Clinical and Translational Science

ImportanceGlucagon-like peptide-1 receptor agonists (GLP-1RAs) are fast-growing treatments for type 2 diabetes, obesity, and sleep apnea and are under investigation as potential treatments for many other conditions. The National Institutes of Healths (NIHs) All of Us Research Program offers a robust observational data source for studying questions related to GLP-1RA use in real-world settings. ObjectiveThis article describes key characteristics of All of Us participants who have been prescribed GLP-1RAs. The goals are to present the utility of the All of Us data and describe the strengths and limitations of using this resource for future research on GLP-1RAs. DesignUsing the All of Us Controlled Tier Curated Data Repository version 8 (CDRv8), we provide a descriptive analysis of the cohort with GLP-1RA records using cross-sectional surveys, longitudinal electronic health record (EHR) data, and longitudinal Fitbit data. SettingThe All of Us Research Program is a large, federally funded, longitudinal cohort study established in 2018 by NIH. Recruitment efforts are nationwide and target a range of populations to advance precision medicine for all. ParticipantsParticipants are U.S. residents, aged 18 or older at the time of study consent, who were enrolled between May 6, 2018, and October 1, 2023. ExposuresThe GLP-1RA cohort included participants with at least two GLP-1RA prescription records on different days at any time point based on their EHRs. Main OutcomesFrequencies and medians for a range of sociodemographic characteristics, health care utilization patterns, comorbid conditions, GLP-1RA prescription trends, laboratory and observation availability, and Fitbit data. ResultsThe All of Us GLP-1RA cohort is large (n=15 477), with high data availability across a range of relevant data types. These participants are older and have more comorbid conditions than the entire CDRv8 population. Prescription trends indicate rapid uptake of GLP-1RA drugs since 2014. Conclusions and RelevanceAll of Us CDRv8 is a valuable resource for research on GLP-1RAs across a large, heterogeneous cohort of participants. The variety and availability of data offer many possibilities for future observational, real-world research to address unanswered questions about GLP-1RA use and replicate recent findings generated from other datasets. Key pointsO_ST_ABSQuestionC_ST_ABSWhat data are available and what are the patterns of GLP-1 receptor agonist (GLP-1RA) prescriptions among participants in the All of Us Research Program? FindingsIn this descriptive cohort study of 633 534 All of Us participants, 15 477 participants had at least two records of GLP-1RA prescriptions. These participants tended to be older, have more comorbid conditions, and have higher health care utilization than the All of Us population as a whole. MeaningThe All of Us Research Program has a robust array of data to support observational studies of people receiving GLP-1RA prescriptions.

BackgroundDrug suitability is determined by safety, efficacy, and pathological appropriateness. The pharmacogenomics of drug suitability can be assessed by analyzing drug response and drug choice in large population cohorts. MethodsWe investigated drug response and drug choice for dyslipidemia and hypertension using genetic, phenotypic, and prescribing data from the UK Biobank and the All of Us Research Program. Drug response was reassessed with rigorous biomarker scaling, while genome-wide association studies (GWAS) and polygenic scores were used to examine genetic factors influencing drug choice. ResultsConventional analyses showed that variants influencing baseline LDL cholesterol (LDL-C) were inversely associated with absolute LDL-C change but concordant with relative change following statin therapy; these signals disappeared after applying a variance-stabilizing Box-Cox transformation, indicating a methodological artifact in biomarker scaling. GWAS for drug choice identified several significant loci and unique genetic correlation patterns with cardiometabolic traits. Polygenic scores for drug choice yielded statistically significant predictive performance, which was enhanced by incorporating demographic factors, though prediction strength in clinical settings remains modest. ConclusionVariance-stabilizing transformation corrects spurious pharmacogenetic associations introduced by biomarker scaling. Genetic variation informs drug choice for dyslipidemia and hypertension, but current polygenic scores provide only modest benefits in clinical application.

GLP-1 receptor agonists (GLP-1 RAs) are effective in delaying progression of chronic kidney disease in individuals with type 2 diabetes mellitus (T2DM). We evaluated whether GLP-1 RA prescription is associated with reduced nephrotoxicity in adults receiving long-term lithium therapy. We conducted a retrospective, propensity score-matched cohort study using electronic health records from the TriNetX global network, which includes de-identified data from over 127 million patients across 109 healthcare organizations. The study population consisted of adults aged [≥]18 years with T2DM, with lithium exposure within the 2 years preceding the index date and at least one prescription for a GLP-1 RA. The primary efficacy outcome was the rate of renal nephrotoxicity in persons with T2DM prescribed lithium and a GLP-1 RA versus those with T2DM prescribed lithium but no GLP-1 RA or other antidiabetic agents. Nephrotoxicity was a composite of ICD-10 and CPT-coded renal disease. Incidence and time-to-event outcomes were assessed using Kaplan-Meier curves and Cox proportional hazards models. In our 24-month analysis, 462 matched patient pairs were included. Initiation of a GLP-1 RA during lithium therapy was associated with a lower incidence of renal events versus lithium alone (6{middle dot}1% vs 10{middle dot}4%), corresponding to a risk difference of -4.3% (95% CI -7{middle dot}86 to -0{middle dot}80), a risk ratio of 0{middle dot}58 (95% CI 0{middle dot}37-0{middle dot}91; p=0{middle dot}017), and higher event-free survival (89{middle dot}0% vs 83{middle dot}2%; log-rank p=0{middle dot}037). GLP-1 receptor agonist therapy was associated with a reduction in reports of lithium-associated nephrotoxicity. Our findings provide impetus to conduct mechanistic renal histopathologic studies combining GLP-1 RAs with lithium.

Angioedema is a life-threatening adverse drug reaction associated with renin-angiotensin-aldosterone system (RAAS) inhibitors, characterized by localized swelling in the deep layers of the skin. Well-established evidence indicates an up to fivefold higher incidence of RAAS inhibitor-induced angioedema in self-identified Black patients compared to White patients. The mechanisms underlying this health disparity remain poorly understood and are often attributed to race, a poor proxy for interindividual genetic similarity and social stressors. Here, we investigate the genetic and social determinants of RAAS inhibitor-induced angioedema as well as the etiology of this racial difference. In particular, we (1) discovered OTULINL and CRABP1 as novel loci for RAAS inhibitor-induced angioedema, (2) confirmed the importance of bradykinin for this adverse drug reaction, (3) reported the first significant genome-wide association in self-identified Black participants, (4) identified alcohol use as an important social determinant, (5) demonstrated the strong role of variants enriched in 1000 Genomes African superpopulation-like genomes as the driver of racially differential angioedema risk, and (6) demonstrated the combined role of polygenic effect size and allele frequency differences in explaining these racial differences. Our results suggest that a clinical precision medicine tool may more precisely predict for whom RAAS inhibitors should be avoided (to prevent angioedema) compared to using race. These findings ultimately underscore the value of an evidence-based approach to removing race from treatment guidelines, which carries less potential harm than other removal strategies.

ImportanceAlcohol use is a leading cause of morbidity and mortality worldwide. Growing evidence suggests that glucagon-like peptide-1 receptor agonists (GLP-1RAs) may represent a novel potential pharmacotherapeutic tool for alcohol use disorder (AUD). ObjectiveTo examine the association between GLP-1RA prescriptions and alcohol use. DesignThis cohort study used a cross-sectional measure of alcohol consumption and longitudinal electronic health record (EHR) data collected between 1981 and October 2023 from NIHs All of Us Research Program participants. SettingAll of Us is a large program to recruit and collect surveys, EHR, genomic, and wearable data from a wide array of Americans. The data presented here are from the All of Us Curated Data Repository version 8. Participants393,596 All of Us participants with EHR data recruited across the United States. ExposureAt least two GLP-1RA prescription records in the EHR. Main Outcomes and MeasuresAlcohol Use Disorders Identification Test (AUDIT-C) scores and responses to individual AUDIT-C questions. ResultsAmong 15,447 participants with at least two recorded GLP-1RA prescriptions on separate days, 3650 had active GLP-1RA prescriptions, 5642 would have future GLP-1RA prescriptions (primary comparison group), and 544 had former GLP-1RA prescriptions. Those with active GLP-1RA prescriptions had statistically significant but modestly lower AUDIT-C scores on average compared with those with future prescriptions (incidence rate ratio [IRR] of 0.95; 95% CI, 0.91-0.99; P = 0.01). Participants with a former GLP-1RA prescription had lower AUDIT-C scores compared with those with future prescriptions, but this difference was not statistically significant. Results were similar using a propensity-score matched comparison group with a lower average AUDIT-C score for the current GLP-1RA group (IRR = 0.89; 95% CI, 0.85-0.93; P = <0.001) and no significant difference for the former prescription group. Analysis of individual AUDIT-C questions shows a significant association with GLP-1RA prescriptions and frequency of drinking but not drinks per occasion or binge drinking. Conclusions and RelevanceThis studys findings indicate that GLP-1RAs may reduce alcohol consumption by decreasing use frequency. Experimental studies and randomized controlled trials are needed to test the mechanisms and potential efficacy of GLP-1RAs in people with AUD. KEY POINTSO_ST_ABSQuestionC_ST_ABSIs there an association between glucagon-like peptide-1 receptor agonist (GLP-1RA) prescriptions and alcohol consumption? FindingsIn this observational cohort study of 15 447 people with GLP-1RA prescriptions in NIHs All of Us cohort, active GLP-1RA prescriptions were associated with significantly lower Alcohol Use Disorders Identification Test (AUDIT-C) scores compared with scores of those who would have GLP-1RAs in the future and of a matched comparison group with no GLP-1RAs. People with former GLP-1RAs did not have lower AUDIT-C scores than these comparison groups. MeaningActive GLP-1RA use may be effective in reducing alcohol consumption.

BackgroundGlucagon-like peptide-1 (GLP-1) receptor agonists, including liraglutide and semaglutide, are widely prescribed to treat type 2 diabetes mellitus and obesity. Recent anecdotal reports have suggested these agents might be associated with allodynia, a neuropathic pain syndrome, but large-scale epidemiologic evidence is lacking. MethodsTo investigate this potential link, a retrospective cohort study was conducted using the IQVIA PharMetrics(R) Plus database. Adults aged 18 and older who initiated liraglutide, semaglutide, or bupropion-naltrexone between 2006 and 2020 were included, excluding those with prior diabetes or antihyperglycemic therapy. Incident allodynia was identified via ICD-9/10 codes as the primary outcome. ResultsAmong 20,504 new users, those on GLP-1 receptor agonists had an allodynia incidence of 35 per 1,000 person-years, compared to 15 per 1,000 person-years for bupropion-naltrexone users. Adjusted analyses demonstrated over a twofold increased risk of allodynia with GLP-1 receptor agonists (aHR 2.15, 95% CI 1.57-2.96). ConclusionThese findings emphasize the need for heightened clinical vigilance and further research into mechanisms and management.

IntroductionAnti-vascular endothelial growth factor (anti-VEGF) therapies are standards of care for vision-threatening retinal diseases. This retrospective observational study describes demographics, utilization, best recorded visual acuity (BRVA), and safety among eyes with neovascular age-related macular degeneration (nAMD), diabetic retinopathy (DR), diabetic macular edema (DME), or retinal vein occlusion (RVO) treated with the biosimilar aflibercept-ayyh (PAVBLU(R)) in routine clinical practice. MethodsElectronic medical records from the Retina Consultants of America database of patients receiving aflibercept-ayyh (12/1/2024-10/31/2025) were analyzed, focusing on eyes with [&ge;]84 days of follow-up. The index date was the first documented aflibercept-ayyh injection. Postindex data were used to assess treatment patterns, BRVA (Wilcoxon signed rank test), and adverse events of special interest (AESIs). ResultsA total of 1,000 consecutive eyes from 989 patients received 3,730 injections of aflibercept-ayyh; most (91%) switched from prior anti-VEGF therapy and 9% were anti-VEGF treatment-naive. Disease distribution was 58% nAMD, 19% RVO, 16% DME, and 7% DR. Among switchers, median (IQR) number of prior injections was 21 (8-46). Median (IQR) follow-up was 6.0 months (4.6-7.1). Median (IQR) number of aflibercept-ayyh injections per eye was 4 (3-5). Among eyes with [&ge;]84 days of follow-up (n=889), mean BRVA expressed as logarithm of minimum angle of resolution (logMAR) remained stable for switchers (0.4 to 0.4; P=0.96) and improved from baseline in anti-VEGF-naive eyes (0.5 to 0.4; P<0.01). Confirmed AESIs included iritis (n=2; 0.05% of injections), with no events of vitreous cells, endophthalmitis, retinal detachment, retinal vasculitis, or vitreous hemorrhage. ConclusionIn this descriptive real-world analysis, aflibercept-ayyh was associated with stable visual acuity in previously treated eyes and vision improvement in treatment-naive eyes, with no new or unexpected safety findings, consistent with expectations for aflibercept. These findings add real-world experience to preexisting evidence demonstrating no clinically meaningful differences between aflibercept-ayyh (PAVBLU(R)) and reference aflibercept (EYLEA(R)). KEY SUMMARY POINTSO_ST_ABSWhy carry out this study?C_ST_ABSO_LIThe anti-vascular endothelial growth factor (VEGF) drug aflibercept, approved in 2011 and marketed in the United States as EYLEA(R),* has demonstrated efficacy in treating retinal diseases such as neovascular age-related macular degeneration (nAMD), diabetic retinopathy (DR), diabetic macular edema (DME), or retinal vein occlusion (RVO) and is a standard of care for these disorders. C_LIO_LIAflibercept-ayyh is a biosimilar to aflibercept that has demonstrated comparable efficacy and safety in the treatment of nAMD in a randomized controlled clinical trial. C_LIO_LIThis study describes the real-world use patterns, vision outcomes, and safety of aflibercept-ayyh in clinical settings in the United States for the treatment of nAMD, DR, DME, and RVO. C_LI What was learned from the study?O_LIIn this real-world study of 1,000 consecutive eyes treated with the biosimilar aflibercept-ayyh in patients with retinal diseases, we observed no new safety concerns and that aflibercept-ayyh maintained visual acuity in eyes switching anti-VEGF agents and improved vision in anti-VEGF-naive eyes, consistent with expected responses to aflibercept. C_LIO_LIThese findings support aflibercept-ayyh as a suitable treatment option when anti-VEGF therapy is indicated. *EYLEA(R) is a registered trademark of Regeneron Pharmaceuticals, Inc. PAVBLU(R) is a registered trademark of Amgen Inc. C_LI

ContextErogothioniene (EGT), a potent natural antioxidant, exerts hepatoprotection. However, human clinical evidence remains absent. Objectiveto observe the clinical efficacy and safety studies of GeneIII(R) L-Ergothioneine Capsules in the Hepatoprotective Efficacy. Materials and methodsThirty subjects with some abnormal liver function indicators were selected to take 2 capsules of 30mg GeneIII(R) L-Ergothioneine Capsules per day, for 30 consecutive days. The changes in serum liver function biomarkers, clinical efficacy self-rating scale, and Pittsburgh sleep quality index scale (PSQI) from baseline in different visit cycles were compared by self-control. All adverse events that occured after receiving the trial medication were also tracked and the incidence of adverse events during the trial period was calculated. ResultsAll subjects completed treatment and follow-up. After taking GeneIII(R) L-Ergothioneine Capsules, the subjects aspartate aminotransferase (AST) levels were significantly reduced compared to baseline (p=0.0082). Additionally, alanine aminotransferase (ALT) levels were also significantly reduced (p=0.0025), gamma-glutamyl transferase (GGT) levels were significantly reduced compared to baseline (p=0.0270). Physical function scores on the Clinical Efficacy Self-Assessment Scale improved significantly compared to baseline. Physical function scores decreased significantly by 39.04% compared to baseline (p<0.0001). Additionally, the level of daytime functional impairment on the Pittsburgh Sleep Quality Index was significantly reduced by 51.56% compared to baseline (p=0.0038). No adverse events occurred throughout the study. No side effects were observed clinically, confirming the reliable safety of GeneIII(R) L-Ergothioneine Capsules under the current study design. ConclusionGeneIII(R) L-Ergothioneine Capsules have a significant effect on improving liver function, physical function, and sleep quality in subjects, and the overall safety is good.

Human genetics has become a cornerstone of drug target discovery, yet the value of Mendelian randomization (MR) for predicting clinical success remains uncertain. Here, we systematically evaluated MR across 11,482 target-indication pairs with documented Phase II clinical outcomes to assess its utility for drug development. We find that MR statistical significance alone does not enrich for Phase II success, in contrast to genome-wide association study (GWAS) support, which confers an increase in success probability. However, this apparent limitation reflects the heterogeneous nature of clinical failure and the fact that MR encodes information beyond P values. When MR-derived features, including instrument strength and explained variance, are integrated into machine learning models, predictive performance improves substantially. An MR-informed XGBoost classifier identifies target-indication pairs with a 55% overall approval rate, corresponding to a 6.4-fold enrichment over unstratified programs and a 2.8-fold improvement over GWAS- supported targets in Phase II. Notably, this enrichment is achieved without reliance on statistically significant MR results. Our findings demonstrate that MR is most informative when treated as a graded, context-dependent source of causal evidence rather than a binary hypothesis test, and that its integration with machine learning enables scalable, genetics-informed prioritization of drug targets across the clinical pipeline.

Autologous CAR-T cell therapy has demonstrated remarkable clinical efficacy in hematologic malignancies, yet its broader application remains limited by complex, labor-intensive manufacturing and inconsistent product quality. We describe a novel microfluidic cell separation platform based on Deterministic Lateral Displacement (DLD), integrated into a fully automated, closed-system instrument (Curate System), capable of processing full leukopacks in under one hour. Compared to Ficoll(R)-based density gradient centrifugation, DLD processing yielded significantly higher leukocyte recovery (88% vs. 58%), superior platelet and red blood cell depletion, and reduced CD69 T-cell activation. Flow cytometric analysis revealed improved phenotypic preservation across key T-cell subsets, including naive and central memory populations. Cytokine profiling demonstrated enhanced washing efficiency, with markedly lower levels of biologic response modifiers such as RANTES and TGF-{beta}1. DLD-purified T cells exhibited enhanced expansion kinetics and greater yield, supporting improved manufacturing outcomes. These findings position DLD-based processing as a clinically relevant, scalable alternative to conventional methods, with potential to improve consistency, potency, and accessibility of CAR-T therapies.

We designed a platform model that integrates physiologically-based pharmacokinetic (PBPK) modeling with quantitative systems pharmacology (QSP) to bridge translational challenges in antibody-drug conjugate (ADC) development. The PBPK-QSP platform model was developed for the ADC trastuzumab emtansine (T-DM1) in breast cancer patients. This mechanistic framework facilitates translation across preclinical in vitro experiments, in vivo studies, and clinical trials, supporting decision-making for novel ADCs. The PBPK-QSP model adequately predicts preclinical and clinical PK and PD data from two additional ADCs: trastuzumab deruxtecan (T-Dxd) and tusamitamab ravtansine. For within-target validation with T-Dxd in breast cancer, despite extensive preclinical calibration, efficacy predictions were initially overly optimistic compared to T-DM1 validation experience with the model and aggregated phase II trial data. Individual patient data from a phase II T-Dxd trial allowed evaluation of model performance and quantification of translational uncertainty in predicting clinical outcomes using preclinical experiments. Cross-pathway validation with tusamitamab ravtansine in non-small cell lung cancer has revealed the importance of incorporating a resistance module to describe clinical efficacy adequately. Clinical trial simulations for tusamitamab ravtansine subsequently inform that alternative fractional dosing could offer a potential efficacy advantage compared to existing clinical dosing. We integrated these insights into a practical recommended workflow for translational development programs, which addresses the key challenges in parameter estimation, data requirements, and uncertainty quantification in the key system parameters for each indication and cancer type. Ultimately, integrating an interactive modeling platform with a structured workflow to mitigate the risks of human translation and to potentially improve the clinical benefits of novel ADCs in oncology drug development.

ObjectivesThe 2025 Global Consensus recommends continuing biologics throughout pregnancy in women with inflammatory bowel disease (IBD). Real-world evidence on biologic treatment patterns and outcomes remains limited. This study compared maternal and neonatal outcomes across different biologic use trajectories during pregnancy. MethodsA retrospective study was performed in pregnant women with IBD, treated and/or delivering at the University Hospitals Leuven, Belgium, between 2017 and 2025. Patients were categorized as continuers, discontinuers, non-users or initiators of biologics during pregnancy ResultsAmong 255 pregnancies, 103 (40.4%) were continuers, 68 (26.7%) discontinuers, 77 (30.2%) non-users, and 7 (2.7%) initiators. Before conception, 67.1% used biologics. Third-trimester disease activity was most frequent in initiators (42.9%, 3/7) and discontinuers (19.1%, 13/68), followed by non-users (14.3%, 11/77) and continuers (13.6%, 14/103). C-sections occurred more often in non-users (41.3%, 26/63) and discontinuers (39.4%, 26/66) than continuers (31.1%, 23/74). Preterm birth was more common among initiators (14.3%, 1/7) and discontinuers (12.1%, 8/66) than continuers (8.0%, 6/75) and non-users (3.2%, 2/62). Low birthweight occurred most in initiators (14.3%, 1/7), continuers (8.1%, 6/74) and discontinuers (6.1%, 4/66). Small-for-gestational-age infants were most frequent among continuers (14.9%, 11/74) and initiators (14.3%, 1/7) than discontinuers (7.6%, 5/66). ConclusionsWomen who discontinued biologics during pregnancy had higher rates of C-sections, preterm birth, and third-trimester disease activity than continuers, supporting continuation of biologics in pregnancy. The higher SGA rates among continuers, however, require further investigation. Initiators showed the poorest outcomes, highlighting the need for adequate disease control before and during pregnancy.

BackgroundBiomedical Large Language Models (LLMs) combined with prompt engineering offer domain-specific reasoning, yet their application to individual-level causality assessment remains unexplored. This study evaluated five combinations of biomedical LLMs, prompting strategies, and causality algorithms by comparing their agreement with two human expert evaluators. Research design and methodsA total of 150 Individual Case Safety Reports (ICSRs) were analyzed: 140 reports from Food and Drug Administration Adverse Event Reporting System (FAERS), and 10 myocarditis/pericarditis ICSRs from Vaccine AERS (VAERS). Assessments were conducted using the Naranjo and WHO-UMC algorithms. Biomedical LLMs tested included TinyLlama 1.1B, Medicine LLaMA-3 8B, and MedLLaMA v20, combined with Chain-of-Thought (CoT) or Decomposition prompting. Agreement was measured using Gwets Agreement Coefficient 1 (AC1) and percentage agreement, alongside performance metrics and qualitative error analysis. ResultsThe Medicine LLaMA-3 8B-Naranjo-CoT combination achieved the highest agreement with human assessors for the final classification of causality (64%). Biomedical LLMs demonstrated low inter-rater agreement on critical items of causality assessment such as identification of listed AE, temporal plausibility, alternative causes, and objective evidence of AEs. Frequent model failures included irrelevant responses. ConclusionsBiomedical LLMs showed improved performance over general purpose models previously tested but remain suboptimal for reliable causality assessment of ICSRs.

BackgroundMetabolic dysfunction-associated steatohepatitis (MASH) is a prevalent and progressive liver disease with limited pharmacologic treatment options. Pemvidutide, a GLP-1-glucagon dual receptor agonist, has shown promise in targeting both hepatic steatosis and fibrosis. This systematic review and meta-analysis aimed to evaluate the efficacy and safety of pemvidutide in adults with MASH. MethodsWe systematically searched PubMed, Scopus, Web of Science, and Cochrane CENTRAL through December 15, 2025, for randomized controlled trials (RCTs) comparing once-weekly subcutaneous pemvidutide (1.2 mg, 1.8 mg, or 2.4 mg) with placebo in adult MASH patients. Primary outcomes were changes in liver fat content (LFC, % via MRI-PDFF) and Enhanced Liver Fibrosis (ELF) score. Secondary outcomes included body weight, glycemic and lipid parameters, blood pressure, heart rate, and adverse gastrointestinal events. Dose-specific pairwise meta-analyses were performed using a random-effects model. ResultsThree RCTs encompassing 370 participants (195 pemvidutide, 175 placebo) were included. Pemvidutide significantly reduced LFC at all doses, with the greatest effect at 1.8 mg (MD = -21.63%, 95% CI: -27.23 to -16.02; p<0.0001). ELF score improvement was significant at 1.2 mg and 1.8 mg doses but not at 2.4 mg. Across all doses, body weight decreased significantly, while HbA1c remained unchanged. Pemvidutide also reduced systolic blood pressure and total cholesterol (1.8 mg and 2.4 mg), with modest HDL reduction at 2.4 mg. Mild-to-moderate gastrointestinal adverse events were observed, with nausea more frequent at 1.8 mg. ConclusionsPemvidutide is effective in reducing liver fat and improving cardiometabolic parameters in MASH, with a favorable safety profile. Dose-specific effects on fibrosis suggest potential early antifibrotic activity, highlighting its promise as a dual-targeted therapy for MASH. Further long-term studies are warranted to confirm sustained hepatic and metabolic benefits.

Virtual clinical trials (VCTs) hold significant promise for improving the drug development process, yet their predictive reliability depends critically on design decisions that remain poorly understood. This study examines how model complexity influences VCT outcomes, as well as how the choice of prior parameter distributions and virtual patient inclusion criteria affects those outcomes. Using oncolytic virotherapy treatment of murine tumors as a case study, we compared three mathematical models of varying complexity under different parameter priors (uniform and normal distributions) and two inclusion methods (accept-or-reject and accept-or-perturb). Our results demonstrate that the simplest model produces a plausible population that inadequately spans the feasible trajectory space, potentially missing critical interpatient heterogeneity. However, we found diminishing returns beyond intermediate model complexity, as both the intermediate and complex models captured similar ranges of patient responses across dosing protocols. Notably, the accept-or-reject method generated posterior parameter distributions that resembled the chosen priors, possibly overly reducing interpatient variability in treatment responses, particularly at high doses. In contrast, the accept-or-perturb inclusion criteria produced more robust results that were less sensitive to prior assumptions. These findings suggest that VCT design should prioritize models with sufficient biological detail to capture key mechanisms without unnecessary complexity, paired with inclusion criteria that avoid over-constraining plausible populations to match potentially unrealistic prior assumptions.

BackgroundIn the past two decades, genetic studies have elucidated the contributions of key biological pathways to the pathogenesis of age-related macular degeneration (AMD), including complement activation, lipoprotein metabolism, angiogenesis, and extracellular matrix maintenance. Of these pathways, complement in particular has been observed to dominate the genetic architecture of AMD. Yet, clinical treatment of AMD with complement inhibitors has met with limited success. MethodsUsing data from four large-scale cohorts spanning 30,251 AMD cases and 438,016 AMD controls, we identified functional genetic variants to serve as proxies for complement inhibitor drug effects, and assessed their interaction with a pathway-specific AMD polygenic risk score (PRS). In each cohort, subjects were divided into low, medium, and high AMD risk groups based on quantiles of the PRS, such that each risk group included one-third of the cohorts AMD cases. Drug target variant associations with AMD were evaluated in each risk group, as well as in all-comers. Quantitative biomarker analysis leveraging retinal phenotypes derived from optical coherence tomography (OCT) data was also performed. ResultsGenetic proxies for C3 and CFB inhibition had an effect on AMD risk that was 1.6 to 2.3 times higher in the high PRS group compared to all-comers. Interactions between genetic drug proxies and the PRS was statistically significant, with replication across cohorts. Statistical support was strongest in three cohorts for C3 and across all four cohorts for CFB. Examining a retinal thickness phenotype (ISOS-RPE), genetic drug proxy by PRS interaction was nominally significant for CFB, and directionally consistent for C3. Our results point to a continuous relationship between genetic complement activation / inhibition and AMD risk, across disease stages, without threshold effects. ConclusionOur findings suggest that patient heterogeneity due to genetically-influenced complement activation may explain the limited efficacy of AMD treatment with complement inhibitors to date. Prospective studies are warranted to assess whether precision therapy with complement inhibitors may be achieved by enrichment of patients with high PRS in future trials.

Inflammatory pain is a major clinical challenge, yet appropriate human models mimicking local infection are lacking. We established a novel human pain model based on intradermal administration of lipopolysaccharide (LPS), a component of Gram-negative bacteria, and investigated the time course and underlying molecular mechanisms of inflammatory pain hypersensitivity. In a placebo-controlled pilot study with 12 healthy subjects, the intradermal LPS injection induced hyperaemia peaking at 4.5 h and mechanical hypersensitivity peaking at 6 h. Hypersensitivity to increasingly acidic injections and mechanical pinch lasted longer than hyperaemia. The double-blind, randomized, placebo-controlled full crossover main study was completed by 40 subjects and investigated the role of the Receptor for Advanced Glycation End-products (RAGE). Co-injection of the RAGE antagonist azeliragon largely reduced LPS-induced hyperaemia (-87%) and significantly attenuated hypersensitivity to mechanical (-55%) and increasingly acidic stimuli (-40%). In contrast, the Toll-like receptor 4 antagonist resatorvid had no effect on any readout. In both naive and inflamed skin, TRPV1 antagonist BCTC inhibited the majority of acid-induced pain. LPS-induced inflammation caused a substantial shift in the pH sensitivity of pain, suggesting that even mild tissue acidification contributes to inflammatory pain. The human LPS skin inflammation model is largely RAGE-dependent, highlighting its potential as a target in inflammation.

BackgroundPsychedelics exert widespread effects on brain activity, but their impact on motor function is unclear. This is clinically relevant given the emerging interest in psychedelic-assisted physical therapy for disorders of motor function. This studys primary objectives examined the feasibility and safety of administering movement tasks following low-to-moderate doses of psilocybin in healthy volunteers. MethodsHealthy participants were randomly assigned three psilocybin doses consisting of either (1) 5mg, 10mg, and 15mg, or (2) 10mg, 15mg, and 20mg, with at least one week between doses. Movement tasks were administered during the acute drug effects. Participants, physiotherapists, and statisticians were blinded to the dosing order. Feasibility was assessed by evaluating completion of the de Morton Mobility Index and Functional Movement Exploration (measures of gross motor function). Safety outcomes included vital signs and adverse events. Additional exploratory motor outcomes included the Action Research Arm Test (assessing dexterity), Box and Block Test (Original and Modified versions) (combining dexterity with motor speed), Digit Symbol Substitution Test (combining motor speed with intellectual functions), and Reaction Time Ruler Drop Test (assessing reaction time). The 5-Dimensional Altered States of Consciousness and Ego-Dissolution Inventory assessed changes in states of consciousness. Blinding efficacy was assessed by asking participants and physiotherapists to guess the doses administered. ResultsThirteen participants were randomised: seven to 5mg, 10mg, and 15mg; six to 10mg, 15mg, and 20mg. One participant was unable to complete several movement tasks at 20mg. Nausea (n=8, 62%) and headache (n=7, 54%) were the most common adverse events. No serious adverse events or adverse events related to movement task administration occurred. Median values [interquartile ranges] remained near-perfect across doses for the de Morton Mobility Index (92.5-100.0 [85.0-100.0]), Functional Movement Exploration (100.0 [96.0-100.0]), and Action Research Arm Test (56.0-57.0 [52.0-57.0]). Baseline Box and Block Test (Original) median scores (65.0 [60.0-67.0]) improved to 79.0 [70.0-83.0] at 5mg and 4.5 hours post-dose (5mg-4.5H), and worsened to 57.5 [51.0-64.0] at 20mg-1.5H. Baseline Box and Block Test (Modified) median scores (48.0 [47.0-53.0]) worsened to 43.0 [35.0-45.0] at 20mg-1.5H. Baseline Digit Symbol Substitution Test median scores (73.0 [66.0-77.0]) improved to 87.0 [81.0-90.0] at 10mg-4.5H, and worsened to 62.0 [54.0-86.0] at 20mg-1.5H. Reaction Time Ruler Drop Test scores lacked consistent dose-related changes across participants. Changes in states of consciousness were greatest at 20mg. Participants and physiotherapists correctly guessed the administered dose 53% and 50% of the time, respectively. ConclusionsMovement tasks were feasible during psilocybin dosing up to 15mg. Impairments emerged at 20mg in tasks that combined motor and additional cognitive functions. These findings support the feasibility of performing complex movement tasks during psilocybin dosing and will inform the conduct of trials utilising psilocybin-assisted physical rehabilitation in neuropsychiatric disorders. Trial RegistrationAustralian New Zealand Clinical Trials Registry: ACTRN12621000560897 Date registered: 12 May 2021 URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381526&isReview=true Key FindingsO_LIThere is growing interest for psychedelic-assisted physical therapy in neuropsychiatric disorders of motor dysfunction, however, the impact of psychedelics on motor function remains unclear. C_LIO_LIThis study investigated the feasibility, safety, and impact on motor function of administering movement tasks following low-to-moderate doses of psilocybin in healthy volunteers. C_LIO_LIThese findings support the feasibility of performing complex movement tasks during psilocybin dosing up to 15mg and will inform the conduct of trials utilising psilocybin-assisted physical therapy in neuropsychiatric disorders. C_LI

ObjectivesTo evaluate whether a EHR cohort, alone and linked to Medicare claims, has sufficient data quality to support design elements required for target trial emulation, using type 2 diabetes (T2D) as a case example. Materials and MethodsWe constructed annual University of Florida Health EHR-Medicare linked cohorts of patients [&ge;] 65 years with T2D from 2013 to 2020. Using Medicare claims as the reference, we assessed EHR data quality for target trial emulation-relevant elements across completeness, accuracy, plausibility, and concordance, spanning target trial components (eligibility, exposure/new-user ascertainment, baseline covariates, outcomes, and follow-up). Data quality was compared across EHR-only, claims-only, and EHR-claims linked data. ResultsThe mean annual EHR-Medicare linked cohort included 12,895 patients (mean age 74.9 years; 58.0% female). Demographics were complete and highly accurate. In the EHR-only cohort, completeness ranged 34.1-78.4% for conditions and 53.7-63.4% for glucose lowering drugs (GLDs). Accuracy was high for prevalent conditions and GLD use but low for incident measures. Plausible values were common (>98.5%), and HbA1c - T2D concordance was strong (98.6%). Linking EHR and claims substantially improved completeness and accuracy, especially for encounters, mortality, incident diagnoses, and medications. DiscussionThe linked dataset addressed major limitations of EHR-only data and provided enhanced granularity compared to claims alone, offering a comprehensive resource for real-world target trial emulation research. ConclusionEHRs offer valuable clinical details but face data quality challenges. Robust quality assurance strategies and linkage with external data are essential to strengthen real-world evidence and support target trial emulation. Lay SummaryWe evaluated whether a University of Florida Health electronic health record (EHR) cohort--alone and when linked to Medicare claims--has sufficient data quality to support "target trial emulation," a common approach for using real-world data to study medication effects when randomized trials are not feasible. We studied adults aged 65 years and older with type 2 diabetes from 2013-2020 and assessed four practical dimensions of data quality: completeness (how often key information is captured), accuracy (agreement with Medicare for billing-derived elements), plausibility (whether recorded values are clinically reasonable), and concordance (internal consistency between related EHR elements). Demographic fields were highly complete and accurate, and most lab and vital sign values were biologically plausible, supporting the reliability of core EHR clinical measurements. However, the EHR alone missed a substantial share of encounters, deaths, incident diagnoses, and medication initiation events that appeared in Medicare, reflecting care received outside a single health system. Linking EHR with Medicare substantially improved capture of these cross-setting events while preserving EHR-only clinical details (e.g., HbA1c and BMI), yielding a more robust dataset for real-world target trial emulation research.

Artificial intelligence (AI), particularly large language models (LLMs), is increasingly explored in healthcare, yet its real-world usability and safety in high-risk clinical pharmacy tasks remain uncertain. Vancomycin therapeutic drug monitoring (TDM), which requires precise pharmacokinetic calculations and context-sensitive interpretation within a narrow therapeutic window, provides a stringent test case for AI-assisted decision support. This proof-of-concept study developed and evaluated a hybrid clinical decision support system (TDM-AID) integrating a validated deterministic pharmacokinetic calculation engine, GPT-4o-based structured clinical interpretation, and retrieval-augmented guideline support. Thirty retrospective adult vancomycin TDM cases were assessed using a weighted six-domain rubric covering pharmacokinetic accuracy, AUC estimation, prospective prediction, timing recommendations, clinical judgment, and documentation quality. Two independent expert pharmacists evaluated system outputs against benchmark consultations. The overall median performance was 78% (IQR 12%), classified as Acceptable, and 73% (IQR 14%) when deterministic calculations were excluded. Foundational pharmacokinetic calculations achieved 100% accuracy. Clinical judgment demonstrated Good performance (83%), whereas prospective prediction was limited (58%), and timing recommendations were absent in all cases. Safety violations occurred in 17% of cases, including dose recommendations exceeding 4 g/day. Inter-rater reliability was good (ICC 0.87). These findings suggest that hybrid AI-driven decision support is technically feasible and usable as a pharmacist-augmenting draft generator; however, limitations in predictive reasoning, timing logistics, and safety enforcement necessitate deterministic safeguards and mandatory expert oversight before clinical implementation.