Category: Imported News

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Perspectives on Continuous Glucose Monitoring Among Adults with Type 2 Diabetes in the United Kingdom: Cross-Sectional Survey

<strong>Background:</strong> Type 2 diabetes (T2D) is one of the most common noncommunicable diseases, requiring ongoing lifestyle changes and continuous glucose management through medication, diet, and physical activity. Traditional self-monitoring of blood glucose can be burdensome, especially with frequent finger pricks. As continuous glucose monitoring (CGM) becomes more affordable and accessible, it offers benefits such as increased glucose awareness, behavioral modifications, and reduced anxiety. However, challenges remain, including cost, discomfort, skin reactions, and privacy concerns. In the United Kingdom, perceptions of CGM among people with T2D, including both users and nonusers, are not well understood, limiting insight into factors influencing adoption and sustained use. <strong>Objective:</strong> This study aims to explore how adults with T2D perceive the benefits and challenges of using CGM, including both current users and nonusers. <strong>Methods:</strong> This study used a cross-sectional, online survey using YouGov’s nationally representative panel to explore experiences of CGM among adults with T2D in the United Kingdom. A total of 531 participants were recruited from November to December 2024. Thematic analysis of responses to 2 open-ended questions identified key perceived benefits and challenges associated with CGM use. <strong>Results:</strong> A total of 531 adults with T2D completed the YouGov online survey. Over half were male (297/531, 55.9%) and aged 65 years and older (281/531, 52.9%). Two-thirds (347/531, 65.3%) had lived with T2D for more than 5 years, and 9.6% (51/531) use or had previously used a CGM. Overall, 50.8% (270/531) responded to at least one free-text question, with 49% (260/531) commenting on benefits and 33.1% (176/531) on challenges. Thematic analysis identified five key benefit themes: (1) reduced monitoring burden, described as eliminating frequent finger prick testing and simplifying daily routines; (2) lifestyle feedback, enabling participants to better understand how diet and physical activity influence glucose levels; (3) greater control, by supporting more informed decision-making and increasing confidence in self-management; (4) feeling safer, through alerts for hypo- and hyperglycemia; and (5) sharing data with clinicians, which facilitated communication and more collaborative care. The main challenges were (1) access barriers, including restrictive eligibility criteria and the high cost of self-funding; (2) device issues, such as discomfort, inconvenience, and practical difficulties wearing the sensor; (3) technology reliance, with concerns about depending on devices rather than listening to bodily cues; (4) emotional strain, including anxiety, over-monitoring, and increased preoccupation with glucose levels; and (5) data concerns, particularly regarding accuracy, interpretation, and privacy. <strong>Conclusions:</strong> Adults with T2D, including both users and nonusers, described CGM as a practical and empowering tool that improves understanding, safety, and collaboration with health care providers. Nevertheless, access barriers, usability issues, and emotional and data-related burdens remain major obstacles to equitable adoption. Addressing these through improved affordability, digital literacy support, and customized clinical guidance may support ongoing and inclusive CGM use in routine care.
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Backed by $165M, Bionyra Pharma Launches to Advance Inflammatory Disease Biologics

Though he is trained as a gastroenterologist and scientist, Frédéric Marrache, MD, PhD, has always had something of an entrepreneurial itch. Following his post-doctoral program and a stint in management consulting, he made his way to Sanofi where he would work on early- to mid-stage drug development programs focused on immune-mediated diseases.

“This was right around the time when Sanofi, together with Regeneron, was finalizing the development of Dupixent,” a prescription biologic injection used to treat multiple inflammatory conditions, he told GEN. Those experiences gave him “meaningful insights” into patient care as well as about “how to develop therapies in this space.”

One of those insights was the scale of the unmet medical need in the immune-driven inflammatory disease space. Though some large pharma companies have developed products for the space already, “I had a few insights about what could be differentiated,” he said. That led him to engage with a team at Sofinnova Partners in early 2025. “I came in with my insights about patient needs, immunology, and target selection, and [my] view on right and wrong assets,” he said. “They came with experience in building companies” and “we mapped out the entire asset space specifically on the target and pathway of interest.” 

Those discussions led to the launch of Bionyra Pharma, a clinical-stage biopharmaceutical company that is developing next-generation biologics for severe immunological and inflammatory diseases. The company emerged from stealth this week after raising $165 million in an oversubscribed Series A. The round was co-led by Jeito Capital and Sofinnova Partners with participation from Arkin Bio, Sanofi Ventures, Sixty Degree Capital, Vives Partners and Apollo Health Ventures. 

Marrache serves as the co-founder and CEO of the company. In addition to the financing, Mehdi Ainouche, partner at Jeito Capital; Anta Gkelou, partner at Sofinnova Partners; Avital Adler, principal at Arkin Bio; and Laia Crespo, partner at Sanofi Ventures, will join Bionyra’s board of directors.

“When we co-founded Bionyra with Frédéric, our conviction in both the company and his leadership was grounded in his deep expertise in immune and inflammatory diseases,” said Sofinnova’s Gkelou. “Looking ahead, we are focused on advancing these programs with the aim of bringing meaningful new treatment options to patients.” 

Specifically, the funds will support Bionyra’s efforts to advance mono and multispecific antibodies for various inflammatory conditions including atopic dermatitis and inflammatory bowel disease (IBD). 

Right out of the gate, Bionyra is launching a pipeline of three clinical and near-clinical anti-inflammatory therapies, some of which are already in clinical trials. The company’s first asset, BYN-002 is a TL1A monoclonal antibody with the potential to treat IBD and other TL1A-relevant indications. This therapy is currently in a fully-enrolled Phase I study in healthy people. Its next candidate, BYN-003, is a TL1A*IL-23p19 bispecific antibody that is also in Phase I testing. Both assets have been improved with half-life extension (HLE) engineering to maximize efficacy and patient benefit.

Generally speaking, “TL1A is a game changer target right now in [immunology and inflammation] with great results in inflammatory disease,” he said. However, it is likely that this target will be relevant across multiple indications. To that end, Bionyra is keeping its options open in terms of what it will target with its TL1A assets. “Whether it’s going to be in the inflammatory bowel disease space, whether we go for another indication space or whether we decide to develop it in combination in any of these indications, that’s an option,” he said. 

For now, the focus is on validating the safety and efficacy of both therapies in healthy volunteers. “That’s especially a question around the bispecific antibody” because there will likely be questions around the immunogenicity, he noted. “Our advantage here is that our bispecific is built on the backbone of our monospecific, so at least we have some level of early validation here, and we hope to present some results soon.”  

A third candidate, BYN-001, is an IL-25 monoclonal antibody that has also benefited from HLE technology. It is currently in the IND-stage for atopic dermatitis and type 2 inflammation. While there are several assets in development that aim to target type 2 inflammation, once all of the me-too drugs are excluded, the field becomes narrower, Marrache said while explaining the rationale for choosing this particular drug candidate for Bionyra’s portfolio. “IL-25 has been known to be a strong driver of type 2 inflammation for some time,” he said.

Furthermore, some recently published early clinical data from a competitor, who are developing their own asset for IL-25, “clearly validated the pathway and suggested potential for differentiation.” At the time, Bionyra was already exploring the same target space so “we were able to move very quickly” and find what, Marrache believes, is the “most potent IL-25 antibody out there” with the “longest half life.” 

Two of the assets BYN-002 and BYN-003 were licensed from TrueLab Biopharmaceutical. Under the terms of the agreement Bionyra was granted exclusive worldwide rights, excluding Greater China, to research, develop, manufacture and commercialize both therapies. TrueLab is eligible to receive up to $985 million in total consideration related to both assets, including the upfront payment as well as development, regulatory, and commercial milestone payments. The agreement also includes tiered royalties on future net sales. In addition, TrueLab has a single-digit equity stake in Bionyra Pharma following completion of its Series A financing. 

For its part, BYN-001 was licensed from NovaRock Biotherapeutics. Bionyra is also progressing additional preclinical assets including some from TrueLab. It will support these efforts with some of the funds from the Series A.

The post Backed by $165M, Bionyra Pharma Launches to Advance Inflammatory Disease Biologics appeared first on GEN – Genetic Engineering and Biotechnology News.

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VR Rehabilitation Improves Arm and Hand Movement After Stroke

A new rehabilitation platform combining virtual reality (VR) and nerve stimulation significantly improved the recovery of arm and hand function after a stroke compared to conventional rehabilitation approaches. Published today in Nature Medicine, results from a small-scale clinical study show early promise for a more effective and accessible rehabilitation approach that can be personalized to each patient’s needs. 

Approximately 60% of stroke survivors develop long-term disability affecting their mobility. Even after extensive physiotherapy and occupational therapy, many continue to live with reduced arm and hand function, which severely impacts their ability to perform day to day tasks and live independently. 

“Our aim was to go beyond mere movement training,” said Stanisa Raspopovic, PhD, professor of biomedical engineering at the Medical University of Vienna and senior author of the study. “After a stroke, patients often have difficulty not only moving the affected limb, but also feeling it and perceiving it correctly. MultiSensy was developed to reconnect movement, sensation and body awareness during rehabilitation.” 

The MultiSensy rehabilitation platform combines immersive VR with electrical nerve stimulation. The VR goggles present users with interactive virtual tasks designed to train arm and hand functions such as reaching, grasping, pinching, and forearm rotation. Meanwhile, electrodes on the skin stimulate sensory nerves in real time to make patients feel virtual objects as if they were physically touching them. 

The system was tested on a cohort of 34 patients who had suffered a stroke over three months before. Participants were divided into two groups who were treated either with MultiSensy or conventional rehabilitation including physiotherapy and occupational therapy. Both groups completed a total of 12 training sessions over the course of three weeks. 

Patients who used the VR system saw a greater recovery of arm and hand movement compared to those in the control group, achieving nearly twice the improvement according to a standard assessment of motor impairment after stroke. In addition, MultiSensy was able to address body awareness and sensory deficits caused by stroke, which are often left aside by conventional rehabilitation strategies.  

“After a stroke, some patients struggle to feel touch in their affected hand and may even perceive the arm as distorted in size, shape, or position,” said Valerio Aurucci, PhD, lead author of the study and former graduate student at ETH Zurich. “Participants treated with the new system showed improvements in their sense of touch and in perception of their affected arm.”

Another advantage of the MultiSensy platform is that each task can be adapted to the impairment level of the user, tailoring treatment to their unique needs. The VR system collects movement data during training, providing objective measurements of progression that clinicians can rely on to monitor a patient’s performance and recovery over time.

“The results provide early clinical evidence that immersive virtual reality combined with sensory nerve stimulation can support recovery after stroke, even after months from the event”, said Raspopovic. “The technology is still at the research stage, and larger clinical trials are needed to confirm its benefits. However, the study opens a promising perspective for future personalized and potentially home-based stroke rehabilitation.”

The post VR Rehabilitation Improves Arm and Hand Movement After Stroke appeared first on Inside Precision Medicine.

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Toward a Digitally Informed Knitted Prosthetic Interface With Graded Stiffness to Enhance Comfort in Transtibial Amputees: Proof-of-Concept Case Study

Background: Despite considerable advancements in prosthetic technology, a substantial proportion of lower limb amputees reduce or discontinue prosthesis use, with reported nonuse rates ranging from 12% to 53%. This reflects the multifactorial challenges associated with long-term prosthetic use, among which comfort and skin health are consistently identified as key determinants. More specifically, studies point toward nonbreathable silicone liners trapping heat and sweat, leading to skin and hygiene problems. These persistent limitations underscore the need for alternative interface materials that offer improved breathability, moisture management, and tunable mechanical properties. Objective: This study aimed to introduce Flexoknit, a transtibial prosthetic liner that integrates user-specific digital skin strain analysis with computer numerical control multimaterial knitting to create a mechanically tuned, breathable, and anatomically customized interface. Using digital biomechanical data as the primary design driver—rather than clinician heuristics alone—Flexoknit aims to determine the feasibility and performance of a skin strain–guided, computer numerical control–knitted prosthetic interface in terms of material function, clinical performance, and user experience. Methods: Flexoknit uses programmable multimaterial knitting, incorporating thermal-reactive yarns that stiffen when heated to create structural support zones, alongside spandex yarns that provide elastic compression and breathable zones. Uniaxial tensile tests showed that yarn and stitch combinations can generate distinct stiffness grades, with nearly order-of-magnitude differences. The spatial layout of these graded zones aligns high-stiffness regions with the lines of nonextension, and low-stiffness regions with areas of greater skin strain. With the new prosthetic interface, a series of controlled tests was conducted to compare performance against the participant’s existing prosthesis with a conventional silicone liner. User testing was organized into 3 domains (ie, mobility, suspension, and comfort) using standardized quantitative assessments and structured qualitative data collection. Results: User testing demonstrated a 22.5% improvement in total range of motion, a 37.5% reduction in interface mass, and improved thermal regulation in hot, humid environments compared to that of a conventional silicone liner. The user walked unaided and performed sit-to-stand movements, reporting positive comfort and usability feedback. Conclusions: This work establishes Flexoknit as a promising direction for future prosthetic development—one that integrates principles of biomechanics, textile engineering, and digital fabrication to create user-centered interface solutions. The findings suggest that digitally engineered knitted interfaces can provide a highly customizable, breathable, and compliant alternative to conventional silicone liners, particularly for lower-activity amputees or individuals prioritizing comfort and ease of use.
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Clinical Outcomes of Individualized Electrostimulation Using a Wearable Electro Suit and Qualitative Feedback From a Mixed Cohort of Survivors of Stroke and Spinal Cord Injury With Spasticity: Case Series

Background: Various forms of electrical stimulation have been integrated into the multimodal management of spasticity. However, high-frequency electrical stimulation can potentially induce muscle fatigue. The Exopulse Mollii Suit (EMS) is a multichannel full-body garment that delivers low-frequency (20 Hz), low-amplitude (20 V), subthreshold sensory stimulation aimed at reducing spasticity. Objective: Primarily, we examined the effects of a single session of the EMS on spasticity in 7 participants with chronic stroke or cervical spinal cord injury (SCI), specifically those with upper or lower limb spasticity impacting function and gait who were able to walk with minimal or no assistance (Functional Ambulatory Category scores of 2‐5). We assessed the impact on gait and ambulatory function, as well as user perceptions of usability and acceptability. Methods: Participants wore the EMS for 60 minutes, consisting of 30 minutes of standardized goal-directed activities performed in two 15-minute blocks, interspersed with 15-minute rest breaks. Measurements included the Modified Tardieu Scale with surface electromyography for spasticity and functional mobility tests (Functional Ambulatory Category, 10-meter walk test, 5 times sit-to-stand test, and step test). Spatiotemporal gait parameters were quantified using a markerless vision-based motion capture system using the OpenPose BODY25 pose estimation model. Results: On the basis of the Modified Tardieu Scale and surface electromyography signals, improvements in spasticity were only observed in 2 participants. However, 4 participants demonstrated faster walking speeds. Improvements in the 5 times sit-to-stand test and step test were noted in 3 and 4 participants, respectively. Spatiotemporal gait parameters revealed improvements in gait symmetry in 6 participants. Qualitative feedback based on the Assistive Technology Usability Questionnaire for People With Neurological Diseases (NATU Quest) returned positive results in 3 participants. Overall outcomes, defined as meeting the individualized goals of each participant, were positive in 4 participants. Conclusions: This case series provides preliminary evidence that a single session with the EMS may offer benefits for functional mobility and gait quality for individuals with spasticity resulting from stroke or SCI. To our knowledge, this is the first report examining the effects of the EMS in participants with SCI and the first to include spatiotemporal gait parameters associated with its use. However, the small sample size, variable outcomes, and lack of a control group necessitate caution in interpreting these findings and preclude definitive conclusions regarding the efficacy of the EMS. Larger, controlled trials with repeated sessions of EMS use are required to establish the effectiveness and optimal application of the EMS for spasticity management.
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Improving Models to Predict Care Utilization Using Machine Learning: Retrospective Observational Study

Background: The use of artificial intelligence and machine learning (ML) tools is now common in the advancement of health care services and clinical risk estimation. Legacy systems make use of highly informative feature sets developed from years of clinical expertise and research to estimate different outcomes, but only recently have they been tested against novel statistical approaches. One such system, the Johns Hopkins Adjusted Clinical Group (ACG) System, is a long-standing and widely used approach to categorizing clinical risk factors, and it is amenable to ML techniques. Objective: This study aims to test the ACG System using a contrasted area under the receiver operating characteristic (AUROC) and classification optimization strategy and compare its performance against traditional logistic regression methods. Assuming that selected ML algorithms can be tuned to enhance overall measures of performance, this would strengthen arguments for incorporating them into ACG-related workflows. Methods: Using a retrospective observational design, prospective year estimates of all-cause hospitalization and elevated total cost were modeled using a cross-validation framework. Patients with elevated costs were identified as those falling above the 95th percentile of total amounts billed, including pharmacy costs. Hyperparameter settings for XGBoost (Extreme Gradient Boosting), random forest, and elastic net were determined using average cross-validated performances for and AUROC in a grid search aimed at maximizing either statistic. Additional iterated cross-validation was used to compare point-estimated average AUROC and -scores between models, further decomposed by sensitivity, positive predictive value, and -beta statistics. Results: There were 350,463 patients selected in 2019 from the Johns Hopkins Health System. Model features identified by the ACG System for predicting prospective year hospitalization and total cost were included in these analyses. Findings suggest small but statistically significant improvements in cross-validated AUROC and -scores over logistic regression, using either optimization strategy and XGBoost. Logistic models achieved average receiver operating characteristic values of 0.886 and 0.841 for cost and hospitalization, respectively, whereas XGBoost achieved 0.891 and 0.849, respectively. optimization yielded similar findings, with logistic models achieving 0.367 and 0.341 on average for hospitalization and cost, respectively, but XGBoost exceeded values for cost but not for hospitalization (0.411 and 0.328, respectively). Conclusions: The clinical implications of these findings and the effect of class imbalance on model calibration are explored, along with the limitations of these data and approach. The core finding is that logistic regression remains very well-suited to these tasks, especially in situations where the efficiency or interpretability of models is critical. Under conditions of imbalance, regressions tended to yield high-precision estimates for the outnumbered class. Nevertheless, the findings also underscore a diversity of suitable models depending on clinical use cases, each having its own tradeoffs for evaluating performance. As such, health systems must clearly identify the needs and expectations of a model before calibrating one for use.
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Real-World Engagement With a Generative AI Conversational Agent for Mental Health Support: Retrospective Descriptive Study

Background: Generative artificial intelligence (GenAI) conversational agents are increasingly integrated within digital mental health interventions (DMHIs). However, empirical data on real-world engagement, usage patterns, and satisfaction with GenAI conversational agents remain limited. Objective: This study examined real-world engagement among users who interacted with the GenAI conversational agent within Mental, a DMHI designed to support mental health. We aimed to (1) characterize users engaging with Mental’s GenAI conversational agent, (2) examine real-world usage patterns, (3) examine satisfaction and user feedback following sessions, and (4) explore preliminary predictors of engagement with Mental’s GenAI conversational agent. Methods: This retrospective study analyzed naturalistic user data from 5082 paid subscribers who engaged with Mental’s GenAI conversational agent between October 2024 and March 2026. Users’ onboarding characteristics (ie, sex, mindset, distress level, desire for greater discipline, and primary stressors) and session satisfaction were collected via optional app-native items; session-level engagement metrics were captured through backend app usage data. Descriptive statistics were used to characterize user demographics and usage patterns. Session satisfaction was compared across temporal engagement variables using ANOVAs and independent-samples tests. As an exploratory aim, session-level mixed-effects logistic regression was used to estimate predictors of session-to-session return, with session satisfaction as the primary predictor and moderation by self-reported mindset. Results: Among users reporting onboarding data, 78.8% (2610/3312) identified as male and 90.0% (2667/2964) reported moderate-to-high distress on an app-native item. A total of 59,602 sessions were recorded (mean 11.8 sessions per user), most frequently occurring in the evening (17,206/59,602, 28.9%) and outside traditional business hours (37,181/59,602, 62.4%). Mean session satisfaction was high (mean 4.5, SD 0.9) and did not differ by time of day or day of the week. The most commonly selected session descriptors were “Insightful” (9236/19,883, 46.5%), “Felt seen” (7974/19,883, 40.1%), and “Good advice” (7510/19,883, 37.8%). The session-to-session return rate was 92.6%, and 69.4% (3528/5082) of users returned after their first session. In an exploratory analysis, session satisfaction was a significant predictor of return (odds ratio 1.35, 95% CI 1.14-1.60; <.001), although this finding should be interpreted as hypothesis-generating. Conclusions: Users engaged with a GenAI conversational agent within the Mental app outside of traditional care hours and presented with high return rates. Objective behavioral engagement data (eg, session frequency, timing, and session-to-session return rate) provide novel evidence that GenAI conversational agents may sustain real-world engagement, including among individuals who face barriers to traditional mental health services. Future research should determine whether these engagement patterns translate into clinically meaningful outcomes.
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Blood Protein May Signal Dementia Risk Decades Before Symptoms Appear

A blood protein long associated with dementia in older adults may also identify people at increased risk decades before symptoms develop, according to a large international study published in Science Advances.

Analyzing data from six large longitudinal cohorts, researchers from the National Institute on Aging found that elevated levels of growth differentiation factor-15 (GDF15)—a circulating cytokine involved in inflammation and cellular stress responses—in adults younger than 55 years were associated with a significantly greater risk of developing dementia later in life, particularly vascular dementia. The findings suggest that molecular changes associated with neurodegeneration may be detectable years before cognitive symptoms emerge.

“Our findings extend existing evidence by demonstrating that elevated GDF15 levels are detectable in midlife—before age 55—in individuals who later develop dementia,’” the authors write.

The study included approximately 500,000 participants from the UK Biobank, more than 15,000 from the Atherosclerosis Risk in Communities (ARIC) study, nearly 5,700 from the AGES-Reykjavik Study, and three additional cohorts. Participants were followed for 15 to 25 years, enabling investigators to determine whether plasma GDF15 levels measured in midlife predicted future dementia.

Across nearly all cohorts, elevated plasma GDF15 was associated with increased risk for all-cause dementia. However, the relationship was strongest for vascular dementia, with effect sizes approximately two to five times greater than those observed for Alzheimer’s disease.

The distinction suggests GDF15 may be particularly useful for identifying individuals at risk for vascular cognitive impairment rather than the amyloid-driven pathology typically associated with Alzheimer’s disease. As the authors note, “the association was particularly pronounced for vascular dementia,” supporting the protein’s potential as an early marker of vascular brain injury.

To investigate whether GDF15 might play a biological role in disease rather than simply reflect ongoing pathology, the researchers performed Mendelian randomization analyses using genetic data. The analyses supported a potential causal relationship between elevated circulating GDF15 and Alzheimer’s disease and related dementias.

Additional analyses linked higher plasma GDF15 concentrations with several established indicators of neurodegeneration, including cerebral small vessel disease, elevated phosphorylated tau (pTau-181) in both plasma and cerebrospinal fluid, and increased neurofilament light, a marker of neuronal injury. In contrast, GDF15 was not associated with amyloid pathology, suggesting that it may reflect alternative disease mechanisms.

Instead, multiple lines of evidence pointed toward inflammation and immune dysregulation. Individuals with elevated GDF15 exhibited cerebrospinal fluid protein signatures consistent with neuroimmune activation, including complement activation, inflammatory signaling pathways, and disease-associated microglial responses.

To better understand these mechanisms, the investigators exposed cultured human macrophages to recombinant GDF15. The protein altered cellular pathways involved in interferon signaling, energy metabolism, and heme scavenging—processes that have all been implicated in dementia risk. Together, the experimental and clinical findings suggest that GDF15 may actively influence neurodegeneration through immune and vascular pathways rather than acting solely as a marker of biological aging.

The authors conclude that “these findings support circulating GDF15’s role as an early biomarker—particularly for vascular dementia and neuroinflammation—and identify the mechanisms by which it may drive dementia risk.”

The post Blood Protein May Signal Dementia Risk Decades Before Symptoms Appear appeared first on Inside Precision Medicine.

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Implementing a Commercial AI Fracture Detection Tool in Health Care Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability Framework: A Formative Evaluation Study

Background: Artificial intelligence (AI) has the potential to enhance resource efficiency, improve patient treatment, and increase safety in health care. Still, there is limited knowledge on how to implement and evaluate AI solutions in real-world clinical settings. To address this gap, we conducted a formative process evaluation of the first large-scale procurement and implementation of a commercial AI solution in Norwegian health care. F The Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, was used for the formative process evaluation throughout the 4-year project to guide data collection, analysis, and real-time feedback. Objective: This study aimed to evaluate the usefulness of the NASSS framework for formative process evaluation of AI implementation in health care. Methods: A formative process evaluation was conducted from 2020 to 2024, covering the procurement, preimplementation, and implementation phases. Data included 65 interviews, observations, and document analysis. Data were analyzed thematically using the 7 NASSS domains, supplemented with subtopics within each domain to capture emerging infrastructural complexities and temporal dynamics. Real-time findings were discussed with the implementation team, decision-makers, and clinicians. Results: Key factors for successful implementation included clinician trust, workflow integration, task distribution, and digital maturity. Major challenges comprised limited documentation of Conformité Européenne–marked solutions, deskilling, and misaligned financial incentives. The NASSS framework enabled the identification of sociotechnical values and complexities, but did not fully capture workflow evolution and changing user perceptions over time. Conclusions: The NASSS framework is useful for evaluating AI implementation but requires adaptation to capture temporal dynamics and workflow changes better. These findings contribute to improving evaluation approaches for AI in health care.
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BIO 2026: AI, federal policy impacts, and general vibes

This was my first year attending BIO. JPM is called the “Super Bowl of biotech,” so with delegations from dozens of countries in attendance, you might say BIO is the World Cup. The big question I had going in, like with any other industry event, was “what are the vibes going to be like?” After witnessing some, frankly, bad overall moods at other major events last year, I was struck by how different things felt at BIO 2026. 

Joining me in San Diego were STAT biotech correspondent Meghana Keshavan, health tech reporter Brittany Trang, and Washington correspondent Daniel Payne. In this week’s STATus Report, you’ll get vibe checks from some industry executives and my three aforementioned colleagues and hear what difference a year can make.