Clinical and Translational Science

Chronic wounds, such as diabetic and ischemic ulcers, involve impaired perfusion and delayed healing. TOP-N53 is a novel bifunctional molecule combining nitric oxide (NO) release with phosphodiesterase-5 (PDE5) inhibition to enhance local NO-cGMP signalling, resulting in vasodilation and angiogenesis. This first-in-human, randomized, double-blind, vehicle-controlled Phase I trial assessed the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of single subcutaneous TOP-N53 doses in 29 healthy male volunteers. Each participant received injections of TOP-N53 and vehicle in the same forearm, but either at the proximal or at the distal site in an intra-individually blinded manner. Safety assessments included local and systemic parameters. PK and PD responses were evaluated by analysis of TOP-N53 and its bioactivation metabolite TOP-52 in plasma, and by Laser Speckle Contrast Imaging (LSCI), a non-invasive method to measure skin perfusion, respectively. TOP-N53 was safe and well tolerated, with no serious adverse events or local or systemic adverse reactions. Plasma concentrations remained below the quantification limit and LSCI showed sustained dose-dependent increases in local skin perfusion at doses of 4.84 {micro}g and 9.075 {micro}g TOP-N53 SC for up to 24 h post injection when compared to vehicle. These findings support the favourable safety and tolerability profile of TOP-N53 associated with locally improved skin perfusion, encouraging its further clinical development as a topical treatment for chronic wounds with microvascular dysfunction.

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 Plasma gelsolin (pGSN) is a non-immunosuppressive anti-inflammatory immunomodulator with demonstrated efficacy in animal models of acute lung injury. Its potential role in moderate-to-severe acute respiratory distress syndrome (ARDS) is currently under investigation. Methods We conducted a phase 1, randomized, double-blind, placebo-controlled study to evaluate the safety, tolerability, and pharmacokinetics of recombinant human pGSN (rhu-pGSN) following intravenous (IV) administration to healthy volunteers. Thirty-two participants were assigned to 4 sequentially ascending dose cohorts (6, 12, 18, 24 mg/kg of body weight) to receive five IV infusions of rhu-pGSN or saline placebo. Each cohort includes 8 subjects randomized 3:1 with rhu-pGSN or placebo. Doses were administered at 0 hours, 12 hours, 36 hours, 60 hours, and 84 hours. The primary outcome is the incidence and severity of clinical and laboratory AEs regardless of causality. Secondary outcomes include the pharmacokinetics of IV rhu-pGSN and the presence of anti-rhu-pGSN antibodies at Day 28. Results Overall, 10 subjects (41.7%) who received rhu-pGSN reported a total of 13 adverse events (AEs), and 1 subject (12.5%) who received placebo reported an AE. All AEs were mild or moderate. AEs in system organ classes that were reported by 2 or more subjects in either arm were skin and subcutaneous tissue disorders (12.5% rhu-pGSN; 0% placebo), gastrointestinal disorders (8.3% rhu-pGSN; 0% placebo), and nervous system disorders (12.5% rhu-pGSN; 12.5% placebo). No AEs by preferred term were reported by more than 1 subject in either arm. Three subjects (12.5%) experienced an AE assessed as related to study drug. No serious AEs occurred, and no AEs led to study discontinuation, dose interruption/reduction, or death. There were no apparent between-treatment differences in laboratory abnormalities, vital signs, or electrocardiogram findings. Conclusions Overall, in this study, IV rhu-pGSN (up to 24 mg/kg daily) appeared safe and well tolerated compared to placebo. The median half-life of rhu-pGSN exceeded 14 h across all dosing regimens, supporting once daily IV dosing in healthy subjects. Trial registration This study was registered with ClinicalTrials.gov on 2023-03-29 under the registration identifier NCT05789745.

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.

Mocravimod (KRP203) is a selective sphingosine 1-phosphate (S1P) receptor modulator currently in development for patients with haematological malignancies undergoing allogenic haematopoietic cell transplantation (HCT). This first-in-human, randomised, double-blind, placebo-controlled, single ascending oral dose study evaluated the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of mocravimod in 136 healthy adult participants (EudraCT No. 2006-006814-13). Participants received single doses ranging from 0.01 to 40 mg or placebo, with a cohort dedicated to studying food-effect at 3 mg. Mocravimod demonstrated slow absorption (mean Tmax 6-11 hrs), extensive distribution, and a long terminal half-life (91-132 hrs). Exposure increased dose-proportionally for doses [&ge;]2 mg. The most common adverse events were headache, dizziness, and fatigue, all graded as mild or moderate; no serious adverse events or deaths occurred. Mocravimod-phosphate induced robust, dose-dependent reductions in lymphocyte counts, with significant decreases at doses [&ge;]2 mg and recovery to baseline observed in all but the highest dose groups. Cardiac effects included transient bradycardia and benign second-degree atrioventricular (AV) block at higher doses, without clinically significant arrhythmias. Food intake had minimal impact on PK. No clinically meaningful changes in pulmonary function or laboratory safety signals were detected. These results indicate that single oral doses of mocravimod up to 40 mg are safe and well tolerated in healthy adults, with predictable PK and expected PD effects. The findings support further clinical development of mocravimod as a targeted immunomodulator in settings such as allogeneic HCT for haematological malignancies.

In the management of atrial fibrillation, the most frequently prescribed oral anticoagulant is apixaban, given at a fixed dose of 5mg BID. Apixaban is predominantly metabolized by cytochrome P4503A4 (CYP3A4) and is also a substrate for the drug efflux transporter P-glycoprotein (P-gp). In nearly 300,000 Medicare patients with AF receiving apixaban, we previously showed that concomitant therapy with drugs that inhibit both CYP3A4 and P-gp, specifically amiodarone or diltiazem, significantly increased serious bleeding that caused hospitalization and/or death. We hypothesized that this adverse effect was mediated by an increase in apixaban plasma concentrations caused by concomitant therapy that reduced drug elimination. Utilizing left-over samples obtained from clinically indicated blood draws that would typically be discarded, the Vanderbilt University Medical Center biobank BioVU contains >353,000 samples linked to de-identified electronic medical records (EMRs), with both DNA and plasma harvested. Of 35 samples drawn from patients taking apixaban 5mg BID, 5 were identified to be drawn from patients concomitantly taking drugs inhibiting both CYP3A4 and P-gp. Using a chromogenic anti-Xa assay, we found that plasma concentrations of apixaban were significantly higher (347{+/-}64 ng/mL; mean{+/-}SEM) for patients receiving concomitant CYP3A4/P-gp-inhibiting drugs compared to those not treated with these drugs (166{+/-}67 ng/mL; P=0.025, Mann Whitney). There were no differences between the 2 patient groups with respect to age, weight, or serum creatinine. The results of this pilot study provide preliminary data to support our hypothesis, and they demonstrate the practicality of obtaining pharmacokinetic data from a large cohort of plasma samples linked to deidentified EMRs. This approach could be used to define the role of apixaban levels in high-risk clinical scenarios and to better understand the relationship between drug levels and bleeding risk.

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.

The development of lung-directed therapeutics is limited by poor translational fidelity between preclinical models and early-phase clinical trials. We report a first-in-human Phase 0 intratarget microdosing study demonstrating the feasibility of intrapulmonary delivery and pharmacological interrogation of a novel inflammasome inhibitor. A 100 g microdose of ADS032, a dual NLRP1/NLRP3 inhibitor, was administered to distal airways via bronchoscopy in patients with interstitial lung disease, informed by optimisation in ex vivo human lung perfusion and ventilation systems. Clinical-grade manufacture, formulation, stability, and toxicology enabled intrapulmonary administration. Using liquid chromatography-mass spectrometry, ADS032 was detected in plasma, bronchoalveolar lavage fluid, distal airway micro-aspirates, and recovered cells, with spatially resolved sampling achieved without cross-contamination. Fluorescent labelling enabled direct visualisation of alveolar drug uptake ex vivo. These findings establish intrapulmonary intratarget microdosing as a human-relevant platform for early pharmacological evaluation of lung therapeutics prior to Phase 1 trials.

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.

Nicotinamide riboside (NR), an endogenous precursor to the essential coenzyme nicotinamide adenine dinucleotide (NAD+), is characterized as safe and effective at longitudinally elevating NAD+ in blood and tissues, when administered orally. Preclinical research on NR as an augmenter of NAD+ has demonstrated great promise in support of healthy aging, metabolic health, and several diseases, though clinical translation of thesefindings has been limited. Interest in alternative routes of administration of NR has increased in recent years and led to the development of pharmaceutical-grade NR for intravenous and injectable administration. Two separate Phase 1 pilot clinical trials were conducted evaluating NR via bolus injections. While the designs of the two studies are different, the similarities warrant combined presentation to note the similarities, particularly with regards to safety-related outcomes. Trial 1 involved 45 participants that were randomized to a 3x3 design, accounting for three interventions, placebo, NR, and NAD+ and three routes of administration, intramuscular (IM), intravenous (IV), and subcutaneous (SC), resulting in a 9-arm study (placebo IM, n=5; placebo IV, n=5; placebo SC, n=5; NR IM, n=6; NR IV, n=5; NR SC, n=4; NAD+ IM, n=4; NAD+ IV, n=5; and NAD+ SC, n=6). Participants were administered NR once daily for three days, followed by a 7-day washout period. In Trial 2 (n=39), the 2x2 study design incorporated 4-arms for phase 1, where the participants were randomized to 50 or 100 mg of NR, administered either IM or SC in-clinic for 3 consecutive days, followed by a 7-day washout (50 mg IM, n=7; IM, 100 mg IM, n=11; 50 mg SC, n=11; and 100 mg SC, n=10). Phase 2 of Trial 2 involved participants self-administering either 50 or 100 mg of NR subcutaneously. Safety assessments for both trials included vitals, blood biomarkers, participant reported outcomes regarding the experience, and adverse event monitoring. Participant retention for both studies was 100%, and the injections did not result in any attributable unexpected adverse events or experiences. The experiences described by the participants regarding the actual injection varied. In Trial 2, pain more than two minutes after the injection and muscle soreness and tightness were reported by 45.9 and 43.2% of the participants, respectively, regardless of the route of administration or dose. Vitals remained generally consistent throughout both trials, and reductions in systolic blood pressure observed in both trials should be evaluated in larger, properly powered studies. Blood chemistry biomarkers for both trials did not elicit treatment-related patterns. Both trials presented within-group reductions in hsCRP in the NR SC arms, however, given baseline imbalance and small samples size, this finding should be considered hypothesis-generating, only. Overall, in both trials, the interventions, regardless of route of administration were associated with some discomfort but were well tolerated and did not produce any concerning safety signals. It is recommended that comprehensive metabolic and inflammatory panels should continue to be employed in future studies and clinical settings to assess whether consistent patterns emerge in larger populations.

Background: Cysteamine is the only disease-modifying therapy for nephropathic cystinosis and has shown promise in mitochondrial disorders, but its clinical utility is limited by poor tolerability due to high peak concentrations with existing formulations. TTI-0102 is a novel natural controlled-release cysteamine prodrug designed to provide sustained cysteamine exposure with improved tolerability. Methods: A multi-center, randomized, single-blind, placebo-controlled Phase 2 trial enrolled 9 patients with MELAS syndrome caused by mtDNA m.3243A>G mutation (>50% heteroplasmy) and moderate disease severity (NMDAS score 15-45). Patients received placebo (n=3) or TTI-0102 at 2.75 g/day for one week then 5.5 g/day (n=6, equivalent to 2.5 g/day cysteamine base). Pharmacokinetic parameters, safety, and pharmacodynamic biomarkers including pyruvate, taurine, pantothenic acid, tryptophan, GSH/GSSG, lactate, GDF-15, and FGF-21 were assessed. Clinical efficacy was evaluated using the Modified Fatigue Impact Scale (MFIS) and 12-minute walk test. Results: TTI-0102 demonstrated expected gastrointestinal side effects (nausea, vomiting, diarrhea) consistent with the cysteamine class, with dropout occurring in patients 50 kg receiving fixed 5.5 g/day dosing. Weight-based dosing at 60 {+/-} 5 mg/kg TTI-0102 (~26 mg/kg cysteamine base equivalent) achieved sustained 24-hour cysteamine exposure with half the daily dose and peak concentrations lower than expected by dose proportionality, compared to approved formulations (Procysbi: 56 mg/kg, peak 2.5 mg/L vs. TTI-0102: 26 mg/kg, peak ~2 mg/L). TTI-0102 significantly elevated pantothenic acid (plateauing at 2 weeks) and taurine levels, providing mitochondrial cofactor support and antioxidant effects. Statistically significant pharmacodynamic effects included increased plasma pyruvate (p=0.03) without lactate elevation, suggesting enhanced glycolytic flux, and decreased tryptophan (p<0.01), potentially reducing oxidative stress from neurotoxic kynurenine pathway metabolites. Interestingly, increase in plasma pyruvate and decrease in tryptophan were negligible at doses up to 40 mg/kg/day, optimal at 60 mg/kg/day, and slightly less at 65 mg/kg/day. GSH/GSSG measurements were confounded by sample stability issues. GDF-15, FGF-21, and 12-minute walk distance showed no treatment-related changes. Most notably, MFIS total scores demonstrated significant improvement in TTI-0102-treated patients at 60 mg/kg/day average dose compared to placebo (p=0.04). Polynomial regression revealed therapeutic onset at ~4 weeks, maximal benefit at ~12 weeks, and subsequent plateau. Conclusions: This Phase 2 trial provides proof-of-concept that TTI-0102 is safe and well-tolerated in MELAS patients while treated with less than 65 mg/kg/day, with efficacy signals in fatigue reduction, a cardinal symptom affecting 71-100% of mitochondrial disease patients. The drug tri-faceted mechanism through sustained cysteamine, taurine, and pantothenic acid delivery addresses oxidative stress, mitochondrial energy metabolism, and cofactor deficiency. Significant MFIS improvement coupled with favorable modulation of pyruvate and tryptophan supports advancing TTI-0102 to larger Phase 2b/3 trials in mitochondrial disease employing weight-based dosing (60 {+/-} 5 mg/kg), validated patient-reported outcomes, and minimum 12-week treatment duration. The same mechanism of cysteamine/cystine thiol-disulfide exchange in lysosomes that may benefit mitochondrial diseases also supports cystinosis treatment. An investigator-initiated study in cystinosis will evaluate whether once-daily TTI-0102 at 60 {+/-} 5 mg/kg can maintain therapeutic WBC cystine levels, potentially offering improved adherence and quality of life compared to current twice-daily or four-times-daily regimens, and this weight-adjusted dosing strategy and pharmacodynamic biomarkers identified in the MELAS study are going to be used to inform the design of the planned Phase 2 study in Leigh syndrome, another mitochondrial disorder, in collaboration with the Childrens Hospital of Philadelphia (CHOP), with particular attention to dose optimization and biomarker-based assessment of pharmacological activity. Acknowledgement: We are very thankful to the patients and the clinical teams of Radboud University Nijmegen Medical Centre (Netherlands) and Centre Hospitalier Universitaire d'Angers (France) for their participation in this operationally challenging study.

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.

ObjectiveConventional pharmacodynamic (PD) modeling workflows require manual model selection, repeated equation rewriting, and empirical parameter adjustment, resulting in limited automation, high cross-scenario migration costs, and insufficient reproducibility. This study aims to develop PD Union, a unified, automated, and interpretable framework for mechanistic PD modeling. MethodsPD Union is built upon a unified continuous dynamical skeleton that organizes absorption and systemic exposure module, the receptor module, the drug input module, the first delay module, the primary pharmacodynamic function module, the primary pharmacodynamic state module, the downstream pharmacodynamic state module, the second delay module, the feedback module, the circadian modulation module, the biophase module, the direct effect module, the disease state module, the second PD axis first delay module, the second PD axis primary pharmacodynamic function module, the second PD axis primary pharmacodynamic state module, the second PD axis downstream pharmacodynamic state module, the second PD axis second delay module, and the second PD axis feedback module. A machine learning-based structure identification module is incorporated to recognize drug input modes and mechanism labels from population PK/PD time series, followed by constrained population parameter optimization, forming an integrated pipeline of structure identification, candidate generation, and parameter fitting. ResultsValidation was conducted at two levels. In standardized synthetic benchmarking across 14 representative single-endpoint scenarios, the structure identification model achieved an output mode accuracy(NRMSE) of 0.7600 and macro-average F1 of 0.6307; parameter fitting yielded an NRMSE mean of 0.146 and median of 0.117. In the unified reconstruction validation based on 15 population pharmacokinetics/pharmacodynamics (PK/PD) literature data, the mean NRMSE of PDUnion model for PD was 0.261, and the median was 0.228. Among the 15 studies, 14 performed better than the models provided in the original literature. ConclusionsPD Union demonstrates that interpretable mechanistic modularization combined with machine learning-assisted structure identification is feasible for automated PD modeling. The framework provides an executable methodological foundation for unified, reproducible, and extensible mechanistic PD modeling, with potential applicability to multi-endpoint and complex disease-state modeling scenarios.

BackgroundPost-market pharmacovigilance relies predominantly on single-database disproportionality analysis of spontaneous adverse event reports, which lacks corroboration across independent evidence streams and cannot integrate randomised trial evidence. No publicly accessible platform has previously combined European national pharmacovigilance registries, the US FDA Adverse Event Reporting System (FAERS), and clinical trial meta-analyses into a unified, continuously scored signal detection framework. MethodsWe describe the Signal Consensus Index (SCI), a composite 0-100 pharmacovigilance signal score integrating disproportionality evidence from the Danish National Pharmacovigilance Database, the UK MHRA Yellow Card scheme, and FAERS, with DerSimonian-Laird meta-analytic risk ratios from ClinicalTrials.gov, across 6,905,874 drug-adverse event pairs. Each source contributes a continuous score derived from the lower bounds of three complementary disproportionality metrics (ROR, PRR, IC025) for spontaneous reporting sources, and from the pooled risk ratio lower confidence bound for clinical trials. The SCI is publicly accessible via the Adverse Event Atlas (aeatlas.com). We report reference set validation against the EU-ADR reference standard, a single-source comparison with discordance characterisation, temporal stability analysis across eight cumulative data windows (2015-2023), and a weight sensitivity analysis across seven pre-specified weighting schemes. ResultsThe SCI generated 129,176 Moderate-or-Strong signals (SCI [&ge;] 50, confidence [&ge;] 50) and 7,290 Strong signals (SCI [&ge;] 70, confidence [&ge;] 70). Reference set validation against 88 classifiable drug-event pairs (44 positive controls, 44 negative controls) yielded 18 true positives, 0 false positives, 44 true negatives, and 26 false negatives (sensitivity 40.9%, specificity 100.0%, PPV 100.0%, NPV 62.9%). Zero false positives were observed across all 44 classifiable negative controls, with five false negatives attributable to the confidence gate correctly suppressing single-source signals pending multi-source corroboration. Single-source comparison demonstrated that FAERS alone generated 1,438,246 disproportionality signals, of which 94.8% were not confirmed by the SCI, while 54,184 SCI-detected signals were absent from FAERS, of which 8.3% involved drugs absent from the US reporting system. Discordance analysis showed that 99.8% of Danish non-confirmation reflected data availability constraints. Temporal stability was high: 98.5% of pairs received identical classifications across all seven weight scenarios, and 57.0% of final Strong signals were already detectable as Moderate or Strong in the earliest data window (2015-2016). Strong classifications were stable across weight scenarios (94.0% of Strong observations remaining Strong). ConclusionsThe SCI provides a transparent, openly accessible framework for cross-source pharmacovigilance signal prioritisation with 100% specificity and PPV against an established reference standard and stable classifications across weighting schemes. Progressive signal emergence through the Moderate tier supports its use as an early detection layer. The platform is available at aeatlas.com.

BackgroundLarge language models (LLMs) are increasingly used by clinicians to generate executable code for pharmacokinetic (PK) simulation. Whether such code meets the accuracy standards of target-controlled infusion systems has not been systematically evaluated. MethodsFive LLMs (ChatGPT, Claude, DeepSeek, Gemini, Grok) were prompted to generate Python code for the Marsh three-compartment propofol model under a standardized 120-minute bolus-plus-infusion regimen. Each LLM was tested in two phases: Phase 1, integrator free; Phase 2, fourth-order Runge-Kutta with 1-second step size mandated. Twenty runs per LLM per phase were collected (n = 200). Plasma concentrations were compared against a triple-validated reference using median prediction error (MDPE), median absolute prediction error (MDAPE), and Wobble. Runs were classified as Class A (MDAPE < 1 %), B (1-30 %), C ([&ge;] 30 %), or D (failed). ResultsAll 200 scripts were invokable and created a CSV file; 199/200 (99.5 %, 95 % CI 97.1-99.9 %) produced a valid time-concentration series. The remaining script (Gemini Phase 2 run 18) aborted during row formatting with ValueError and left a header-only CSV. Median MDAPE per LLM x phase ranged 0.0043-0.020 %, with 195/200 runs (97.5 %, 95 % CI 94.3-98.9 %) achieving Class A. Five runs (2.5 %, 95 % CI 1.1-5.7 %) were non-excellent or structurally defective: three were Class C due to time-scale/unit-handling errors (one DeepSeek run with a 6-second effective Euler step from a minute-as-second declaration, two Grok runs with min-{superscript 1} rate constants applied per second), one was Class D (the empty-CSV failure above), and one was Class B but reflected a duplicated-bolus implementation error rather than a benign numerical deviation. Kruskal-Wallis testing showed significant inter-LLM heterogeneity across all metrics and phases (all omnibus p < 0.01). Strict compliance with Phase 2 directives was 98 % (98/100 runs; 95 % CI 93.1-99.5 %); lenient compliance accepting RK4-adaptive implementations as a superset was 100 % (100/100 runs; 95 % CI 96.3-100 %). Yet all three numerically divergent Phase 2 runs occurred under nominally compliant RK4/dt = 1 s configurations; the fourth non-Class-A Phase 2 outcome was a formatting failure that produced no usable trajectory. ConclusionLLMs generate numerically accurate Marsh-model code in most runs but silently diverge in a clinically non-negligible minority. The Marsh model -- the simplest fixed-parameter three-compartment propofol model -- functioned here as a positive control: even so, three distinct classes of structural bug (unit/time-scale mismatch, duplicated-bolus event handling, malformed f-string formatting) slipped past apparent execution success. Two additional Phase 2 runs used an RK4-adaptive variant rather than classical RK4 and are therefore better interpreted as strict prompt non-compliance than as numerical failure. Prompt-level method specification substantially reduced algorithm-selection errors but did not eliminate unit or structural bugs. LLM-generated pharmacokinetic code requires reference-based validation before any safety-relevant use.

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

BackgroundRoutinely collected prescribing and medicine-related data in Scotland are comprehensive and of high quality. However, they are generated across multiple healthcare settings and stored in complex source systems that are not optimised for longitudinal or outcomes-focused research. To maximise the research value of these data, there is a need for curated, analysis-ready resources that provide consistent representations of medicines exposure and enable linkage to clinical outcomes. The Medicines in Acute and Chronic care Scotland (MACCS) provides standardised, curated medicines data to support longitudinal analyses of medicine-related exposure across NHS healthcare systems. MethodsMACCS resource is a national individual-level medicines dataset for adults (18 years of age and older), derived from routinely collected prescribing and medicine-related data held by Public Health Scotland (PHS). It integrates data from the Hospital Electronic Prescribing and Medicines Administration (HEPMA), Prescribing Information System (PIS), and Homecare Medicines (HCM) datasets, which are linked at the individual level to eleven other national clinical records; including Scottish Morbidity Records (SMR00/01/02/04/06), laboratory data and mortality records; using the unique NHS Scotland person identifier. Data are curated, harmonised and pre-linked within the National Safe Haven and accessed by approved researchers through secure Trusted Research Environments. ResultsMACCS contains individual-level information on adults receiving NHS Scotland care, including patient demographics (such as age, sex and geographical indicators) and detailed records of medicines prescribing in community pharmacies as well as those administered in hospitals and through homecare services. Medicines-related data captures exposure dates and, where available, details on formulation, strength and dose. In addition, MACCS includes cancer registry data, renal registry data, laboratory test results, microbiology surveillance and mortality records. The earliest dates of data availability vary by source dataset. ConclusionMACCS provides a sustainable, longitudinal medicines research resource that simplifies access to complex national prescribing data and enables robust linkage to health outcomes. By supporting population-scale analyses across care settings, MACCS enhances the capacity for high-quality research to inform clinical practice, health policy, and medicines optimisation in Scotland. Key FeaturesO_LIThe Medicines in Acute and Chronic Care in Scotland (MACCS) data resource was established in 2025 to integrate medicine-related data with other electronic data from Scottish healthcare systems, creating a national, linked, routinely updated data resource at population level. C_LIO_LIMACCS provides pre-linked data from multiple routinely collected national datasets within NHS Scotland including, but not limited to, prescribing records, hospital episodes, laboratory results, and death records, within a single secure environment. C_LIO_LIMACCS includes patient demographics, data on medicines prescribing and administration/supply, key biochemistry and haematology test results (e.g., kidney and liver function tests), data on hospital admissions and surgical procedures, and date and cause of death. C_LIO_LIThe data resource provides longitudinal follow-up of the adult population ([&ge;]18 years of age) receiving medicines through NHS Scotland since 2010, covering approximately 4.6 million individuals, and supports pharmacoepidemiological studies, drug utilisation research, pharmacovigilance projects, as well as health services research. C_LIO_LIApproved researchers can apply through a streamlined process to access the linked MACCS data resource through established NHS Scotland governance processes, with data accessed within a Trusted Research Environment. 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.