British Journal of Clinical Pharmacology

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.

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.

BACKGROUNDSotalol loading intravenously enables achieving blood levels of sotalol that are observed at maximal steady-state concentration (Cmax ss) in one-day permitting the measurement of maximum QTc effects. Rapid evaluation of the QTc effects permits determination of arrhythmic risk and thus permits discharge in 24-hours instead of the usual three-day oral load hospitalization. Given the expense of IV Sotalol an oral loading test strategy is presented that also achieves Cmax ss blood levels rapidly, permitting a one-day hospitalization for QTc evaluation. METHODPharmacokinetic parameters referred to in the literature derived from normals as well as patients was utilized for population pharmacokinetic modeling and simulation.to obtain the Cmax ss concentrations for patients with normal renal function, creatinine clearance (CrCl) > 90 ml/min), as well as for patients with a CrCl of 60-89, 30-59, and 10-29 ml/min). Using pharmacokinetic simulations, an oral loading dose, as well as a second oral dose were determined that would reach the estimated Cmax ss in each of the groups based on renal function. RESULTSFor target dosing of 120 mg oral sotalol BID in patients with a CrCl >90 ml/min an oral loading dose of 200 mg provides a peak sotalol level of 1,420 ng/ml in 3-4 hours post dosing. The Cmax ss target is 1,299 ng/ml resulting in a 9% overshoot. The Cmax ss concentration provides a means of evaluating QTc effects within 24-hours. Oral loading regimens are described for varying additional renal function levels (CrCl 60-90, 30-59 and 10-29 ml/min) along with the time to first oral dose and follow-up dosing. The initial test dose can be based on an 80 or 120 mg oral sotalol maintenance dosing strategy. CONCLUSIONSEmploying an oral loading strategy may permit QTc evaluation and one-day discharge, preserving the pharmacoeconomic advantage of a Cmax ss test strategy. Clinical PerspectiveO_ST_ABSWhat is Known?C_ST_ABSO_LIIntravenously loading of sotalol enables achieving blood levels that are observed at maximal steady-state concentration (Cmax ss) in one-day permitting the measurement of maximum QTc effects. C_LIO_LIRapid evaluation of the QTc effects permits determination of arrhythmic risk and thus permits discharge in 24-hours instead of the usual three-day oral load hospitalization C_LI What the Study AddsO_LIWith oral sotalol loading, the Cmax ss can also be achieved in one-day permitting the measurement of maximum QTc effects and discharge from the hospital in 24-hours instead of the usual three-day inpatient initiation of oral sotalol. C_LI

Topiramate (TPM) is approved for seizures and migraine prophylaxis and is used off-label for several neuropsychiatric conditions. The available dosage forms, including tablets and sprinkle capsules, are unsuitable for patients who may be unable to take medicine orally. The resulting potential treatment interruptions could have untoward consequences and underscores the importance of developing a parenteral formulation. In this study, we developed a population pharmacokinetic model of a novel, intravenous TPM formulation using data from a study in patients with epilepsy or migraine receiving a single intravenous dose of stable-labeled TPM. In total, 246 TPM concentrations from 20 adult patients were included for model development. A three-compartment pharmacokinetic model with linear elimination fit the concentration-time data best. Simulations for various loading and maintenance regimens for patients with and without enzyme-inducing comedications were performed. The final estimates(95% confidence interval (CI)) for CL (L/h), V1 (L), and the peripheral volumes, V2 and V3 for a 70 kg person were 1.31(1.01 - 1.53), 9.84 (8.49 - 11.0), 39.1 (36.5 - 41.8)L, and 9.01 (6.41 - 44.3) respectively. The use of enzyme-inducing co-medication was the only significant covariate, associated with a 63% increase in clearance .Goodness-of-fit plots and visual predictive checks indicate satisfactory model performance and prediction. The simulation results indicate that adjusting doses for patients receiving IV TPM can mitigate the changes in plasma TPM concentrations resulting from enzyme induction. This population pharmacokinetic model for intravenous topiramate can inform dosing decisions for patients with epilepsy when used as either initiation or bridging therapy.

BackgroundAntibiotic pricing is a key determinant of access and stewardship in low- and middle-income countries (LMICs), yet empirical evidence on how prices are formed within pharmaceutical markets remains limited. However, there is little longitudinal evidence on how antibiotic prices behave within national pharmaceutical supply systems. This study evaluated the patterns and determinants of systemic antibiotic pricing in Tanzania using national regulatory import permit data. MethodsWe conducted a retrospective analysis of antibiotic importation records from the Tanzania Medicines and Medical Devices Authority for 2010-2016. Systemic antibiotics for human use imported via oral or parenteral routes were included. Unit prices (USD per smallest unit of measure) were summarized using the median and interquartile range (IQR). Prices were compared by route of administration, supplier country, and product naming practice (INN-named versus brand-named) using Mann-Whitney U and Kruskal-Wallis tests with false discovery rate adjustment. ResultsOf the 14,301 records, 10,894 (76.2%) met the inclusion criteria. Oral antibiotics predominated (89.6%). Although the median oral antibiotic prices declined over time, substantial price dispersion persisted across all study years. Parenteral antibiotics were consistently more expensive (USD 0.755-3.370) and more variable than oral antibiotics. Importation was concentrated in a few medicines, with amoxicillin-clavulanate (16.7%) and amoxicillin (11.4%) accounting for over one-quarter of records, and in a few supplier countries, with India representing 44.9% of the records. Significant price differences between INN-named and branded products were observed for amoxicillin (adjusted p<0.001) and ciprofloxacin (adjusted p=0.018), whereas prices differed significantly by supplier country across major medicines (adjusted p<0.05). Across medicines and years, wide within-product price distributions indicate persistent market segmentation rather than price convergence. ConclusionsAntibiotic import prices in Tanzania exhibit systematic and reproducible variations associated with formulation type, supplier origin, and product naming practices. The findings indicate that procurement structure and supplier participation strongly influence pricing in the import-dependent pharmaceutical market. Monitoring import-level prices can serve as an upstream indicator of market conditions and support evidence-informed procurement, pricing regulations, and antimicrobial stewardship policies in LMIC settings.

BackgroundCompounded versions of tirzepatide are widely available in the U.S. in the form of fixed-dose combinations of tirzepatide and various analogs of vitamin B12. These combinations are mass marketed in the U.S. and other countries as comparable to FDA-approved tirzepatide products even though they undergo no evaluation of their potency or impurity profiles. Research Design and MethodsSamples of compounded tirzepatide combined with B12 obtained from various sources in the U.S. market were tested using various analytical methods. Samples were assessed for unacceptable levels of peptide-related impurities. ResultsOur testing identified a widespread and previously unidentified impurity in compounded tirzepatide-B12 products resulting from a chemical reaction between tirzepatide and certain analogs of B12. ConclusionDespite the presence of this impurity, these products continue to be mass marketed as "personalized" treatments. Our findings underscore the importance of testing and FDA approval before new drugs are marketed and highlights potential risks for patients associated with untested combinations. A novel impurity, present at substantial levels in compounded tirzepatide/B12 products, highlights risks inherent in marketing complex therapies outside the drug-approval framework. Although clinical effects of this impurity are unknown, the identification of a widespread impurity adds to the existing quality concerns presented by compounded tirzepatide.

BackgroundElevated low-density lipoprotein cholesterol (LDL-C) is a risk factor for cardiovascular disease. Despite available lipid-lowering therapies (LLT), lipid control remains suboptimal. Bempedoic acid offers a non-statin oral treatment for hypercholesterolemia. However, real-world data in Asia are limited. The study aimed to investigate the effectiveness and safety of bempedoic acid in Taiwan. MethodsThis pragmatic phase IV study enrolled 180 patients with inadequately controlled hypercholesterolemia to receive bempedoic acid for 12 weeks in addition to background LLT. The primary endpoint was the percentage change in LDL-C. Secondary endpoints included changes in other lipid parameters, high-sensitivity C-reactive protein (hsCRP), and safety outcomes. ResultsAmong 180 patients, 160 (88.9%) completed the study. The median percentage change in LDL-C from baseline to week 12 was -19% (interquartile range [IQR]: -36.4% to -3.6%), decreasing from 117.5 to 92 mg/dL (p < 0.01). The median percentage changes from baseline to week 12 were -13.3% for non-high-density lipoprotein cholesterol (non-HDL-C), -10.8% for total cholesterol, -11.5% for apolipoprotein B, and -34.0% for hsCRP (all p < 0.01). Minimal effects were noted on triglycerides (+0.2%), HDL-C (-5.5%), and lipoprotein(a) (+2.6%) (all p > 0.05). At week 12, 31.3% of patients achieved LDL-C targets (< 100 mg/dL for primary prevention; < 55 or < 70 mg/dL for secondary prevention). The safety outcomes were consistent with the locally approved label, with no new safety signals identified. ConclusionsBempedoic acid offers an effective and safe oral therapeutic option for Taiwanese patients whose LDL-C levels remain inadequately controlled with existing LLT, including statins. RegistrationURL: https://clinicaltrials.gov/study/NCT06925100; Unique identifier: NCT06925100 Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABS{diamondsuit} This pragmatic phase IV study provides the first real-world evidence from Taiwan demonstrating that bempedoic acid leads to clinically meaningful reductions in LDL-C (median percentage change: -19%) at week 12 when added to background lipid-lowering therapy in patients with inadequately controlled hypercholesterolemia. {diamondsuit}Approximately one-third of patients achieved guideline-recommended LDL-C targets within 12 weeks, with a safety profile consistent with the locally approved label and no new safety signals identified. What Are the Clinical Implications?{diamondsuit} Bempedoic acid represents an effective and well-tolerated oral add-on lipid-lowering option for Taiwanese patients who fail to achieve LDL-C goals with existing therapies, including those unable to tolerate or intensify statin treatment.

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.

Objective To describe trends in dispensing of monoclonal antibodies (mAbs) for autoimmune conditions during and around pregnancy. Design Descriptive study. Setting Lombardy, Italy between 2012 and 2024. Population All women of reproductive age (14-49 years) resident in Lombardy. Methods We described trends in mAb dispensations among women of reproductive age and the prevalence of mAb dispensing before, during and after pregnancy. We explored maternal factors associated with discontinuation. Main outcome measures Change in prescribing of mAbs over time in all women of reproductive age, and before, during and after pregnancy in those who became pregnant. Prevalence of discontinuation and switching mAbs around pregnancy. Results We included 3,049,175 women of reproductive age and 859,699 pregnancies. Prevalence of mAb dispensing during pregnancy increased over 60-fold over the study period, from 0.0041% (95%CI:0.00084, 0.012) in 2012 to 0.27% (95%CI:0.23, 0.32) in 2024. Pregnancy affected mAb dispensing, with mean prevalence decreasing from 0.080% (95%CI:0.074, 0.087) before pregnancy to 0.051% (95%CI:0.046, 0.057) by the third trimester. Over half (53.3%) of pre-existing users discontinued before or during pregnancy; discontinuation decreased over time, and varied substantially between mAbs. Switching mAbs during pregnancy was rare (3.3%). We found limited evidence that sociodemographic factors were associated with discontinuation, but that some health factors may be, such as use of assisted reproductive technology (OR=1.92, 95%CI:0.98-3.77). Conclusions Italian population-wide data from 2012-2024 show an increase in mAbs dispensed during pregnancy, and fewer instances of discontinuing these drugs over time. This may reflect recent changes in prescribing guidelines for mAbs in pregnancy.

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

BackgroundAnti-tumor necrosis factor (anti-TNF), particularly infliximab, have transformed inflammatory bowel disease (IBD) management, but their high cost imposes a significant economic burden. Infliximab biosimilars were introduced to reduce the unmet needs. Despite the approval of infliximab biosimilars, real-world evidence of cardiovascular safety and effectiveness of infliximab biosimilars is lacking among patients with IBD. In this trial emulation, we compared the effectiveness and cardiovascular safety between patients who initiated infliximab reference product (IFX-RP) and biosimilars (IFX-BP). MethodsUsing the Merative Marketscan Research database (2011-2023), we conducted a retrospective cohort study to emulate the target trial where biologic-naive adults were randomly assigned to initiate IFX-RP or IFX-BP. Primary outcomes included healthcare resource utilization (HRU), and incidence of major adverse cardiovascular events (MACE) over one year. Propensity score matching was applied to mimic the randomization. Both intention-to-treat and per-protocol effects were estimated. ResultsAfter matching, 850 patients (425 per group) were included. HRU was comparable between IFX-RP and IFX-BP groups across outpatient visits, hospitalizations, surgeries, and emergency visit. During follow-up, MACE events were more frequent in the IFX-BP group (9 vs. 3), with an incidence rate ratio (IRR) of 3.04 (95% CI: 0.82-11.23). Although the difference was not statistically significant, consistent directional trends were observed across analyses. Sensitivity analyses supported primary results. ConclusionOur study found comparable effectiveness between IFX-RP and IFX-BP in routine clinical care. While cardiovascular events were infrequent, the potential signal suggesting increased MACE risk associated with infliximab biosimilars warrants further investigation. Continued pharmacovigilance is essential to ensure the cardiovascular safety of biosimilars. SummaryInfliximab biosimilars, introduced to reduce the economic burden of anti-TNF therapy in IBD, demonstrated comparable real-world effectiveness to the infliximab reference product in a target trial emulation using Merative MarketScan data, while a potential signal of increased cardiovascular risk underscores the need for ongoing pharmacovigilance and further investigation. Key MessagesO_LIWhat is known? Infliximab biosimilars demonstrate comparable efficacy and safety to the reference product in IBD, but cardiovascular outcomes remain underexplored. C_LIO_LIWhat is new here? This U.S. real-world study emulating a target trial found similar effectiveness between infliximab reference and biosimilar products, with a possible trend toward increased cardiovascular risk in biosimilar users. C_LIO_LIHow can this study help patient care? Findings highlight the need for continued pharmacovigilance and cardiovascular monitoring when prescribing infliximab biosimilars to optimize safety in IBD management. C_LI

Amatoxin-induced acute liver failure complicates misidentified foraged mushroom ingestion worldwide; abrupt multisystem collapse punctuates apparent improvement. Our prospective single-arm clinical trial investigated proactive toxicokinetic-based management to preserve elimination capacity: sustained enhanced hydration to maintain renal clearance; fasting plus octreotide to suppress meal-driven enterohepatic circulation; and intravenous silibinin to inhibit OATP1B3-mediated hepatic uptake, enabling safe passage and elimination of gallbladder-confined amatoxin-laden bile. Safety population (N=99) transplant-free recovery (TFR): 88.0% (87 recoveries, 6 transplants, 6 deaths). Protocol-adherent Efficacy population (n=86) TFR: 98.8% (85 recoveries, 1 transplant, 0 deaths). Multivariable analysis identified uninterrupted hydration as strongest TFR predictor (P<0.001), followed by earlier silibinin initiation (P=0.003); octreotide shortened INR recovery by 11 hours (P=0.033). These findings support a toxin elimination model in which preserved renal clearance and biliary sequestration are central recovery determinants. The kinetic balance between renal clearance and hepatic uptake governs both recovery and collapse.

Medication adherence is critical for effective management of chronic diseases and reducing healthcare burdens. Statins, commonly prescribed for cardiovascular disease prevention, require sustained, lifelong adherence, yet maintaining long-term adherence remains a significant challenge. Here, we analysed longitudinal electronic health records from over one million statin users in Finland and Italy to characterise adherence trajectories and their determinants. Using functional data analysis, we identified five distinct adherence patterns, with consistently high adherence being the most prevalent across both populations. Younger age, socioeconomic vulnerability, and statin use for primary prevention were consistently associated with a higher risk of declining adherence over time. Sex differences were observed in Italy but not in Finland, where divorced status and health-related educational background were also associated with declining adherence. Despite differences in healthcare systems, several determinants of adherence were consistent across countries. These findings highlight shared behavioural factors underlying long-term statin use and suggest that population-level interventions tailored to patient subgroups defined by adherence patterns may help support sustained medication adherence.

PurposeThe objective of this study was to identify predictors of statin adherence in the primary and secondary prevention of CVD among patients in the first two years after the date of first prescription using real-world data. MethodsThe Electronic Practice Based Research Network Linked Dataset was used in this study. Statin adherence was calculated using a modified proportion of days covered (PDC) formula. Individuals with PDC [&ge;] 80% during the two years of observation period were considered as adherent. All analyses were performed with R software. Descriptive and multivariate logistic regression analyses were performed. Sensitivity analysis was performed using the Akaike Information Criterion model selection method. ResultsOverall, 3,432 patients accounting for 57,227 visits met the selection criteria. The mean PDC was 91.6% ({+/-}22.2%), and 72.0% of the patients were adherent to statins (PDC [&ge;] 80%) in the first two years after the date of first prescription. After adjusting for all other variables, statin adherence was positively associated with age (AOR 1.7, 95% CI 1.4 - 2.0), SEIFA index (AOR 1.8, 95% CI 1.2 - 2.6), polypharmacy (AOR 1.8, 95% CI 1.3 - 2.5) and comorbidities (AOR 1.4, 95% CI 1.1 - 1.7), and negatively associated with the number of statin types (AOR 0.6, 95% CI 0.5 - 0.9) and smoking status (AOR 0.7, 95% CI 0.6 - 0.9). The sensitivity analysis showed similar results as the regression model. ConclusionsStatin adherence is influenced by an aging, multimorbid population, who are exposed to polypharmacy, multiple statin options and socioeconomic diversity. Key pointsO_LIAdherence in the first two years after the first date of statin prescription was measured as proportion of days covered (PDC) C_LIO_LIThe mean PDC was 91.6% ({+/-}22.2%) C_LIO_LI72.0% of the patients were adherent to statins, with PDC [&ge;] 80% C_LIO_LIStatin adherence was positively associated with age, area-based social advantage and disadvantage index, polypharmacy and comorbidities C_LIO_LIStatin adherence was negatively associated with the number of statin types prescribed to the patients and the smoking status of patients C_LI Plain Language SummaryThe objective of this study was to identify predictors of statin adherence among patients in the first two years after the date of first prescription using real-world data. The dataset used was the Electronic Practice Based Research Network Linked Dataset. Statin adherence was calculated using proportion of days covered (PDC). A PDC [&ge;] 80% during the two years of observation period were considered as adherent. Overall, 3,432 patients were eligible for this study, and 72.0% of them were adherent to statins in the first two years after the date of first prescription. Statin adherence was positively associated with age, area-based social advantage and disadvantage index, number of medicines taken by the patient and number of chronic conditions that the patient suffered. Moreover, statin adherence was negatively associated with the number of statin types prescribed to the patients and smoking status of patients.

Background-Blockers (ABs) are the most commonly prescribed medications for benign prostatic hyperplasia (BPH), a highly prevalent condition. Although the ALLHAT raised concerns about cardiovascular (CV) safety of nonselective ABs for the treatment of hypertension, the comparative CV risk profile of selective 1A-adrenergic receptor (1A-AR) antagonists for BPH remains unclear. MethodsWe conducted a retrospective cohort study using the TriNetX federated research network (158 million patients across 113 healthcare organizations). Males aged 55 to 90 years with BPH who initiated ABs or 5-ARIs between October 1, 2015, and database lock were included. Three propensity score-matched analyses were conducted: (1) selective 1A-AR antagonists versus 5-ARIs (n=48,096 per group); (2) nonselective ABs versus 5-ARIs (n=33,232 per group); and (3) 1A-selective versus nonselective ABs (n=54,872 per group). Exposures were new use of selective 1A-AR antagonists, nonselective ABs, or 5-ARIs with evidence of adherence. Main outcomes and measures were heart failure (HF) hospitalization, acute MI, stroke, any hospitalization, major adverse CV events (MACE), and composite MACE plus HF at 1, 3, and 5 years. ResultsIn the 1A-selective AB versus 5-ARI analysis, 1A-selective ABs were associated with increased risk at 1 year of HF (hazard ratio [HR], 1.48 [95% CI, 1.39-1.57]), MI (HR, 1.41 [95% CI, 1.28-1.54]), and stroke (HR, 1.36 [95% CI, 1.22-1.50]). Similar patterns were observed for nonselective ABs versus 5-ARIs: HF (HR, 1.46), MI (HR, 1.29), stroke (HR, 1.32). At 5 years, CV risks remained elevated: HF (HR, 1.50 for selective ABs; HR, 1.52 for nonselective ABs), MI (HR, 1.41; HR, 1.30), and stroke (HR, 1.37; HR, 1.29). Head-to-head comparison of selective versus nonselective ABs showed similar CV outcomes (HF HR, 1.10 at 1 year). ConclusionsBoth 1A-selective and nonselective ABs were associated with increased CV event risk compared with 5-ARIs that persisted through 5 years of follow-up. These findings, which were robust across sensitivity analyses and specific to clinically important CV endpoints, may inform shared decision-making for BPH pharmacotherapy.

BackgroundModern natural language tools have potential to improve clinical workflows, but few have been successfully deployed in practice. Here, we present the development, deployment, and evaluation of an AI language tool for generating preliminary clinical sign-outs in a urine drug testing service. MethodsLarge language models (LLMs) were used to extract substance use patterns from 83,553 urine drug test interpretations. We then trained an AI model using these data to predict substance use from qualitative and quantitative urine testing results. Predicted substance use patterns were used to create preliminary clinical sign-out statements, which were then integrated into an existing clinical workflow. Pre- and post-deployment user studies were performed to evaluate model performance and user experience within this workflow. ResultsLLM-based extraction of substance-use patterns was 99.9% accurate, outperforming human labelling. Substance use prediction was similarly accurate, with area under the ROC curve > 0.99 across 33 drug categories. Workflow integration reduced clinical sign-out times by 65s per case (51% efficiency gain), with the greatest benefits seen for less experienced users. ConclusionsAI-based interpretation of urine drug testing was fast and accurate, providing significant efficiency gains to the clinical service. This demonstrates that natural language tool integration can provide substantial clinical benefit, without comprising quality of care.

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.

BackgroundNon-adherence to lipid-lowering therapy (LLT) affects up to half of patients and contributes substantially to preventable cardiovascular morbidity and mortality. Existing measures, such as the proportion of days covered, provide cross-sectional summaries but fail to capture the dynamic patterns of adherence over time. Although group-based trajectory modelling identifies distinct longitudinal adherence patterns, no approach currently predicts trajectory membership prospectively while incorporating patient-reported barriers. We developed BRIDGE, a barrier-informed Bayesian model to predict adherence trajectories and identify their underlying drivers. MethodsBRIDGE incorporates patient-reported barriers as structured prior information within a Bayesian framework for adherence-trajectory prediction. The model was designed not only to estimate which patients are likely to follow different adherence trajectories, but also to generate clinically interpretable probability estimates that help explain why those trajectories may arise and what modifiable factors may be most relevant for intervention. ResultsBRIDGE achieved a macro AUROC of 0.809 (95% CI 0.806 to 0.813), comparable to random forest (0.815 (95% CI 0.812 to 0.819)) and XGBoost (0.821 (95% CI 0.818 to 0.824)), two widely used machine-learning benchmarks for structured clinical prediction. Calibration was superior to random forest (Brier score 0.530 vs 0.545; ), and performance was stable across six independent training runs (AUROC SD = 0.003). Incorporating barrier-informed priors improved accuracy by 3.5% and calibration by 5.5% compared to flat priors, showing that incorporation of patient-reported barriers added value beyond electronic medical record data alone. Four clinically distinct adherence trajectories were identified: gradual decline associated with treatment deprioritisation amid polypharmacy (10.4%), early discontinuation linked to asymptomatic risk dismissal (40.5%), rapid decline associated with intolerance (28.8%), and persistent adherence (20.2%). Counterfactual analysis identified trajectory-specific intervention levers. ConclusionsBRIDGE provides accurate and well-calibrated prediction of adherence trajectories while offering clinically actionable insights into their underlying drivers. By integrating patient-reported barriers with routine clinical data, the model supports targeted, mechanism-informed interventions at the point of prescribing to improve adherence to cardioprotective therapies. FundingMRFF CVD Mission Grant 2017451 Evidence before this studyWe searched PubMed and Scopus from database inception to December 2025 using the terms "medication adherence", "trajectory", "prediction model", "Bayesian", "lipid-lowering therapy", and "barriers", with no language restrictions. Group-based trajectory modelling has consistently identified three to five adherence patterns across cardiovascular cohorts; however, these applications have been descriptive rather than predictive. Machine-learning models for adherence prediction achieve moderate discrimination but treat adherence as a binary or continuous outcome, thereby overlooking the clinically meaningful heterogeneity captured by trajectory approaches. One prior study applied a Bayesian dynamic linear model to examine adherence-outcome associations, but it did not predict adherence trajectories or incorporate patient-reported barriers. To our knowledge, no published model integrates patient-reported barriers into trajectory prediction. Added value of this studyBRIDGE is, to our knowledge, the first model to incorporate patient-reported adherence barriers as hierarchical domain-informed priors within a Bayesian framework for trajectory prediction. Using 108 predictors derived from routine electronic medical records, the model achieves discrimination comparable to state-of-the-art machine-learning approaches while additionally providing uncertainty quantification, barrier-level interpretability, and counterfactual insights to inform intervention strategies. The identified trajectories differed not only in adherence level but also in switching behaviour, drug-class evolution, and medication burden, suggesting distinct underlying mechanisms of non-adherence that may require tailored clinical responses. Implications of all the available evidenceEach adherence trajectory implies a distinct intervention target: asymptomatic risk communication for early discontinuers (40.5% of patients), proactive tolerability management for rapid decliners, medication simplification for patients with gradual decline associated with polypharmacy, and maintenance support for persistent adherers. By integrating routinely collected clinical data with patient-reported barriers, BRIDGE can be deployed within existing primary care EMR infrastructure to generate actionable, trajectory and patient--specific recommendations at the point of prescribing, helping to bridge the gap between adherence measurement and targeted adherence management.

BackgroundGLP-1 receptor agonists (GLP-1RAs) and SGLT2 inhibitors (SGLT2Is) have established cardiovascular benefits for patients with type 2 diabetes mellitus (T2DM), with similar class-level effectiveness found in previous studies. However, real-world comparative effectiveness assessments of individual agents remain limited. ObjectivesTo compare the cardiovascular effectiveness of individual GLP-1RAs and SGLT2Is. MethodsWe conducted a multi-national, retrospective, new-user active-comparator cohort study using 10 US and non-US administrative claims and electronic health record databases. The study included 1,245,211 adults with T2DM receiving metformin who initiated second-line therapy with one of six GLP-1RAs (albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide, semaglutide) or one of four SGLT2Is (canagliflozin, dapagliflozin, empagliflozin, ertugliflozin). Empagliflozin (393,499; 31.6%), semaglutide (235,585; 18.9%), dapagliflozin (208,666; 16.8%), and dulaglutide (207,348; 16.8%) were most commonly used. A secondary subgroup analysis included 316,242 patients with established cardiovascular diseases (CVD). Primary outcomes were 3-point major adverse cardiovascular events (MACE: acute myocardial infarction, stroke, sudden cardiac death) and 4-point MACE (adding hospitalization/ER visit with heart failure). Secondary outcomes included the individual components. Hazard ratios (HRs) were estimated for pairwise agent comparisons while on-treatment (per-protocol) and over total follow-up using Cox proportional hazards models, with propensity score adjustments, negative control calibration, and pre-specified study diagnostics to guard against potential confounding. Random-effects meta-analysis produced summary HR estimates across data sources that passed diagnostics. ResultsAcross the study cohort, individual GLP-1RAs and SGLT2Is demonstrated broadly similar cardiovascular effectiveness, both within and across drug classes. For example, semaglutide and empagliflozin showed comparable risks for 3-point MACE (meta-analytic HR 1.05; 95% CI 0.79-1.39) and 4-point MACE (meta-analytic HR 0.95; 95% CI 0.81-1.12), with consistent findings in the CVD subgroup. Study diagnostics confirmed adequate equipoise, covariate balance and statistical power to detect similarity in HRs between 0.8 and 1.2 for commonly used agents. ConclusionsIn this large-scale real-world study, individual GLP-1RAs and SGLT2Is exhibited largely comparable cardiovascular benefits, including in patients with established CVD. These findings align with network meta-analytic estimates from major cardiovascular outcome trials and broadly support current treatment guidelines. Clinical choices should be guided by relevant factors such as safety, adherence, tolerability, cost, and patient preference, where further work is needed.

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from PharmGKB (levels of evidence 1A-2B), CPIC, and PharmVar. Additionally, WES limitations and the feasibility of imputing non-coding pharmacogenetic variants were evaluated. ResultsPopulation frequencies of alleles and metabolic phenotypes were determined for 13 Very Important Pharmacogenes (VIPs), along with the distribution of HLA class I and II alleles. The highest allelic and phenotypic variability was observed in CYP family genes, particularly CYP2D6, CYP2C19, and CYP2B6. A total of 663 pharmacogenomic annotations were identified, predominantly related to drug metabolism (50.38%) and toxicity (29.56%), including psychotropic agents, anticoagulants, statins, opioid analgesics, antineoplastic agents, and immunosuppressants. At least 32 drugs require pharmacogenetic testing based on variants located in non-coding regions, as well as accurate CYP2D6 copy number determination. Linkage disequilibrium analysis demonstrated the inability to reliably impute most non-coding pharmacogenetic variants from WES data. ConclusionThese findings represent one of the largest reference assessments to date of pharmacogenetically significant variant and HLA allele frequencies in the Russian population. The results confirm the utility of WES for population pharmacogenomic screening while simultaneously highlighting its fundamental limitations and the need for alternative genetic diagnostic methods in selected cases.