“Glucagon-like peptide-1 agonist (GLP-1) drugs have transformed type 2 diabetes care, but weekly injections can be burdensome for patients. A single shot a month could make it much easier for people living with diabetes or obesity to stick to their drug regimens, improving quality of life and reducing side effects and diabetes complications,” said lead author Dr Claire Mégret from ADOCIA, Lyon, France, the biotechnology company who developed the hydrogel.

Semaglutide works by mimicking the hormone glucagon-like peptide 1 (GLP-1), and is currently authorised for the treatment of type 2 diabetes patients with insufficient glycaemic control and long-term weight management.

Clinical studies suggest that adherence to injected semaglutide is 39-67% for type 2 diabetes patients at one year [1a], and 40% for patients who take the drug for weight loss [1b]. Similarly, adherence to daily oral pill formulations is around 40% at one year [2].

Long-acting delivery formulations could increase drug efficacy and safety by maintaining steady drug levels in the body at optimal concentrations.

The new hydrogel delivery platform uses two innovative degradable polymers that are chemically bound to one another to form a gel, but allow slow, sustained release of soluble peptides over 1 to 3 months.

“A small dollop of gel, known as a ‘depot,’ of the semaglutide-laden hydrogel is injected under the skin,” explained Dr Mégret. “The challenge is to formulate the hydrogel to entrap the peptides to limit initial burst (early release) of semaglutide molecules and, at the same time, to allow smooth release and controlled dissolving of the gel over one month, without generating toxic molecules.”

Several formulations of the hydrogel were tested in vitro to investigate the drug release rate, duration of action, and semaglutide load to define the best candidate.

The researchers found that the hydrogel could be easily injected using an off-the-shelf needle. Additionally, the gel started forming within minutes of mixing, ensuring sufficient time for the injection while minimising spread at the injection site, so that the depot is small enough to be comfortable and inconspicuous.

In vitro drug release assessments for all formulations showed extended and constant release rates over 1 to 3 months. The researchers also found that the release duration could be tailored through optimisation of the hydrogel properties and loading.

The hydrogel-semaglutide formulation was also tested in six laboratory rats. In the rats, a single injection of the hydrogel-based therapy, showed limited burst (early release) and a regular release over a one-month period.

Importantly, the hydrogel was well tolerated with no inflammatory reaction over the treatment period.

“Our pre-clinical results demonstrate that the regular, slow release of semaglutide over one month after administering a single dose, with limited early release, is achievable. Next we will be testing the hydrogel platform in pigs, whose skin and endocrine systems are most similar to those in humans. If that goes well, we will move forward the platform development by expecting clinical trials within the next few years,” said Dr Mégret.

This pilot is part of EMA’s regulatory support for medical devices, following the introduction of new legislation in the EU in 2022. The plan could bring new products to people with rare diseases and conditions with unmet need.

Orphan devices are medical devices which are intended to be used for diseases or conditions affecting only a small number of individuals each year (fewer than 12,000 individuals in the EU per year). Often they are used to treat or diagnose rare diseases or conditions for which no or insufficient alternative diagnostic or therapeutic options exist, thereby fulfilling an unmet medical need.

The programme will initially benefit selected manufacturers and notified bodies – the national authorities responsible for assessing devices and awarding the CE mark. While the first phase of the programme is currently scheduled to run until the end of 2025, the Agency said it aims to establish a long-term process for orphan device support.

Manufacturers can consult the expert panels at different stages of the development of the clinical strategy for their device, while notified bodies can request advice at specific moments of the ongoing conformity assessment of the device.

As part of the pilot programme, EMA will prioritise certain types of orphan medical devices, such as devices for treating a medical condition that is life-threatening or that could cause permanent impairment of a body function, devices intended for children, and novel devices with potential major clinical benefit.

In June 2024, the European Commission announced new guidance on the clinical evaluation of orphan medical devices issued by the Medical Device Coordination Group, which is composed of representatives of all EU Member States. This guidance sets out criteria to determine when a medical device should be regarded as an orphan device under the EU Medical Devices Regulation and aims to guide manufacturers and national authorities.

In response to the rapidly evolving use and approval of AI medical devices in healthcare, a multi-institutional team of researchers at the UNC School of Medicine, Duke University, Ally Bank, Oxford University, Colombia University, and University of Miami have been on a mission to build public trust and evaluate how exactly AI and algorithmic technologies are being approved for use in patient care.

Together, Sammy Chouffani El Fassi, a MD candidate at the UNC School of Medicine and research scholar at Duke Heart Center, and Gail E. Henderson, PhD, professor at the UNC Department of Social Medicine, led a thorough analysis of clinical validation data for 500+ medical AI devices, revealing that approximately half of the tools authorized by the U.S. Food and Drug Administration (FDA) lacked reported clinical validation data. Their findings were published in Nature Medicine.

“Although AI device manufacturers boast of the credibility of their technology with FDA authorization, clearance does not mean that the devices have been properly evaluated for clinical effectiveness using real patient data,” said Chouffani El Fassi, who was first author on the paper. “With these findings, we hope to encourage the FDA and industry to boost the credibility of device authorization by conducting clinical validation studies on these technologies and making the results of such studies publicly available.”

Since 2016, the average number of medical AI device authorizations by the FDA per year has increased from 2 to 69, indicating tremendous growth in commercialization of AI medical technologies. The majority of approved AI medical technologies are being used to assist physicians with diagnosing abnormalities in radiological imaging, pathologic slide analysis, dosing medicine, and predicting disease progression.

Artificial intelligence is able to learn and perform such human-like functions by using combinations of algorithms. The technology is then given a plethora of data and sets of rules to follow, so that it can “learn” how to detect patterns and relationships with ease. From there, the device manufacturers need to ensure that the technology does not simply memorize the data previously used to train the AI, and that it can accurately produce results using never-before-seen solutions.

Regulation During a Rapid Proliferation of AI Medical Devices

Following the rapid proliferation of these devices and applications to the FDA, Chouffani El Fassi and Henderson et al. were curious about how clinically effective and safe the authorized devices are. Their team analyzed all submissions available on the FDA’s official database, titled “Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices.”

“A lot of the devices that came out after 2016 were created new, or maybe they were similar to a product that already was on the market,” said Henderson. “Using these hundreds of devices in this database, we wanted to determine what it really means for an AI medical device to be FDA-authorized.”

Of the 521 device authorizations, 144 were labelled as “retrospectively validated,” 148 were “prospectively validated,” and 22 were validated using randomized controlled trials. Most notably, 226 of 521 FDA-approved medical devices, or approximately 43%, lacked published clinical validation data. A few of the devices used “phantom images” or computer-generated images that were not from a real patient, which did not technically meet the requirements for clinical validation.

Furthermore, the researchers found that the latest draft guidance, published by the FDA in September 2023, does not clearly distinguish between different types of clinical validation studies in its recommendations to manufacturers.

Types of Clinical Validation and A New Standard

In the realm of clinical validation, there are three different methods by which researchers and device manufacturers validate the accuracy of their technologies: retrospective validation, prospective validation, and subset of prospective validation called randomized controlled trials.

Retrospective validation involves feeding the AI model image data from the past, such as patient chest x-rays prior to the COVID-19 pandemic. Prospective validation, however, typically produces stronger scientific evidence because the AI device is being validated based on real-time data from patients. This is more realistic, according to the researchers, because it allows the AI to account for data variables that were not in existence when it was being trained, such as patient chest x-rays that were impacted by viruses during the COVID pandemic.

Randomized controlled trials are considered the gold standard for clinical validation. This type of prospective study utilizes random assignment controls for confounding variables that would differentiate the experimental and control groups, thus isolating the therapeutic effect of the device. For example, researchers could evaluate device performance by randomly assigning patients to have their CT scans read by a radiologist (control group) versus AI (experimental group).

Because retrospective studies, prospective studies, and randomized controlled trials produce various levels of scientific evidence, the researchers involved in the study recommend that the FDA and device manufactures should clearly distinguish between different types of clinical validation studies in its recommendations to manufacturers.

In their Nature Medicine publication, Chouffani El Fassi and Henderson et al. lay out definitions for the clinical validation methods which can be used as a standard in the field of medical AI.

“We shared our findings with directors at the FDA who oversee medical device regulation, and we expect our work will inform their regulatory decision making,” said Chouffani El Fassi. “We also hope that our publication will inspire researchers and universities globally to conduct clinical validation studies on medical AI to improve the safety and effectiveness of these technologies. We’re looking forward to the positive impact this project will have on patient care at a large scale.”

Algorithms Can Save Lives

Chouffani El Fassi is currently working with UNC cardiothoracic surgeons Aurelie Merlo and Benjamin Haithcock as well as the executive leadership team at UNC Health to implement an algorithm in their electronic health record system that automates the organ donor evaluation and referral process.

In contrast to the field’s rapid production of AI devices, medicine is lacking basic algorithms, such as computer software that diagnose patients using simple lab values in electronic health records. Chouffani El Fassi says this is because implementation is often expensive and requires interdisciplinary teams that have expertise in both medicine and computer science.

Despite the challenge, UNC Health is on a mission to improve the organ transplant space.

“Finding a potential organ donor, evaluating their organs, and then having the organ procurement organization come in and coordinate an organ transplant is a lengthy and complicated process,” said Chouffani El Fassi. “If this very basic computer algorithm works, we could optimize the organ donation process. A single additional donor means several lives saved. With such a low threshold for success, we look forward giving more people a second chance at life.”

Other contributors to the study include Adonis Abdullah, Ying Fang, Sarabesh Natarajan, Awab Bin Masroor, Naya Kayali, Simran Prakash, Manesh R. Patel, William Ratliff, Zeshan Hussain, Justin Castillo, Ihsan Yüksel, Haonan Chen, Pengyu Guo, Hamilton McInnis, James E Hancock, Barbara J Evans, and Aurelie Merlo.

– Written by Kendall Daniels

COPD comprises several conditions, including chronic bronchitis and emphysema, and can be caused by irritants like smoke or pollution and genetics. The disease affects more than 30 million Americans, yet awareness of the disease’s symptoms, methods to reduce risk, and disease management remains poor. Symptoms, which include breathlessness, fatigue, and chronic cough, are primarily treated using inhaled medications.

In a new study, “Prevalence of Critical Errors and Insufficient Peak Inspiratory Flow in Patients Hospitalized With COPD in a Department of General Internal Medicine: A Cross-Sectional Study,” the authors examined how often inhalers were misused by patients hospitalized with COPD over the course of nine months at Fribourg Hospital in Switzerland.

Inhaler misuse was categorized as either a critical error in inhalation technique or insufficient peak inspiratory flow. These errors result in a lesser dose of medication reaching the person’s lungs, which impacts the person’s ability to manage their symptoms and can lead to increased exacerbations.

“Misuse of inhalers is common, and in our study, we found that approximately two-thirds of inhalers were misused,” said Gaël Grandmaison, M.D., an assistant physician in internal medicine at University and Hospital of Fribourg in Fribourg, Switzerland. “If an inhaler was misused, a physiotherapist conducted up to three teaching sessions with the patient. These sessions helped reduce the number of critical errors in inhaler use. However, despite this education, more than one in 10 inhalers continued to be used suboptimally, either due to an inability to generate sufficient inspiratory effort or because the inhaler was unsuitable for the patient’s characteristics. These results highlight the importance of regular therapeutic education, assessing the patient’s ability to generate a sufficient inspiratory effort, and selecting an inhaler suited to the patient’s characteristics.”

In a perspective article, “Real-World Use of Inhaled COPD Medications: the Good, the Bad, the Ugly,” the author discusses the decreased effectiveness of inhaled medications as the result of inhaler misuse (often due to intricacies and multiple steps required to use the inhaler) and the high cost of inhaler-based therapies. The author also highlights several advances in inhaler use, including the ability to combine therapies and to choose the right inhaler based on patient-centered decisions.

“Education is key to increasing the effectiveness of inhaled medications, and many clinicians – and often even the patients themselves – are unaware that patients are having difficulty getting enough medication into their lungs,” said Valerie G. Press, M.D., MPH, an associate professor of medicine at the University of Chicago. “Additional inhaler technique education is needed to ensure patients are using the device correctly, especially when multiple inhaled medications are prescribed. Additional education, supported by the necessary resources, would help ensure patients are receiving optimal treatment and avoiding adverse health outcomes.”

To access current and past issues of Chronic Obstructive Pulmonary Diseases: Journal of the COPD Foundation, visit journal.copdfoundation.org.

The national poll of 1,006 people found:

• 75% believe using AI to minimize human errors is important.
• 71% would like AI to reduce wait times.
• 70% are comfortable with AI taking notes during an appointment.
• 66% believe AI should improve work-life balance for health care providers.

To address some of these issues, The Ohio State Wexner Medical Center is piloting the Microsoft Dragon Ambient eXperience (DAX) Copilot application. It uses conversational, ambient and generative AI to securely listen to a provider-patient visit and draft clinical notes in the patient’s electronic medical record. Rather than the provider typing the notes during the visit, they can focus on the patient then review and edit the notes afterward.

Ravi Tripathi, MD, chief health information officer at the Ohio State Wexner Medical Center, led the pilot program. From mid-January to mid-March this year, 24 physicians and advanced practice providers in primary care, cardiology and obstetrics and gynecology tested the technology during outpatient clinic visits. After obtaining the patient’s permission, the provider records the visit through the AI application. Once the visit is complete, the notes are organized and ready for review in less than a minute.

“We found it saved up to four minutes per visit. That’s time the physician can use to connect with the patient, do education and make sure they understand the plan going forward,” Tripathi said. “A few clinicians preferred their old workflow but, overall, 80% completed the pilot. In fact, we allowed them to keep using the AI solution afterward because it had significantly impacted their practices in the eight weeks of testing.”

One of the pilot participants was Harrison Jackson, MD, an internist who has been frustrated by the typing that has to take place during each patient visit.

“Documentation is necessary, but it takes away from the quality of patient interaction during a visit. I even apologize. I say, ‘I’m sorry, I know I’m making more eye contact with the computer than with you,’” Jackson said.

After testing AI documentation, Jackson reports some occasional missteps such as incorrect pronouns or mistaking one word for another – all things he said were easily fixed during his chart review. He supports the use of AI going forward in healthcare.

“I’m spending as much if not more time with each patient, and it’s higher quality time with more eye contact. I often mention aspects of a physical exam out loud for the AI program to capture, and it prompts a good conversation with my patient,” Jackson said. “I’ve also let our residents use the technology under my supervision, and we’ve noticed the quality of their patient interactions and the quality of plans they present have improved.”

While most Americans also see value in AI for healthcare, the survey found just over half (56%) still find it a little scary and 70% have concerns about data privacy.

“I know patients are concerned about the privacy and the security of their data, but we hold the artificial intelligence and this technology to the same standards that we hold our electronic medical record,” Tripathi said.

As of July 1, Ohio State expanded ambient documentation access to all providers in outpatient settings. In the first two weeks of expanded use, 100 clinicians regained 64 hours of time and satisfaction scores have improved from patients who say their conversations with their physicians were more valuable.

Survey Methodology

This study was conducted on behalf of The Ohio State University Comprehensive Cancer Center by SSRS on its Opinion Panel Omnibus platform. The SSRS Opinion Panel Omnibus is a national, twice-per-month, probability-based survey. Data collection was conducted from May 17 – 20, 2024, among a sample of 1,006 respondents. The survey was conducted via web (n=974) and telephone (n=32) and administered in English. The margin of error for total respondents is +/- 3.5 percentage points at the 95% confidence level. All SSRS Opinion Panel Omnibus data are weighted to represent the target population of U.S. adults ages 18 or older.

Video: Ohio State is thoughtfully implementing AI to help providers spend less time on the computer, and more time interacting with their patients.

view more Credit: The Ohio State University Wexner Medical Center

The researchers will present their results at the fall meeting of the American Chemical Society (ACS). ACS Fall 2024 is a hybrid meeting being held virtually and in person Aug. 18-22; it features about 10,000 presentations on a range of science topics.

AI’s vast number of uses has made it almost ubiquitous in today’s technological landscape. However, many AI models are black boxes, meaning it’s not clear exactly what steps are taken to produce a result. And when that result is something like a potential drug molecule, not understanding the steps might stir up skepticism with scientists and the public alike. “As scientists, we like justification,” explains Rebecca Davis, a chemistry professor at the University of Manitoba. “If we can come up with models that help provide some insight into how AI makes its decisions, it could potentially make scientists more comfortable with these methodologies.”

One way to provide that justification is with XAI. These machine learning algorithms can help us see behind the scenes of AI decision making. Though XAI can be applied in a variety of contexts, Davis’ research focuses on applying it to AI models for drug discovery, such as those used to predict new antibiotic candidates. Considering that thousands of candidate molecules can be screened and rejected to approve just one new drug — and antibiotic resistance is a continuous threat to the efficacy of existing drugs — accurate and efficient prediction models are critical. “I want to use XAI to better understand what information we need to teach computers chemistry,” says Hunter Sturm, a graduate student in chemistry in Davis’ lab who’s presenting the work at the meeting.

The researchers started their work by feeding databases of known drug molecules into an AI model that would predict whether a compound would have a biological effect. Then, they used an XAI model developed by collaborator Pascal Friederich at Germany’s Karlsruhe Institute of Technology to examine the specific parts of the drug molecules that led to the model’s prediction. This helped explain why a particular molecule had activity or not, according to the model, and that helped Davis and Sturm understand what an AI model might deem important and how it creates categories once it has examined many different compounds.

The researchers realized that XAI can see things that humans might have missed; it can consider far more variables and data points at once than a human brain. For example, when screening a set of penicillin molecules, the XAI found something interesting. “Many chemists think of penicillin’s core as the critical site for antibiotic activity,” says Davis. “But that’s not what the XAI saw.” Instead, it identified structures attached to that core as the critical factor in its classification, not the core itself. “This might be why some penicillin derivatives with that core show poor biological activity,” explains Davis.

In addition to identifying important molecular structures, the researchers hope to use XAI to improve predictive AI models. “XAI shows us what computer algorithms define as important for antibiotic activity,” explains Sturm. “We can then use this information to train an AI model on what it’s supposed to be looking for,” Davis adds.

Next, the team will partner with a microbiology lab to synthesize and test some of the compounds the improved AI models predict would work as antibiotics. Ultimately, they hope XAI will help chemists create better, or perhaps entirely different, antibiotic compounds, which could help stem the tide of antibiotic-resistant pathogens.

“AI causes a lot of distrust and uncertainty in people. But if we can ask AI to explain what it’s doing, there’s a greater likelihood that this technology will be accepted,” says Davis.

Sturm adds that he thinks AI applications in chemistry and drug discovery represent the future of the field. “Someone needs to lay the foundation. That’s what I hope I’m doing.”

The research was funded by the University of Manitoba, the Canadian Institutes of Health Research and the Digital Research Alliance of Canada.

A Q&A with the researcher will be posted on Sunday, Aug. 18. Reporters can access the video during the embargo period, and once the embargo is lifted the same URL will allow the public to access the content. Visit the ACS Fall 2024 program to learn more about this presentation, “Using Explainable Artificial Intelligence to explore the relationship between structure and activity,” and other science presentations.

This research was presented at a meeting of the American Chemical Society. ACS does not conduct research, but publishes and publicizes peer-reviewed scientific studies.

A paper released today titled “Modeling impact of Inflation Reduction Act price negotiations on new drug pipeline considering differential contributions of large and small biopharmaceutical companies,” published in the journal Clinical Trials, showed that for large pharmaceutical producers, which account for the large majority of product sales, revenue, and profit, the level of R&D spending was strongly related to revenue from 2000-2018. In contrast, for smaller biotechnology companies, which typically have few products and little revenue but sponsor the majority of all clinical trials, there was no relationship between R&D spending and revenue. These companies typically acquire capital for R&D substantially through new investment in equity offerings.

This research also assessed the impact of reducing drug pricing on the number of new drug approvals using a drug development pipeline model that considers the differential contributions of large and small companies and likely changes in R&D spending in response to changes in revenue. This analysis suggests the current level of drug approvals could be maintained in the face of global revenue reductions of up to 10% through strategic distribution of cost reductions in large companies between early and late phases of clinical development, coupled with continued acquisition of candidate products in early phases of development by biotechnology companies.

A related working paper titled “Implications of the Inflation Reduction Act for the biotechnology industry; sensitivity of investment and valuation to drug price indices and market conditions,” published by the Institute for New Economic Thinking, showed that there was no relationship between investment in biotechnology and indices of drug prices 2000-2020. This suggests that investment in biotechnology companies is unlikely to be affected by decreases in drug prices and will continue to provide the capital necessary for early-stage innovation and development in biotechnology companies.

These studies describe a dynamic innovation process in which small, emerging biotechnology companies originate the majority of new products and sponsor the majority of all clinical trials with innovation capital arising from private or public investment. These products may then be developed by the biotechnology companies themselves or acquired by large pharmaceutical companies for late-stage development and commercialization. The analysis suggests that the industry can sustain current levels of product approval and commercialization without compromising corporate earnings or investor returns.

These studies do not support industry arguments that drug price reductions anticipated by the IRA represent a threat to corporate profits, investor returns, or new product approvals.

“Pharmaceutical innovation is not adequately described by conventional economic theories that fail to account for the distinct business models of small, science-based biotechnology companies” said Fred Ledley, Director of the Center for Integration of Science and Industry, and the senior author on these studies. “Our work suggests that established management and investment practices could preserve both the industry’s profits and current levels of drug approvals in face of the reductions in drug price anticipated by the Inflation Reduction Act.”

Dr. Gregory Vaughan, Associate Professor of Mathematical Sciences at Bentley University, was the lead author of the publication in Clinical Trials along with Roger Du and Dr. Ledley. Dr. Cody Hyman, Assistant Professor of Accounting at Bentley University, was the lead author of the working paper published by INET along with Henry Dao, Dr. Vaughan, and Dr. Ledley. Roger Du and Henry Dao worked as undergraduate researchers at Bentley University.

This work was funded by the West Health Policy Center and National Biomedical Research Foundation through grants to Bentley University.

A new study led by Duke Health shows that over half of the medicines stocked in space — staples such as pain relievers, antibiotics, allergy medicines, and sleep aids — would expire before astronauts could return to Earth.

Astronauts could end up relying on ineffective or even harmful drugs, according to the study appearing July 23 in npj Microgravity, a Nature journal.

“It doesn’t necessarily mean the medicines won’t work, but in the same way you shouldn’t take expired medications you have lying around at home, space exploration agencies will need to plan on expired medications being less effective,” said senior study author Daniel Buckland, M.D., Ph.D., an assistant professor of emergency medicine at Duke University School of Medicine and an aerospace medicine researcher.

Expired medications can lose their strength by a little – or a lot. The actual stability and potency of medications in space compared to Earth remain largely unknown. The harsh space environment, including radiation, could reduce the effectiveness of medications.

Buckland and co-author Thomas E. Diaz, a pharmacy resident at The Johns Hopkins Hospital, noted that expired medications could pose a challenge as space agencies plan for long-duration missions to Mars and beyond.

Diaz used a Freedom of Information Act Request to obtain information about the space station formulary, assuming NASA would use similar medications for a Mars mission.

Using a database of international drug expiration dates, the researchers determined that 54 of the 91 medications had a shelf-life of 36 months or less.

Using the most optimistic estimates, about 60% of these medications would expire before a Mars mission concludes. Under more conservative assumptions, the figure jumps to 98%.

The study did not assume accelerated degradation but focused on the inability to resupply a Mars mission with newer medicines. This lack of resupply affects not only medications but also other critical supplies, such as food.

Increasing the number of medications brought on board could also help compensate for lowered efficacy of expired meds, authors said.

“Those responsible for the health of space flight crews will have to find ways to extend the expiration of medications to complete a Mars mission duration of three years, select medications with longer shelf-lives, or accept the elevated risk associated with administering expired medication,” Diaz said.

“Prior experience and research show astronauts do get ill on the International Space Station, but there is real-time communication with the ground and a well-stocked pharmacy that is regularly resupplied, which prevents small injuries or minor illnesses from turning into issues that affect the mission,” Buckland said.

Additional authors include Emma Ives and Diana I. Lazare. The study received no external funding.

Now, a new study offers hope that while they wait to get care, patients could still get some relief by using evidence-based smartphone apps and wearable devices to track sleep and activity.

The study shows that depression and anxiety symptoms, and suicidality, all decreased measurably when patients were assigned to mobile applications that incorporated mindfulness practices, cognitive-behavioral therapy skills, or prompts that encouraged mood-enhancing activities.

The study, conducted at Michigan Medicine, the University of Michigan’s academic medical center, is published in JAMA Network Open. It involved just over 2,000 patients scheduled to get care in coming weeks from a mental health provider at outpatient U-M Health or U-M student clinics.

Adam Horwitz, Ph.D., the U-M Medical School psychologist who is the paper’s lead author, called the results encouraging, with implications for individuals and clinics alike.

“Having this type of option, especially for people who are motivated enough to seek an appointment and wait for it, could be very valuable when providers have long wait lists,” said Horwitz, who is an assistant professor in the Department of Psychiatry. “These individuals want to be doing something about their mental health but don’t yet have access, so this suggests that providing them with some sort of digital option when their motivation is already high, and they are ready to do something, could begin to make a difference.”

Combining app prompts and wearable device data

Nearly all the patients completed standardized mental health assessments both at the start of the study and after six weeks of using the app they had been randomly assigned to install on their smartphone. All participants also wore a study-provided Fitbit or their own Fitbit or smartwatch, to track sleep and physical activity.

The study randomly assigned most participants to one of two commercial apps – Silvercloud, which is based on cognitive behavioral therapy principles, and Headspace, which coaches users in mindfulness techniques. Both apps have been shown separately to help alleviate mental health symptoms, but have never been tested against one another.

Some study participants were randomly assigned to receive a customized version of the study app called MyDataHelps, either alone or together with one of the commercial apps. Those randomized to receive this app received positive encouraging prompts twice per day based on their activity tracker data — for example, applauding them for walking or getting a good amount of sleep, or suggesting a simple act to improve their mood.

Improvement in all groups

Surprisingly, no matter what group they were in, the participants’ scores on standard mental health scales changed for the better by the end of the study period.

At the start of the study, depression scores on average were just under 13 on the 27-point PHQ-9 scale; all groups dropped by two to three points by six weeks. Scores on the 21-point GAD-7 anxiety scale dropped by 1.5 to 2 points across the board.

Meanwhile, scores on measures of protection against suicide risk increased slightly, with the most improvement among participants using Headspace. Scores on the suicide risk measurement dropped slightly across the board, indicating lower risk for suicidal behavior.

Most of the study participants had their initial appointment with a U-M mental health provider before the end of that six-week period, but the drop in mental health scores was similar for those who hadn’t yet started professional treatment.

More research ahead

Horwitz notes that the newly published study, called PROMPT, helped inform the development of a much larger study called COMPASS based at U-M that just got $17.9 million in funding from the National Institute of Mental Health.

The COMPASS study will involve not only smartphone apps, wearable activity trackers and standardized mental health assessments, but also genetic tests and other types of data collection. It will involve thousands of U-M Health and U-M student clinic patients who are waiting for their first mental health-related appointment.

Both PROMPT and COMPASS seek to help researchers develop a more personalized approach to mental health care.

They hope to identify which characteristics make someone more likely to respond positively to different forms of treatment or support, so they can use this knowledge to reduce the time it takes to find the approach that helps each individual.

Future directions

Horwitz notes that people seeking mobile-based mental health support have many apps to choose from – and that most of those apps haven’t gotten scrutiny through objective research. Headspace and Silvercloud have more objective evidence behind them than most of these apps, he notes.

He and his colleagues were surprised but encouraged to see improvement in the group using the customized version of MyDataHelps, too.

Part of the reason may have to do with the study population: people who were motivated to seek help for mental health concerns, had already been on a waiting list to get scheduled, and now had been scheduled and were waiting to be seen.

Because mental health conditions can wax and wane in their symptom severity, apps that support someone during an especially low-mood or high-anxiety time could be important for helping them endure the time until their first appointment.

Horwitz notes that the study participants’ clinical providers didn’t have access to their app data. But, he said, this might be a potential option for clinics moving forward if patients want to grant that access by allowing their app to share a summary with their clinic.

Data from mental health apps could even potentially help providers or systems understand which patients need the most-intensive approaches to psychiatric care, and which might be able to do all right with less-intensive care. That could also improve the waiting list situation for all patients, he notes.

He likens this to a relay race.

“If we can use apps to give the patient a bit of momentum on understanding and managing their symptoms, even before they get to clinic, then perhaps that will help them get more out of therapy once they get to clinic and pass the baton from the app to a professional provider,” he said. “The apps don’t have the same effect as therapy, but doing something while waiting is still important.”

In addition to Horwitz, the study’s authors are Elizabeth D. Mills, Ph.D., of the U-M Department of Anesthesiology, Srijan Sen, M.D., Ph.D., and Amy S.B. Bohnert, Ph.D. Sen, a professor of psychiatry, directs the U-M Eisenberg Family Depression Center and is a member of the Michigan Neuroscience Institute; Bohnert is co-director of the U-M Opioid Research Institute and a professor of anesthesiology. Bohnert and Sen are two of the three leaders of the COMPASS study.

The PROMPT study was funded by Precision Health at U-M and the Eisenberg Family Depression Center as well as the National Institute of Mental Health (MH131761).

Comparative Effectiveness of Three Digital Interventions for Adults Seeking Psychiatric Services, JAMA Network Open, DOI:10.1001/jamanetworkopen.2024.22115

Trusted names including Hilary Jones, Michael Mosley and Rangan Chatterjee are being used to promote products claiming to fix high blood pressure and diabetes, and to sell hemp gummies, explains journalist Chris Stokel-Walker.

Deepfaking is the use of artificial intelligence (AI) to map a digital likeness of a real-life human being onto a video of a body that isn’t theirs. Reliable evidence on how convincing it is can be hard to come by, but one recent study suggests that up to half of all people shown deepfakes talking about scientific subjects cannot distinguish them from authentic videos.

John Cormack, a retired doctor based in Essex, worked with The BMJ to try and capture a sense of the scale of so-called deepfaked doctors across social media.

“The bottom line is, it’s much cheaper to spend your cash on making videos than it is on doing research and coming up with new products and getting them to market in the conventional way,” he says.

The slew of questionable content on social media co-opting the likenesses of popular doctors and celebrities is an inevitable consequence of the AI revolution we’re currently living through, says Henry Ajder, an expert on deepfake technology. “The rapid democratisation of accessible AI tools for voice cloning and avatar generation has transformed the fraud and impersonation landscape.”

“There’s been a significant increase in this kind of activity,” says Jones, who employs a social media specialist to trawl the web for deepfake videos that misrepresent his views and tries to take them down. “Even if you do, they just pop up the next day under a different name.”

A spokesperson for Meta, the company that owns both Facebook and Instagram, on which many of the videos found by Cormack were hosted, told The BMJ: “We will be investigating the examples highlighted by the British Medical Journal. We don’t permit content that intentionally deceives or seeks to defraud others, and we’re constantly working to improve detection and enforcement. We encourage anyone who sees content that might violate our policies to report it so we can investigate and take action.”

Deepfakes work by preying on people’s emotions, writes Stokel-Walker, and when it comes to medical products, that emotional connection with the individual telling you about the wonder drug or magnificent medical product matters all the more.

Someone you don’t know trying to sell you on the virtues of a particular treatment may raise suspicions. But if they’re someone you’ve seen before on social media, television or radio, you’re more likely to believe what they’re saying.

Spotting deepfakes can be tricky too, says Ajder, as the technology has improved. “It’s difficult to quantify how effective this new form of deepfake fraud is, but the growing volume of videos now circulating would suggest bad actors are having some success.”

For those whose likenesses are being co-opted, there’s seemingly very little they can do about it, but Stokel-Walker offers some tips on what to do if you find a deepfake. For instance, take a careful look at the content to make sure your suspicions are well-founded then leave a comment, questioning its veracity. Use the platform’s built-in reporting tools to voice your concerns, and finally report the person who or account that shared the post.

The committee recommended authorisation for the following:

Balversa (erdafitinib) for the treatment of adult patients with unresectable or metastatic urothelial carcinoma, a cancer of the bladder and urinary system.

Eurneffy (epinephrine), the first emergency treatment against allergic reactions that is administered as a nasal spray, not as an injection.

mResvia (Respiratory Syncytial Virus (RSV) mRNA vaccine) for prevention in adults 60 years of age and older of lower respiratory tract disease and acute respiratory disease caused by respiratory syncytial virus (RSV). RSV is a common respiratory virus that usually causes mild, cold-like symptoms but can lead to serious consequences in older adults. This is the first mRNA vaccine targeting a different pathogen than SARS-CoV-2 that receives a positive opinion from the CHMP.

Ordspono (odronextamab) received a conditional recommendation for the treatment of follicular lymphoma and diffuse large B-cell lymphoma, two types of blood cancer that affect the immune system.

Piasky (crovalimab) for the treatment of paroxysmal nocturnal haemoglobinuria, a rare genetic disorder that causes the premature breakdown of red blood cells by the immune system and is potentially life-threatening.

Tauvid (flortaucipir (¹⁸F)) for positron emission tomography (PET) imaging of the brain in adult patients with cognitive impairment who are being evaluated for Alzheimer’s disease.

Winrevair (sotatercept) to treat adult patients with pulmonary arterial hypertension, a rare, long-term, debilitating and life-threatening condition in which patients have abnormally high blood pressure in the arteries in the lungs.

Steqeyma (ustekinumab), a biosimilar medicine for the treatment of adult patients with moderate/severe active Crohn’s disease, plaque psoriasis, paediatric plaque psoriasis and psoriatic arthritis.

The committee also adopted positive opinions for two generic medicines: Enzalutamide Viatris (enzalutamide) for the treatment of prostate cancer, and Nilotinib Accord (nilotinib) for the treatment of Philadelphia chromosome positive chronic myelogenous leukaemia.

Extensions of indication were recommended for 11 medicines that are already authorised in the EU: Betmiga, Beyfortus, Cresemba, Imcivree, Imfinzi, Infanrix hexa, Lynparza, Pegasys, Tepkinly, Vabysmo and Xalkori.

The research team from The Hong Kong Polytechnic University, led by Dr. Arkers Kwan Ching Wong, reviewed data from 3 randomized controlled trials involving over 150 older adults. The evaluation showed that the interventions that focused on increasing awareness of being monitored and used collaborative goal-setting and feedback tools, such as the SystemCHANGE approach, improved adherence to WMDs.

WMDs can offer valuable health insights, but their long-term use can be challenging for older adults who may not be comfortable with technology or not see the value in using it. As this research highlights, providing targeted support to help older adults overcome these barriers and integrate WMDs into their daily routines can help maximize the potential health benefits of these devices.

“Healthcare professionals play a pivotal role in facilitating the adoption of wearable monitoring devices among older adults,”  remarked Dr. Wong.

By working with health care professionals to set specific goals related to the use of wearables, older adults are more likely to benefit from these devices in the long term. Future research should focus on developing and testing interventions that prioritize awareness and collaborative goal-setting to further enhance adherence among older adults.

Chan CSW, Kan MMP, Wong AKC

Effects of Peer- or Professional-Led Support in Enhancing Adherence to Wearable Monitoring Devices Among Community-Dwelling Older Adults: Systematic Review of Randomized Controlled Trials

J Med Internet Res 2024;26:e53607

URL: https://www.jmir.org/2024/1/e53607

doi: 10.2196/53607