—one of the deadliest and most contagious diseases ever recorded—it was observed that individuals who survived the infection acquired protection against future exposure. Based on this observation, practices emerged that sought to artificially induce this immunity[2].

One of the earliest forms of immunization was variolation, developed in China around the 10th century. The method involved using material taken from the lesions of infected individuals—usually ground into a powder—to induce a milder form of the disease and, consequently, generate future protection. Although risky by modern standards, the technique represented a significant advance in the fight against the disease[3].

Eight centuries later, the research of British physician Edward Jenner paved the way for the development of the first modern vaccines. Upon observing that rural workers who had contracted cowpox appeared to be protected against human smallpox, Jenner hypothesized that exposure to the bovine disease might confer immunity. To test this, in 1796, he inoculated an eight-year-old boy with material from cowpox lesions. The boy developed only mild symptoms and, after recovering, was exposed to the human smallpox virus. As he did not contract the disease, Jenner concluded that the prior cowpox infection had conferred protection against the more severe form of the illness, thereby laying the foundations for modern vaccination[4]. It is important to note that this experiment took place in a historical context that predated the ethical and scientific protocols currently governing research involving human subjects. 

Today, vaccine development undergoes rigorous preclinical and clinical research stages, as well as evaluation by ethics committees and regulatory agencies, prior to any administration to the general population.

A study published in 2024 indicated that, since 1974, vaccination has averted approximately 154 million deaths worldwide, including 146 million deaths among children under the age of five—101 million of whom were infants under one year old [5]. Nevertheless, there has been a rise in groups resistant to vaccination, driven by religious, cultural, political, and health-related factors. Although vaccine hesitancy is not a recent phenomenon, a significant milestone in the contemporary anti-vaccine movement occurred in 1998, when British physician Andrew Wakefield published a study in the scientific journal *The Lancet* suggesting a link between the MMR vaccine (measles, mumps, and rubella) and the development of autism in children [6].

Subsequent investigations revealed that the results had been manipulated and that there was no scientific evidence to support such a link. Consequently, the article was retracted by the journal, and Wakefield lost his medical license [7]. Despite the study's broad scientific refutation, its impact helped strengthen anti-vaccine rhetoric in various countries, fueling doubts about vaccine safety and fostering the spread of misinformation that persists today, particularly in digital spaces.

While the anti-vaccine movement—also known as "antivax"—has gained greater visibility in recent decades due to globalization and the expansion of media, its origins predate the contemporary era by a wide margin. The first organized expressions of opposition to vaccination emerged as early as the 19th century, in response to mandatory immunization policies implemented by certain governments. In England, smallpox vaccination became mandatory for the first time in 1853 under the Vaccination Act, which required the immunization of children during their first months of life. However, the measure's implementation faced strong resistance from segments of the population who questioned both the efficacy and safety of the vaccines and the legitimacy of state intervention in individual decisions. Difficulties in enforcing the policy led to successive relaxations of the legislation, culminating in the creation of a "conscientious objection" clause in 1898 and the expansion of exemption grounds in 1907[8] [9].

Against this backdrop, organizations dedicated to opposing mandatory vaccination emerged. Notable among them was the London Society for the Abolition of Compulsory Vaccination, founded in 1880 and later renamed the National Anti-Vaccination League. The group grew to include over 100 branches and approximately 10,000 members, becoming one of the first formally structured organizations to oppose immunization policies[10].

A brief history of vaccination and vaccine resistance in Brazil

Although the topic is currently in the spotlight, vaccine resistance is an issue that researchers and health professionals have been familiar with for decades—and our first challenge involved smallpox. In 1804, a figure from Imperial Brazil emerged as a key player in the introduction of vaccines to the country: the Marquis of Barbacena. A military officer, diplomat, and politician, the Marquis of Barbacena (1772–1842) coordinated with the monarchy to transport enslaved people who had already been immunized—a practice once known as "arm-to-arm transport." Immunization was achieved through a chain of transmission: the animal virus was intentionally administered to one person, and the material was subsequently extracted and used on another healthy individual. Initially, immunization efforts were focused solely on the Royal Court. It was not until 1837 that the vaccine became mandatory for children, and in 1846, for adults.

However, this mandate did not yield effective results; it was against this backdrop that the Vaccine Revolt emerged in 1904. The uprising was a reaction to the stance taken by public health official Oswaldo Cruz—a position reinforced by legislation passed by the National Congress on October 31, 1904, which empowered the police to force entry into homes so that health agents could administer the vaccine. Despite the authorities' concern with combating the smallpox epidemic, the population did not respond positively to the measures, and a fierce popular rebellion broke out on November 13 of that same year.

Declining vaccination coverage in Brazil: a contemporary issue

The National Immunization Program (PNI) was established in the 1970s—a public policy that played a crucial role in expanding the entire vaccination system. During that same period, vaccination campaigns against measles and meningococcal meningitis were carried out. The years spanning the 1970s through the early 2000s marked the "golden age" of vaccination coverage. According to data from the National Immunization Program Evaluation Information System (SIAPI), the campaign against polio achieved 100.7% coverage during its first phase in 2002, while seasonal influenza vaccination among the elderly reached 99.9% coverage. See the table below:

However, starting in 2016, a sharp decline in coverage began, particularly regarding childhood immunization: the coverage rate for the MMR vaccine, for instance—which reached 96% of children in 2015—dropped to 84% in 2017, thereby opening the door to new windows of infection in the country.

What was once spread merely by word of mouth among vaccine-resistant circles found a space to call its own in the era of digital networks. Beyond simply expanding their reach, extremists were able to access new horizons and "arguments"—however wildly unfounded, such as the aforementioned link between vaccines and autism—to justify their actions. Bringing this into the context of the pandemic, between 2020 and 2023, Brazil experienced a renewed uprising, featuring new and far-reaching networks for the dissemination of ideas—but now with the backing of high-ranking executive officials, starting with the president at the time, Jair Messias Bolsonaro, who came to be viewed as the movement’s "ringleader":

“Why force a ‘child’ to get vaccinated? What are the odds of a child, for instance, contracting the virus and dying? […] It looks like—I don’t want to state it as fact—but it looks like the vaccine lobby. […] The interests of pharmaceutical companies making billions off the vaccine. Could that be it? It makes no sense. From what I see in studies—I’m mentioning this here—studies regarding those who have already contracted the virus and recovered, obviously... [For these people] the vaccine is useless, yet the pressure continues.”

– Excerpt from a press conference on October 14, 2021

In another instance, on December 17, 2020, the former president remarked sarcastically:
“If you turn into an alligator, that’s ‘your’ problem. If you turn into Superman, if a woman grows a beard or a man starts speaking in a high-pitched voice, they won’t have anything to do with it. What’s worse: messing with people’s immune systems. How can you force someone to take a vaccine that hasn’t even completed Phase 3 trials yet—one that is still experimental?”
More than ever, the vaccination process in Brazil took on a political tone. The Federative Republic of Brazil shifted from a model of Cooperative Federalism to one of Confrontational Federalism[11], wherein vaccine procurement—an inherently federal responsibility—became fragmented to such an extent that subnational entities formed consortia to facilitate and negotiate purchases on their own. The result? In 2022, the Oswaldo Cruz Institute published an article presenting data on national coverage rates:

“According to Ministry of Health data, vaccination coverage among the population has been plummeting, reaching a point in 2021 where fewer than 59% of citizens were immunized. In 2020, the rate was 67%, and in 2019, it was 73%. The target level recommended by the Ministry of Health is 95%.”

The anti-vaccine movement in Brazil: an import or a local reconfiguration?

Given this scenario, it is worth asking whether the issue of vaccine hesitancy is a phenomenon specific to the Brazilian context or merely a reproduction of what is seen elsewhere. The study by the Laboratory for the Study of Information Disorder and Public Policy[12] shows that this movement—while gaining momentum during the coronavirus pandemic—was not unique to it. In fact, we are dealing with a new context in which scientifically validated information must compete with emotional and religious narratives for the public's perception of reality.

Consequently, anti-vaccine misinformation in Latin America and the Caribbean contributes to the formation of a narrative, emotional, and economic system supported by various actors whose statements and interpretations reinforce one another, since

“[people] find echoes in the words, creating a core group of individuals who know little about anything yet reaffirm each other's beliefs and outlandish theories”

—Cláudio Paixão, PhD in Social Psychology and professor at the UFMG School of Information Science, in an interview with Viva Bem UOL.

Final remarks

First and foremost, it is of utmost importance to mention that all vaccines distributed through the SUS (Unified Health System) have had their efficacy and safety proven and validated by the National Health Surveillance Agency (ANVISA); furthermore, they adhere to World Health Organization (WHO) recommendations and Ministry of Health guidelines. According to the agency, in a news release published in October 2025:

“Immunizing agents are only incorporated into the Unified Health System (SUS) following a rigorous analysis that considers—among other criteria—safety, efficacy, and cost-effectiveness in light of public health needs. All products used in the country undergo quality control by the National Institute of Quality Control in Health (INCQS/Fiocruz).

Furthermore, the safety of vaccines and other immunobiologicals is continuously and systematically monitored through post-marketing pharmacovigilance, carried out through coordinated efforts among manufacturing laboratories, the National Immunization Program (PNI), Anvisa, the INCQS, health departments, and health services and professionals. This coordination ensures the protection of the Brazilian population and maintains public confidence in immunization efforts. Brazil has also been affected by the spread of anti-vaccine rhetoric promoted by various actors—both institutional and non-institutional—many of whom were influenced by international narratives and movements. These narratives often invoked "freedom of expression" to challenge scientific evidence and public immunization policies, contributing to rising vaccine hesitancy in the country. Nevertheless, the latest indicators show a gradual recovery in vaccination coverage. For instance, coverage rates for BCG and Hepatitis B vaccines among newborns surpassed the 95% mark again in 2025.

In such a digital world, there is a need to "know how to play the game" by identifying opportunities beyond standard institutional communication channels—after all, let’s face it: the chances of visibility are far greater when a message is promoted on social media than on a traditional website. In 2022, a section titled "Fact or Fake?" was launched on the Federal Government’s website to verify or debunk claims regarding topics such as agriculture and the fight against environmental crimes. If this institutional editorial approach were expanded beyond the website and integrated into vaccination policies—serving as a form of promotion that simultaneously provides scientifically grounded information and reinforces the importance of vaccination at every stage of life—it could lead to improved coverage rates and a broader audience reach. Furthermore, the Ministry of Health has an asset that could be effectively leveraged, especially in campaigns targeting childhood vaccination: *Zé Gotinha*! This character was created specifically to connect with this target audience, yet has rarely appeared in recent vaccination campaigns.

There is a long road ahead, with a great deal of misinformation to combat. Yet, it is by building brick by brick—and policy by policy—that we move closer to restoring ideal vaccination coverage rates and achieving a population that is immunized, protected, and well-informed.

Isabella Tardelli Maio holds a bachelor's degree in... ...Sciences and Humanities from UFABC; currently pursuing a Master’s degree in Territorial Planning and Management and an undergraduate degree in Public Policy at the same institution. Coordinator and researcher at the Center for Public Policy Analysis and Monitoring (CAMPP).

Giovanna Vitor is an undergraduate student pursuing Bachelor’s degrees in Sciences and Humanities, Public Policy, and International Relations at UFABC. She is a researcher at the Center for Public Policy Analysis and Monitoring (CAMPP).

References

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[1] SILVA, E. C. M.; RICARD, J. C.; ALVES, M. A.; ROCHA, G.; VITÓRIA, S. Vaccine Misinformation in Latin America and the Caribbean. São Paulo – SP, Brazil, Oct. 2025.

[2] KRIZEK, J. P. O. Edward Jenner and the origin of vaccine inoculation. Filosofia e História da Biologia, São Paulo, Brazil, v. 19, no. 1, pp. 31–44, 2024. DOI: 10.11606/issn.2178-6224v19i1p31-44. Available at: <https://revistas.usp.br/fhb/article/view/fhb-v19-n1-02>.

[3] MAGENTA, M. The lessons of the vaccine that arrived in Brazil ‘arm-to-arm’ in 1804. BBC News Brasil. July 25. 2020. Available at: <https://www.bbc.com/portuguese/brasil-53533707>. Accessed on June 24, 2026.

[4] Ibid.

[5] SHATTOCK, A. et al. Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization. Available at: <https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)00850-X/fulltext>. The Lancet, 2024; 403, 2307-2316.

[6] IDOETA, P. A. The story that gave rise to the myth of the link between vaccines and autism. BBC News Brasil. July 24, 2017. Available at: <https://www.bbc.com/portuguese/geral-40663622>. Accessed on June 26, 2026.

[7] Ibid.

[8] GUEDES, M. J. Anti-vaccine movement: learn what it is and how it emerged. Politize! March 24, 2022. Available at: <https://www.politize.com.br/antivacina/#a-primeira-pratica-de-vacinacao>. Accessed on June 24, 2026.

[9] RO, C. The turbulent history of mandatory vaccination in Brazil and the world. BBC News Brasil. Dec. 4, 2021. Available at: <https://www.bbc.com/portuguese/geral-59424621>. Accessed on: June 25, 2026.

[10] Guedes, 2022

[11] FLEURY, Sonia; FAVA, Virgínia M. D. Covid-19 vaccine: arena of the Brazilian federal dispute. Saúde em Debate, v. 46, no. spe1, pp. 248–264, 2022. Available at: <https://doi.org/10.1590/0103-11042022E117>. Accessed on June 24, 2026.

[12] DesinfoPop/FGV, 2025