Clinical and Translational Science

In some countries, melatonin is sold without a physician prescription and dosage is unregulated. Transdermal products have become popular including those marketed for children. We measured consumer assumptions about these products among adult residents of the United States, analyzed lot-to-lot variability, and compared the pharmacokinetics of melatonin administered in oral, lotion, and bath product forms. Survey respondents (n=199) believed oral melatonin was more effective than transdermal products and that all melatonin products were relatively safe. Melatonin lotion products analyzed by HPLC displayed lot-to-lot variability as well as changes in formulation and product claims. To determine pharmacokinetics, three different treatments (oral tablets, lotion, and bath immersion) were administered to twelve undergraduate participants in a randomized, crossover design. Five additional participants completed bath product treatment only. Participants collected saliva samples up to 48 hours after administration, which were analyzed for melatonin by enzyme-linked immunosorbent assay. Oral (n=11) and lotion formulations (n=12) caused maximum salivary melatonin levels within 30 minutes after administration, but bath immersion did not cause increases in saliva melatonin (n=17). The half-life of oral melatonin was 1.17 [0.69 -- 1.65] hours versus 5.72 [3.75 -- 7.68] hours for lotion treatment (p = 0.011, effect size r = 0.770). Melatonin lotion may pose a risk to consumers who assume it is safe and less effective than oral tablets, when in fact it may be very potent and remain at high physiological levels into the following day. This study is registered on clinicaltrials.gov (NCT06382610) and was funded by the Sleep Research Society.

Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical application. Methods: Data from the FDA Adverse Event Reporting System (FAERS) database from the period of 2019 Q1-2025 Q3 were analyzed. Disproportionality analysis algorithms, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), were utilized to mine safety signals.The time to onset (TTO) was evaluated using the Weibull distribution model. Results: Among 11,697,906 reports, 4,177 EV-treated patients experienced 14,511 AEs. The most common System Organ Classes (SOCs) were skin and subcutaneous tissue disorders (18.23%), general disorders and administration site conditions (13.17%).Multi-algorithm consensus identified 179 positive signals. Alongside known toxicities (rash, peripheral neuropathy, hyperglycemia), potential new signals emerged, including dysgeusia, atypical skin lesions, and myelosuppression. Median TTO was 14 days, with the Weibull {beta} of 0.736, confirming an "early failure" profile. Subgroup analysis revealed toxicity heterogeneity: patients aged [&ge;]65 and females exhibited stronger signals for fatal severe cutaneous adverse reactions, while patients aged < 65 and males showed higher susceptibility to neurological and metabolic toxicities. Conclusions: The real-world safety profile of EV confirms known toxicities, reveals new risks (e.g., dysgeusia), and shows toxicity concentrated in the first treatment cycle. Clinical practice requires proactive monitoring during the first two weeks using demographic-specific strategies: vigilance for fatal skin toxicity in elderly and female patients, and close follow-up of neurological and metabolic indicators in younger and male populations.

UT-018, a stem cell chemoattractant formulation, demonstrated significant regenerative activity across independent murine wound-healing and hair-regeneration studies. Topical treatment accelerated wound closure, enhanced granulation tissue formation, improved collagen organization, increased fibroblast proliferation, and enhanced dermal vascularization. Separate hair-growth studies demonstrated increased follicular density, deeper follicular penetration, enhanced dermal vascularization, and induction of anagen-phase transition by UT-018. Mechanistic studies demonstrated strong intracellular cAMP generation and activation-associated {beta}-catenin phosphorylation consistent with GPCR-mediated regenerative signaling.

Background: Mocravimod is an oral sphingosine-1-phosphate (S1P) receptor modulator. This Phase 1 multiple-ascending-dose study evaluated its safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) in healthy volunteers. Methods: In this double-blind, randomized, placebo-controlled, parallel-group trial, 60 healthy male volunteers were enrolled in five cohorts. Mocravimod was administered once daily at 0.3, 0.6, 1.2, or 3.0 mg for 14 days, or at 2.0 mg for 28 days. Safety assessments included adverse events (AEs), laboratory tests, vital signs, electrocardiography, and Holter monitoring. PK of mocravimod and its active metabolite, mocravimod-phosphate, and PD effects on absolute lymphocyte count (ALC) and leukocyte subsets were assessed. Results: Fifty-nine of 60 participants completed the study. One participant in the 3.0 mg cohort discontinued treatment because of asymptomatic transaminase elevation. No deaths or serious AEs occurred. AEs were mostly mild or moderate, transient, and showed no clear dose relationship. Mocravimod produced dose-dependent reductions in ALC from 0.6 mg onward, with maximum geometric mean reductions of 65%, 74%, 83%, and 77% at 0.6, 1.2, 2.0, and 3.0 mg, respectively. ALC values recovered to above the lower limit of normal during follow-up in all cohorts. Holter monitoring showed an initial placebo-corrected reduction in heart rate of approximately 10-15 beats/min at doses of 1.2-3.0 mg, which attenuated with continued dosing. One participant in the 3.0 mg cohort had a recurrent daytime second-degree atrioventricular block (Mobitz I/Wenckebach), reported as a mild non-dose-limiting AE. No QT prolongation was observed. Exposure to mocravimod and mocravimod-phosphate increased approximately dose-proportionally. Steady state was reached by Day 14 (Day 28 in the 2.0 mg cohort), accumulation was approximately five- to sevenfold, terminal half-lives were approximately 100-40 hours for both analytes, and parent-to-metabolite exposure ratios were close to 1. Conclusions: Once-daily mocravimod up to 3.0 mg for 14 days and 2.0 mg for 28 days was generally well tolerated and showed predictable S1P-modulator class effects on lymphocyte counts and heart rate, with PK properties supporting once-daily dosing and further clinical development.

BackgroundThe discontinuation of Fasiglifam (TAK-875), a GPR40/FFAR1 full agonist, during Phase 3 clinical trials due to hepatotoxicity led to widespread abandonment of GPR40 as a viable therapeutic target for type 2 diabetes mellitus (T2DM). However, mechanistic evidence suggests that Fasiglifams hepatotoxicity arises from mitochondrial liability driven by high lipophilicity (aLogP = 5.31), rather than from on-target GPR40 signaling. We hypothesized that target-level failure was incorrectly inferred from compound-level safety concerns, and that superior candidates exist within publicly available databases. MethodsWe queried ChEMBL Release 36 (28 GB SQLite, 74 tables) for all compounds with documented GPR40/FFAR1 activity (UniProt: O14842). Compounds were filtered by EC50 [&le;] 10 nM in nM units with standard relation "=". Drug-likeness was assessed using Lipinskis Rule of Five (Ro5), aLogP, molecular weight (MW), hydrogen bond donors/acceptors (HBD/HBA), and polar surface area (PSA). A parallel analysis of Therapeutic Target Database (TTD v10.1.01, 4,298 targets) provided clinical context. A real-world evidence (RWE) patient stratification framework was constructed using EMR data from tens of millions of patients with >10 years of longitudinal follow-up. ResultsOf 2,637 GPR40-active compounds in ChEMBL 36, 526 (19.9%) demonstrated EC50 < 100 nM and 102 (3.9%) demonstrated EC50 < 10 nM. Eight compounds met stringent drug-likeness criteria (Ro5 violations = 0, aLogP < 5.0, EC50 [&le;] 1 nM). The lead compound (CHEMBL4859651) exhibited EC50 = 0.04 nM (8.75-fold more potent than Fasiglifam), MW = 297 Da (43% lower), and aLogP = 4.30 (19% lower), with zero Ro5 violations. Mean MW of the eight candidates was 317 {+/-} 28 Da versus 524 Da for Fasiglifam. A parallel GCK analysis identified a protein-protein interaction target (CHEMBL3885579, GCK-GKRP interface) harboring 40 exclusive compounds as an orthogonal strategy for partial GCK activation. ConclusionsSystematic cheminformatic analysis reveals that compounds with substantially superior activity and drug-likeness profiles relative to Fasiglifam exist within ChEMBL 36. Fasiglifams hepatotoxicity is attributable to compound-specific physicochemical properties, not GPR40-mediated toxicity. RWE patient stratification may further mitigate hepatotoxicity risk for next-generation GPR40 agonists. These findings argue for systematic reappraisal of GPR40 as a viable therapeutic target for T2DM.

Gray-market retatrutide use is increasing, but patient safety experiences remain poorly characterized. This cross-sectional analysis examined Reddit posts and comments from retatrutide-specific and broader peptide or weight-management communities through December 2025. A validated large language model classified self-reported retatrutide use and extracted author-attributed symptoms mapped to MedDRA Preferred Terms. Among 13,589 users reporting current use, 7,823 had at least one mapped symptom after exclusions. Unlike phase 2 trial findings dominated by gastrointestinal events, Reddit reports most often described appetite increase, fatigue, increased energy, nausea, food craving, insomnia, and elevated heart rate. Findings are hypothesis-generating and warrant pharmacovigilance attention.

Abstract Introduction The sharing of individual patient data is essential for advancing pharmacometrics but is strictly limited by privacy regulations (e.g., GDPR). While synthetic data generation offers a legally compliant alternative, its structural impact on complex nonlinear mixed-effects (NLME) modelling remains largely unexplored. This study aimed to benchmark five generative artificial intelligence algorithms by evaluating the balance between data privacy and the preservation of structural PK properties and clinical dosing guidance. Material & methods A daptomycin two-compartment PopPK model was used to simulate a reference cohort of 500 patients. Five generative algorithms (Modified AVATAR, Gaussian Copula, Synthpop, TVAE, and CTGAN) produced 100 independent synthetic datasets each. A two-stage evaluation framework was applied: first, a statistical indistinguishability test based on logistic regression (AUC ROC) was used as a macroscopic pre-selection criterion to determine algorithm eligibility for NLME modelling and privacy risk assessment. Privacy risk was independently quantified using the Anonymeter framework (Singling Out and Linkability attacks). Eligible algorithms were further evaluated on PK parameter recovery bias and clinical dosing simulations. Results Deep learning architectures (TVAE, CTGAN) were excluded at the pre-selection stage due to both biologically implausible covariate generation and high macroscopic detectability (mean AUC ROC = 0.837 and 0.986, respectively). Synthpop, AVATAR, and Gaussian Copula all passed the indistinguishability threshold (AUC ROC = 0.475 +- 0.033, 0.490 +- 0.013, and 0.619 +- 0.031, respectively) and proceeded to NLME evaluation. However, attack-based privacy assessment revealed that Synthpop carried an unacceptable singling-out risk (0.035), disqualifying it from privacy-preserving data sharing. AVATAR and Gaussian Copula demonstrated acceptable privacy profiles (singling-out = 0.004 and 0.001; linkability = 0.010 and 0.003, respectively). At the structural level, Gaussian Copula injected stochastic noise inflating residual error (+157.0%) and V1; (+25.9%), blunting predicted Cmax and predisposing to empirical dose escalation and risk of toxicity. AVATAR acted aSs a smoothing filter, deflating V2; (-48.3%) and underestimating CL (-12.9%). Forward clinical simulations confirmed directionally opposed prediction errors: Gaussian Copula consistently underestimated Cmax across standard and renally impaired profiles (-14.5% and -16.0%, respectively), predisposing to empirical dose escalation, whereas AVATAR- and Synthpop-derived models overestimated Cmax and Cmin in the obese infected patient (+14.7% and +8.2%, respectively), compounding the accumulation risk already present in this profile. Conclusion While no generative algorithm currently offers a perfect solution, AVATAR and Gaussian Copula represent the most viable candidates, being the only methods to satisfy both macroscopic indistinguishability and attack-based privacy criteria. These findings highlight the necessity of a structured, two-stage validation framework and suggest that, when coupled with therapeutic drug monitoring, synthetic datasets could significantly enhance multicentre collaboration while maintaining strict regulatory compliance

Manufacturers are adopting propellants for use in pressurized metered-dose inhalers (pMDIs) that have lower global warming potentials (GWPs) than the propellants traditionally used in pMDIs. Hydrofluoroalkane (HFA)-134a has been used as the propellant in the pMDI used to deliver the fixed-dose triple combination of budesonide, glycopyrrolate and formoterol fumarate (BGF); following successful clinical evaluation, the BGF pMDI is now being transitioned to the next generation propellant hydrofluoroolefin (HFO)-1234ze(E), which has near-zero GWP. We describe formulation development efforts that led to selection of HFO-1234ze(E) over another propellant, HFA-152a, for reformulation. Propellant-specific studies evaluated active pharmaceutical ingredient (API) stability and aerodynamic particle size distribution (aPSD). Those analyses have been complemented by in silico regional lung deposition modeling conducted after the clinical evaluation of the reformulated BGF pMDI. HFO-1234ze(E) supported favorable stability and aPSD characteristics for BGF pMDI reformulation, compared with HFA-152a, and modeling predicted regional deposition consistent with therapeutic intent. Given that each pMDI is a unique combination of APIs, device, propellant, and excipients, propellant substitution requires product-specific evidence and regulatory approval, and typically takes several years. Targeted analyses, such as those described here, helped to identify the most suitable candidate propellant for successful substitution in the BGF pMDI. HighlightsO_LIFormulation development efforts that led to evaluation of a budesonide-glycopyrrolate-formoterol fumarate pressurized metered-dose inhaler (BGF pMDI) reformulated with the next generation propellant HFO-1234ze(E) in a clinical trial program are described; the suitability of another propellant, HFA-152a, was also assessed C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% relative humidity [RH]), the HFA-152a formulation approached and, in one replicate, fell below the 90% of formulation label claim threshold of evaluation, whereas the original HFA-134a product and the HFO-1234ze(E) formulation remained above that threshold C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% RH) and 18 months under long-term stability storage conditions (25{degrees}C/60% RH), the fine particle mass and fine particle fraction for all active pharmaceutical ingredients (APIs) showed that the HFO-1234ze(E) formulation tracked more closely than the HFA-152a formulation to the original HFA-134a product C_LIO_LILater in silico modeling, conducted after clinical testing, predicted a trend for greater deposition of APIs in early airway generations with HFA-152a, whereas HFO-1234ze(E) was predicted to more closely match HFA-134a, indicating a greater likelihood of achieving equivalence to the original HFA-134a product with HFO-1234ze(E) than with HFA-152a C_LIO_LIBased on these analyses and other formulation development efforts, HFO-1234ze(E) was identified as the most suitable propellant for reformulation of the BGF pMDI; for HFA-152a, analyses raised concerns about storage stability, and differences in aerosol characteristics that can impact API deposition in the lungs and, in turn, efficacy C_LI

Drug-induced seizures remain a major safety concern in drug development, yet human seizure liability is difficult to predict using conventional preclinical models. Here, we evaluated whether spontaneous calcium network activity in human induced pluripotent stem cell-derived CNS-3D Brain Organoids could predict clinically observed seizure risk across a pharmacokinetically anchored drug set. CNS-3D organoids contained neuronal and astrocytic populations, expressed neuroactive receptor and ion-channel gene programs that aligned with human cortical tissue, and exhibited reproducible spontaneous calcium oscillations across production batches. A retrospective drug panel of 66 small-molecule drugs was assembled from human clinical evidence, including 30 seizure-associated drugs and 36 comparator drugs without documented clinical seizure liability. Drugs were tested across concentration ranges anchored to reported clinical Cmax, and calcium time-series responses were integrated with chemical structure features using a machine-learning workflow. The final model predicted clinical seizure liability with an AUROC of 0.872, achieving 83.3% sensitivity and 88.9% specificity in drug-level cross-validation. Model scores also stratified seizure-associated drugs by clinical context and prevalence, suggesting that CNS-3D activity profiles capture clinically meaningful differences in seizure risk. Compared with published in vitro and preclinical seizure-liability models, CNS-3D organoid-based predictions showed improved balanced sensitivity and specificity. These findings support high-throughput calcium profiling in human CNS-3D organoids as a scalable, exposure-aware platform for predicting human seizure liability and contributing functional human data to neuro-safety assessment.

Background: GLP-1 receptor agonists (GLP1-RAs) are an established treatment for type 2 diabetes mellitus (T2DM) and obesity. Their widespread use is set to increase through both indication expansion and patent expiry. As well as efficacy, it is crucial to understand the safety of this drug class to enable optimal use. Here we demonstrate how a genetic approach can augment signal-detection and post-market authorization surveillance. Methods: We used single nucleotide polymorphisms (SNPs) in GLP1R to recapitulate the effect of agonism with GLP1RAs on circulating glucose, glycated hemoglobin (HbA1c), body mass index (BMI) and risk of type 2 diabetes (T2DM) using Mendelian randomisation. We then tested if the adverse effect highlighted by medicines regulators of pancreatitis and the emerging effect of sarcopenia were causally related to GLP1R agonism, using this approach. Analyses were conducted in UK biobank and replicated in FinnGen and All of Us, results being combined using meta-analysis. Analyses were further stratified by a priori risk factors of age and alcohol consumption. Results: Genetically proxied GLP-1R agonism was associated with a reduction in glucose (exp({beta}) = 0.95 95% CI [0.94, 0.97]), HbA1c (exp({beta}) = 0.94 95% CI [0.92, 0.95]), and BMI (exp({beta})=0.98 95% CI [0.97, 0.99]); and a reduced risk of T2DM (OR = 0.82 95% CI [0.79 to 0.86]). Risk of acute and chronic pancreatitis was however increased (OR = 1.10 95% CI [1.01 to 1.20] and OR = 1.05 95% CI [0.95, 1.17], respectively), which varied as a function of age with risk most pronounced in those aged 50-59 years-old (OR = 1.79 95% CI [1.43, 2.24], OR = 1.57 95% CI [1.16, 2.12]) and in drinkers (OR = 1.32 95% CI [1.12, 1.54], OR = 1.36 95% CI [1.12, 1.65]). Risk of sarcopenia also increased (OR 1.34; 95% CI 1.05,1,71). Conclusions: Genetically proxied agonism with GLP-1RAs recapitulated the pharmacological effects of GLP1-1RAs on glycaemic traits, BMI and T2DM risk. This approach supports a causal effect of GLP-1RAs on the well reported adverse effects of pancreatitis and further indicates age and alcohol consumption as risk modifying effects. The less well reported but emerging effect of sarcopenia appears to also be casually related to agonism at GLP-1R. These analyses suggest a genetic approach could be used as an adjunct to signal detection studies to enhance safety regulation as well as personalisation of the use of these drugs.

Background: Platinum-based chemotherapy is known to cause severe and debilitating hearing loss, but unlike cisplatin, the true incidence of carboplatin-induced hearing loss remains unclear. We evaluated functional hearing outcomes in children receiving carboplatin to determine the incidence and severity of ototoxicity. Procedure: We identified a large cohort of children with cancer treated with carboplatin and graded their audiograms using the SIOP ototoxicity scale. Patients with inadequate audiological follow-up, prior hearing loss, or exposure to cisplatin were excluded. Fishers exact test, logistic regression, and ROC analyses were performed to investigate associations of demographic, treatment, and exposure-related risk factors with incidence of hearing loss. Results: 200 patients were included, all of whom had been treated with carboplatin. Only nine (4.5%) patients developed clinically significant hearing loss (SIOP grade [&ge;]2). Younger age at first exposure to carboplatin was the only significant predictor of hearing loss (OR = 0.7888, p=0.0241). Age [&le;]28 months was significantly associated with hearing loss (OR 12.37, p=0.0042). No other risk factors or exposures were statistically significant. Conclusions: Clinically significant carboplatin-associated hearing loss was uncommon (incidence 4.5%). We show that young age is the single-most important risk factor for hearing loss; of nine children who developed hearing loss, eight were aged [&le;]28 months. Children below this age have twelve-fold higher odds of developing hearing loss compared to those above this age (OR 12.37). These findings will allow physicians to provide more appropriate counselling to families regarding ototoxic risk and support intensified hearing surveillance in young children.

The preclinical safety of human-equivalent lactoferrin alpha (heqLF; effera(R)), produced by Komagataella phaffii, was evaluated to support its use as a food ingredient in infant formula and products for young children. Genotoxicity was assessed using a bacterial reverse mutation (Ames) assay in five strains of Salmonella typhimurium and Escherichia coli, and an in vitro micronucleus assay in TK6 cells. Both studies followed OECD guidelines and were conducted up to the recommended limit concentrations (5000 {micro}g/plate and 2000 {micro}g/mL, respectively). A 14-day non-GLP juvenile dose range-finding study and a 13-week GLP juvenile rat toxicity study with a 4-week recovery phase were conducted under ICH S11 guidance. Neonatal Sprague-Dawley rats received heqLF at 0, 1500, 3000, or 5000 mg/kg body weight/day by twice-daily oral gavage from postnatal day 7 to 98. Bovine lactoferrin (bLF) and whey protein at 5000 mg/kg body weight/day served as reference controls. heqLF was non-mutagenic and non-clastogenic in both genotoxicity assays. In the 13-week juvenile rat study, no heqLF-related mortality, clinical signs, developmental, neurobehavioral, or immune toxicity effects were observed. Minor, non-adverse renal findings consistent with high protein intake were observed and largely reversed during recovery. Clinical pathology parameters fully resolved during recovery. Toxicokinetic evaluation showed no systemic accumulation. Based on the absence of toxicologically relevant adverse findings, heqLF is well tolerated at doses up to 5000 mg/kg body weight/day, establishing a no observed adverse effect level (NOAEL) of 5000 mg/kg/day, the highest dose tested, and supporting its safety across intended populations from birth to adulthood.

Background Classical pharmacokinetic-pharmacodynamic (PK/PD) theory models exposure-effect in two dimensions: magnitude and time. Rate-dependent toxicity has been documented across therapeutic domains but never formalised as a conserved biological constraint. Methods We developed the Human Adaptive Rate Limit (HARL) framework, formalising the maximum tolerable velocity as |dS/dt|_max = sigma_max / tau. We validated HARL across five domains using published trial data and a reanalysis of the longitudinal biomarker data from the 202-patient CAR-T cohort of Wei et al (2023). An 8-ODE quantitative systems pharmacology model guided biomarker selection. Early biomarker velocities (maximum positive slope within days 0-5) were computed for ferritin and D-dimer. Patients were classified as high-risk only if both velocities exceeded their thresholds (dual-velocity classifier). Thresholds were identified by grid-search optimisation of the Youden index and assessed by leave-one-out cross-validation. Findings A prospective crossover study (Kleinbloesem 1987, n=8) demonstrated that matched steady-state nifedipine concentrations produce divergent haemodynamic responses depending solely on rate of rise, anticipating the dose-related mortality signal subsequently reported across ~8350 patients with coronary heart disease (Furberg 1995), a meta-analysis that was itself debated. Convergent evidence spans haematology (CHOIR, 1432 patients, hazard ratio [HR] 1.34 [1.03-1.74] for aggressive Hb correction), radiation (dose-rate effectiveness factor [DDREF] 1.5-2.0), and infusion pharmacology. In the CAR-T cohort, high-risk classification (ferritin >232 ng/mL per day AND D-dimer >1.21 mg/L per day) predicted severe CRS with 100% sensitivity (~78% specificity) in safety rule-out mode and 91.1% sensitivity (93.6% specificity, AUC 0.95 [95% CI 0.91-0.98]) in Youden-optimised mode. Median kinetic lead time was 4 days (range 3-7) before clinical decompensation. Interpretation Biological tolerability is three-dimensional. HARL unifies rate-dependent toxicity across domains spanning minutes to weeks. MTDyn--specifying target level and allowable rate of change--should supplement conventional dose-response assessment.

Background: Electrolyte replacement is ubiquitous in the acute care setting, but its familiarity cannot belie that even small dosing errors with potassium can cause lethal cardiac arrhythmias. Recently, MedAgentBench offered a benchmark for agentic artificial intelligence (AI) including the ability to correctly dose potassium based on a single rule; however, this does not adequately reflect the clinical complexity or safety concerns of an agent that has been used as the lethal injection. The purpose of this analysis was to a probe leaderboard large language model (LLM) capabilities to follow basic dosing rules to safely replace potassium in a series of clinician-annotated cases. Methods: Using a clinician panel, we developed a series of dosing principles and 20 clinical cases reflective of the complexity of potassium replacement. External clinicians were surveyed to assess practice variability and agreement to clinician panel answers. We tested GPT-5-chat with each case in triplicate, with and without the clinician curated dosing principles, and prompted the model to answer six questions involving potassium goals, dosing, route, lab frequency, concurrent interventions, and the model's perceived level of confidence for the output and complexity of the case. The primary outcome was the rate of appropriate recommendations in comparison to clinician answers. Results: A total of 54 clinicians reviewed the 20 hypokalemia cases and hypokalemia dosing guideline. Clinicians expressed "highly agree" or "somewhat agree" for 66.8% of the cases evaluated when asked if they agree with the guideline-recommended management. When given the potassium dosing guideline, total errors dropped from 165 to 104, and average accuracy improved from 45% to 65% with GPT-5-Chat. GPT-5-Chat conveyed a high level of confidence for 100% of responses, while labeling 80% and 76% of cases as highly complex with and without the criteria, respectively. Potential harm scores were considerable in both groups, however, a notable reduction in severity scores occurred with the dosing guidance document. Recommendations on concurrent interventions and dosing had the highest rate of errors in both groups. Conclusions: Benchmarks must appropriately reflect clinical complexity to be considered valuable for the deployment of agentic artificial intelligence tools in the healthcare domain. GPT-5-Chat assessment on a comprehensive medication management task for potassium replacement showed improvement with dosing guidance, yet unfit benchmarking performance.

Population pharmacokinetic (popPK) models are commonly developed using ordinary differential equations (ODEs) to describe deterministic concentration-time profiles, with unexplained variability typically attributed to interindividual variability or residual error. When model misspecification is present, system-level deviations may be absorbed into these conventional variability terms, making the source and magnitude of model inadequacy difficult to assess quantitatively. Stochastic differential equations (SDEs) provide an alternative framework by introducing an explicit system-noise component into the structural model, allowing model-data mismatch to be evaluated more directly. However, historical implementation of SDE-based models in NONMEM has been technically challenging. The availability of the Fortran plug-in subroutine SDE.f90 substantially lowers this barrier and enables more practical implementation of SDE-based models in NONMEM. In this work, SDE-based nonlinear mixed-effects models were evaluated as a quantitative diagnostic framework for probing popPK model misspecification. The SDE.f90 implementation was first verified using simulated one-compartment intravenous bolus datasets with stochastic process noise. Additional simulation-estimation scenarios were then conducted under intentionally misspecified structural or stochastic assumptions, including time-varying elimination, compartmental misspecification, and residual error misspecification. Across these scenarios, the estimated system-noise parameter was generally sensitive to misspecification, with larger values usually associated with greater structural or stochastic mismatch. SDE-based modeling also helped partially separate system-level variability from residual variability and, in selected settings, supported localization of misspecification to specific model components, thereby helping guide model refinement. Overall, SDE-based popPK modeling is a useful addition to the pharmacometric diagnostic toolbox, with system-noise estimates best interpreted together with structural model evaluation, residual diagnostics, parameter behavior, and pharmacologic plausibility.

Background: Psychedelics are emerging as potential management options for chronic musculoskeletal pain due to preliminary evidence of effectiveness and low addictive potential, but patients perceptions remain unknown. This study assessed patient perceptions regarding psilocybin for musculoskeletal pain. Methods: We conducted a cross-sectional survey of adults ([&ge;]19) with musculoskeletal pain attending a hospital-based orthopaedic clinic. Participants reported demographics, perceptions of psychedelics for pain management, and willingness to participate in psychedelic research. Multivariable regression explored factors associated with perceived analgesic potential, and willingness to try a full therapeutic dose of psilocybin or a microdose. Results: Among 295 participants, 73% reported moderate-to-severe pain; 75% used analgesics; of these, 41% used opioids (86/209). While 24% reported prior psychedelic use, only 3% had discussed psychedelics with a healthcare provider. Most perceived that psilocybin had moderate-to-high effectiveness for pain (76%). Most respondents endorsed a moderate-to-high willingness to try microdoses (58%) and macrodoses (53%) of psilocybin for pain. Prior non-therapeutic psychedelic use predicted a 1.05-unit increase in perceived analgesic potential on the 10-point scale (p=.013). Willingness to try a macrodose of psilocybin was most strongly associated with prior non-therapeutic (B=3.16) and therapeutic (B=2.42) psychedelic use; in contrast, pain severity had a significant but modest association, with a 0.21-point increase in willingness for every 1-unit increase in pain severity (p=.017). Similarly, willingness to try a microdose of psilocybin was predicted by non-therapeutic (B=2.82) and therapeutic (B=2.48) use, whereas the effects of pain severity (B=0.20) and younger age (B=-0.30) were significant but small. Most respondents (52%) reported moderate-to-high willingness to participate in a trial of psilocybin for pain relief, and health risks were the primary concern (33%). Conclusions: Study findings suggest a majority hold neutral-to-positive perceptions of psilocybin for pain. Addressing perceived barriers, including health effects and gaps in patient knowledge, should be considered when designing future trials.

Background Simon two-stage designs for binary endpoints and their time-to-event analogues, including the Kwak and Jung method, rely on a fixed null benchmark. Their Type I error control is valid only when that benchmark is correctly specified. In practice, historical benchmarks are often inconsistent due to small samples, population heterogeneity, changing eligibility criteria, and evolving standards of care. Even modest misspecifications can substantially inflate the Type I error rate, leading to costly advancement of ineffective treatments. Methods We propose the Interval-Null Robust (INR) two-stage design framework that accounts for uncertainty in the historical null benchmark. We define the null hypothesis as a plausible range of clinically uninteresting values: p[isin][p0L, p0U] for binary endpoints and {lambda}[isin][{lambda}0L, {lambda}0U] (or equivalent survival probabilities) for time-to-event endpoints. Type I error is controlled uniformly over the full null interval: sup{theta}[isin]{theta}0 Pr{theta}(Go) [&le;] . Under the monotonicity of the Go probability, the supremum occurs at the least favorable null configuration - p0U and {lambda}0L - but the design is not reduced to a point-null formulation. The interval defines the uncertainty set for error control and is used in selecting among feasible designs through robust criteria such as worst-case regret or minimal average expected sample size. Results Across representative planning scenarios for both endpoint types, classic designs calibrated to a single benchmark exhibit substantial Type I error inflation when the true null parameter exceeds the assumed planning value. INR designs maintain the nominal Type I error rate across the full null interval, directly addressing this vulnerability to benchmark misspecification. The robustness-efficiency trade-off can be managed through design constraints and robust optimization criteria while preserving uniform Type I error control. Conclusions INR two-stage designs offer a transparent framework for addressing historical control uncertainty in single-arm Phase II trials. By replacing reliance on a fixed benchmark assumption with a more realistic interval of clinically plausible null values, INR design reduces the risk of false-positive Go-decisions caused by benchmark misspecification. INR applies to both binary and time-to-event endpoints and is implemented in the open-source INRDesign R package and accompanying interactive Shiny app.

NAT2 is an important pharmacogene which encodes the N-acetyltransferase 2 enzyme that is involved in the metabolism of multiple medications, and variants in this gene can affect patient response to these medications. CPIC has published a clinical guideline for prescribing hydralazine using NAT2 genotypes. Just prior to the guideline, updated NAT2 star allele numbering and definitions were released, differing somewhat from the historical nomenclature. Clinical pharmacogenomic testing panels often test for the most common star alleles, so knowledge of the most common updated NAT2 star alleles is critical for the implementation of the CPIC NAT2/hydralazine guideline. We first determine NAT2 diplotype frequencies from UK Biobank (UKBB) 200k phased genomes, then analyzed allele, diplotype, and phenotype population frequencies from the All of Us Research program, PennMedicine BioBank (PMBB) and UKBB 500k datasets. We found that analyzing NAT2 diplotypes from phased data provides critical information for algorithms designed to predict diplotypes from unphased data. We observed that NAT2*5, *6, and *4 were the most common star alleles in that order, and the top 11 most frequent NAT2 star alleles were the same across all biobanks. However, differences in star allele frequencies across biogeographical populations were observed. The largest difference led to a higher frequency of NAT2 poor metabolizer phenotypes as compared to rapid and intermediate metabolizer phenotypes in all global populations except in the EAS population, where NAT2 poor metabolizers were in the minority.

Background. Balanced (1:1:1) transfusion of red blood cells (RBCs), plasma, and platelets is the standard of care in trauma-induced massive haemorrhage, where early coagulopathy is a defining feature. In gastrointestinal (GI) haemorrhage this physiology is non-prominent, and whether plasma and platelets provide benefit when [&ge;] 10 RBC units are required within 24 hours is unknown. Objective. To test whether a red-blood-cell-only (RBC-only) transfusion strategy is non-inferior to a balanced (Balanced) strategy for in-hospital mortality in adults meeting massive-transfusion criteria for GI haemorrhage. Design. Single-centre retrospective cohort of 559 adult massive-transfusion encounters (536 patients; 2021-2025) with a primary admitting diagnosis of upper, lower, or unspecified GI haemorrhage. Exposures were RBC-only versus Balanced (RBCs with any plasma and/or platelets). The primary outcome was in-hospital mortality, with a pre-specified 5-percentage-point (pp) non-inferiority margin on the absolute risk difference and a 3-pp sensitivity margin. Analysis used augmented inverse-probability-of-treatment weighting (AIPTW) with bootstrap inference (2,000 resamples by patient). Five pre-specified sensitivity analyses were performed. Results. 505 encounters (90.3%) received RBC-only and 54 (9.7%) received Balanced transfusion. The AIPTW risk difference for in-hospital mortality (RBC-only - Balanced) was -19.8 pp (95% CI -68.1 - -2.2 pp). Non-inferiority was demonstrated at both the primary 5-pp and the more stringent 3-pp margins. Five pre-specified sensitivity analyses, (1) a propensity-score matched cohort, (2) a complete-case model incorporating INR, (3) a broader GI diagnosis set (n = 749), (4) a first encounter per patient restriction, and (5) E-value bound analysis were concordant with the primary estimate. Conclusion. In this propensity-score-weighted cohort of adults with massive GI haemorrhage, an RBC-only transfusion strategy was non-inferior to a balanced strategy for in-hospital mortality at both 5-pp and 3-pp margins. The findings support individualized use of plasma and platelets in GI haemorrhage rather than reflexive application of the 1:1:1 trauma protocol; prospective confirmation is warranted.

Matrixyl (palmitoyl pentapeptide-4, KTTKS core) is a collagen-stimulating peptide used in topical anti-ageing products, but its in-use efficacy is limited by poor permeation through the stratum corneum. We describe a deterministic computational workflow that combines a tournament genetic algorithm and NSGA-II with exact RDKit molecular descriptors to search the fixed-length, edit-distance-2 neighbourhood of KTTKS (3,706 candidate sequences) for analogs with descriptors more favourable for passive transdermal diffusion. The search returns a 9-member Pareto frontier that quantifies the trade-off between predicted permeability and motif preservation. Five of the nine frontier members carry the same substitution, lysine to proline at position 4 (K4P). This single change lowers the topological polar surface area by 25.6%, removes the +1 charge contributed by lysine, and reduces the functional-preservation score from 1.00 (KTTKS) to 0.67. The frontier ranking is unchanged by {+/-}30% perturbations to the TPSA and Mw penalty weights and by a 30% increase in the LogP penalty; only a 30% reduction in the LogP penalty produces rank movement. The frontier matches the ground-truth Pareto set obtained by exhaustive enumeration of all 3,706 candidates (precision and recall both 100%). On the basis of these results we recommend three sequences for experimental validation: PTTPS (largest predicted gain), KTTPS (single-mutation, conservative), and KTTPP (backup). All code, results, and figures are released under MIT and CC BY 4.0.