The Journal of Clinical Pharmacology最新文献

{"title":"Optimizing Linezolid Dosing in Lung Transplant Recipients: Population Pharmacokinetics, Target Attainment, and Thrombocytopenia Risk Assessment","authors":"Dan Zhang PhD,&nbsp;Wenwen Du PhD,&nbsp;Pengmei Li MS,&nbsp;Wenqian Chen PhD,&nbsp;Xiaoxing Wang PhD","doi":"10.1002/jcph.70153","DOIUrl":"10.1002/jcph.70153","url":null,"abstract":"<p>The pharmacokinetic (PK) profiles of linezolid in lung transplant recipients (LTRs) differ from those in other patients. This study aimed to develop a population pharmacokinetic (PopPK) model to evaluate dosage regimens based on various biological covariates and assess the risk of thrombocytopenia. The nonlinear mixed-effects modeling method was employed to establish the PopPK model. Monte Carlo simulations assessed the probability of target attainment (PTA) under different covariates and minimum inhibitory concentration (MIC) ranges. The study included 43 LTRs with 142 linezolid concentration–time data points. The final model identified estimated glomerular filtration rate and tacrolimus trough level as key covariates for apparent clearance. The 300 mg bid regimen maintained peak and trough concentrations within the 2–8 mg/L range, while the 600 mg qd dosing group achieved a PTA greater than 80% across an MIC range of 0.25–1 mg/L. Linezolid C_min impacted platelet levels, with baseline levels influencing the severity of reduction. This PopPK model offers valuable insights for optimizing linezolid dosing, considering immunosuppressant therapy and thrombocytopenia risk, and serves as a reference for dose selection in post-surgical LTRs.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146127126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing a Common Misconception of Simple Additive and Cumulative Drug Inhibition: Multiple Weak Inhibitors of Common Metabolic Pathway Do Not Pose a Strong Interaction Risk!","authors":"Daniel Scotcher PhD,&nbsp;Avijit Ghosh PhD,&nbsp;Aleksandra Galetin PhD,&nbsp;Amin Rostami-Hodjegan PhD, FCP","doi":"10.1002/jcph.70154","DOIUrl":"10.1002/jcph.70154","url":null,"abstract":"&lt;p&gt;The global population is becoming older, and prevalence of multimorbidity and polypharmacy is increasing.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; Most research into pharmacokinetic drug–drug interactions (DDIs) has focused on pairwise interactions between drugs and corresponding metabolites, while the impact of co-administration of multiple drugs has received less attention. More recently, the differences in DDI risk between population sub-groups has received increased attention (e.g., in pediatrics vs adults&lt;span&gt;&lt;sup&gt;2, 3&lt;/sup&gt;&lt;/span&gt;). It is well recognized that simultaneous inhibition of multiple different pathways of a drug's elimination can lead to much larger increases in drug exposure compared with inhibition of only the major pathway.&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; The potential magnitude of DDI in this scenario is linked with the fraction metabolized (fm) of each pathway for the object (also known as “victim”) drug&lt;span&gt;&lt;sup&gt;5, 6&lt;/sup&gt;&lt;/span&gt; (Equation 1). In contrast, there is a common misconception about the cumulative effects of multiple precipitant (also known as “perpetrator”) drugs that competitively inhibit the same enzyme. It is often mistakenly perceived that cumulative effects of multiple weak inhibitors are likely to lead to a strong DDI. This misconception arises despite the true relationship being governed by a simple concentration–response relationship, with a well-known theoretical basis (Equations 1 and 2),&lt;span&gt;&lt;sup&gt;4, 5&lt;/sup&gt;&lt;/span&gt; analogous to the dose dependence of competitive inhibition. Surprisingly, there is very limited research on multiple inhibitors and their implications on clinical endpoints such as the ratio of area under the curve of the plasma concentration–time profiles (AUCR) in the interaction phase relative to the control,&lt;span&gt;&lt;sup&gt;7&lt;/sup&gt;&lt;/span&gt; possibly contributing to such misunderstandings about polypharmacy–DDI risks.&lt;/p&gt;&lt;p&gt;The ICH M12 Drug Interaction Studies Guidance defines weak, moderate, and strong CYP inhibitors as causing ≥1.25- to &lt;2-fold, ≥2- to &lt;5-fold, and ≥5-fold increase in AUC of a sensitive index CYP substrate.&lt;span&gt;&lt;sup&gt;8&lt;/sup&gt;&lt;/span&gt; Assuming a sensitive CYP substrate will have fm ∼ 1, the corresponding [I]/Ki for weak, moderate, and strong CYP inhibitors will be ≥0.25 to &lt;1, ≥1 to &lt;4, and ≥4, respectively. Hence a 4-fold difference in [I]/Ki (after correction for exposure) may be a useful approach to benchmark between weak, moderate, and strong inhibitors.&lt;/p&gt;&lt;p&gt;When fm = 1 the relationship between ∑[I]/Ki and AUCR is linear (AUCR = ∑[I]/Ki + 1, Figure 1a). However, this relationship is not proportional due to the non-zero intercept.&lt;span&gt;&lt;sup&gt;5, 6, 9&lt;/sup&gt;&lt;/span&gt; Particularly at low ∑[I]/Ki values (e.g., from multiple weak inhibitors), the relative change in AUCR will be much lower than the relative change in [I]/Ki (Figure 1b). In other words, to see a change in AUCR from 1.25 to 2 for a weak inhibitor, the co-administration of three additional inhibitors with equivalent [I]/Ki wou","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12859390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146093915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obstetric Pharmacology at an Inflection Point","authors":"Ahizechukwu C. Eke MD, PhD, MPH","doi":"10.1002/jcph.70152","DOIUrl":"10.1002/jcph.70152","url":null,"abstract":"&lt;p&gt;Obstetric pharmacology is undergoing a long-awaited evolution. Historically, pregnancy was treated as a “confounding condition,” leading to systematic exclusion from drug development programs and evaluation. Increasingly however, the field is shifting toward a data-generating discipline that recognizes pregnancy and lactation as biologically dynamic pharmacologic states. Pregnancy is not dichotomous: physiologic and placental changes evolve across gestation, vary by underlying disease and maternal phenotype, and then resolve variably in the postpartum period. These time-varying processes mean that a single, fixed “pregnancy dose” is often an oversimplification.&lt;/p&gt;&lt;p&gt;Several developments make this moment feel like a true “infection point” rather than incremental progress. First, the therapeutic pipeline now includes agents with pregnancy-specific value propositions (e.g., FcRn inhibitors for antibody-mediated disease) as well as programs explicitly designed around fetal or neonatal benefit (e.g., maternal immunization). Second, quantitative tools for characterizing maternal, placental, fetal, and lactational exposures have matured, most notably physiologically based pharmacokinetic (PBPK) modeling and population pharmacokinetics. Third, regulatory expectations have become more explicit. The Pregnancy and Lactation Labeling Rule (PLLR)&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; requires narrative risk summaries supported by data, and the International Council on Harmonization (ICH E21) document&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; provides a contemporary framework for inclusion of pregnant and breastfeeding women in clinical trials.&lt;/p&gt;&lt;p&gt;This “inflection point” builds on earlier field-shaping work rather than replacing it. The 2021 FDA/M-CERSI workshop on fetal pharmacology and therapeutics,&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt; and scholarly efforts that followed, helped crystallize the conceptual and methodological agenda for the field. What is changing now is the convergence of pipeline, quantitative methods, and policy guidance, narrowing the gap between what is technically feasible and what is operationally expected. A peer-reviewed supplement in the &lt;i&gt;Journal of Clinical Pharmacology&lt;/i&gt; (2022)&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; further articulates the regulatory science and methodologic foundations for obstetric pharmacology.&lt;/p&gt;&lt;p&gt;At the same time, realism is essential. Advances in pediatric therapeutics were driven not only by scientific consensus but also by legislation that created incentives and obligations, most notably the Best Pharmaceuticals for Children Act (BPCA) and the Pediatric Research Equity Act (PREA). Obstetric pharmacology faces an analogous “therapeutic orphan” problem. In the absence of policy levers that reward or require evidence generation, pregnancy data continue to emerge late, often after widespread real-world use has already occurred.&lt;/p&gt;&lt;p&gt;Against this backdrop, the central challenge for obstetric pharmacology is not simply whether to “include pregnancy,” but","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://accp1.onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Impact of Adjusted Valproic Acid Level in Patients with Hypoalbuminemia: A Single-Center Cohort Study","authors":"Renad Bin Naheet PharmD,&nbsp;Khalid Al Sulaiman BCCCP, BCNSP, MBA, FCCM,&nbsp;Khuld Aloufi PharmD,&nbsp;Abdullah F. Alharthi PharmD,&nbsp;Mashael AlFaifi PharmD,&nbsp;Lama Nazer PharmD,&nbsp;Mohammad Shawaqfeh PharmD,&nbsp;Abdulmajeed M. Alshehri PharmD,&nbsp;Mohammed Abutaleb PharmD,&nbsp;Abdulaziz Alarifi PhD,&nbsp;Asma A. Alshehri PharmD,&nbsp;Ahmad H. Al-Ani PharmD,&nbsp;Omar Saggaf MD,&nbsp;Ramesh Vishwakarma PhD,&nbsp;Maryam Alharbi PharmD,&nbsp;Delael Alnaser PharmD,&nbsp;Saud Alrashdi PharmD,&nbsp;Abdulaziz A. Jaly PharmD,&nbsp;Farhan Alenezi MD,&nbsp;Moayad Alkhlewi MD,&nbsp;Abdulelah Alanazi MSc,&nbsp;Ohoud Aljuhani PharmD","doi":"10.1002/jcph.70139","DOIUrl":"10.1002/jcph.70139","url":null,"abstract":"<p>Valproic acid (VPA) is highly protein-bound, thereby impacting its free fraction and clearance in hypoalbuminemia. There is limited data on VPA use in such patients. Thus, this study evaluates the impact of adjusted VPA concentration (aVPAc) in predicting effectiveness and adverse effects compared to total VPA (tVPA) levels in hypoalbuminemic patients. A retrospective cohort study involved adult patients with seizures or epilepsy between January 1, 2016, and December 31, 2022. The levels of tVPA and aVPA (adjusted for albumin) were compared using receiver operating characteristic curves, and AUC differences were assessed using the DeLong method. Safety endpoints included hepatotoxicity, hyperammonemia, hyponatremia, and thrombocytopenia, while effectiveness endpoints were seizure occurrence, status epilepticus, and the use of additional antiepileptic medications during hospitalization. Of the 1621 screened patients, 71 with hypoalbuminemia received VPA. An aVPAc threshold of 154.19 mg/dL demonstrated higher sensitivity (86%) but lower specificity (47%) for predicting hepatotoxicity compared to a tVPA threshold of 67.53 mg/dL (sensitivity: 71%, specificity: 72%). Although aVPAc yielded a comparable negative predictive value (96% vs 95%), tVPA showed superior positive predictive value (25% vs 18%) and a higher Youden index (0.43 vs 0.33), indicating better overall discriminatory performance; however, these findings did not achieve statistical significance. In contrast, an aVPAc threshold of 188 mg/dL showed a sensitivity of 100% and a specificity of 82% for predicting hyperammonemia, which is superior to the tVPA threshold of 74.32 mg/dL that has a sensitivity of 40% and a specificity of 88%. The aVPAc also achieved a higher Youden index of 0.82 compared to 0.28 for tVPA. Adjusted VPA concentrations showed greater sensitivity than tVPA in predicting hepatotoxicity and hyperammonemia, suggesting potential utility for ruling out these adverse effects in hypoalbuminemic patients. Further research with a larger sample size is needed to validate these findings.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146031251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"No QTcF Prolongation with Sepiapterin: Results From a Thorough QT Study in Healthy Subjects at Therapeutic and Supratherapeutic Doses","authors":"Lan Gao PhD,&nbsp;Hongqi Xue PhD,&nbsp;Borje Darpo MD, PhD,&nbsp;Kimberly Ingalls MD,&nbsp;Diksha Kaushik PhD,&nbsp;Neil Smith PharmD,&nbsp;Ronald Kong PhD,&nbsp;Lee Golden MD","doi":"10.1002/jcph.70149","DOIUrl":"10.1002/jcph.70149","url":null,"abstract":"<p>Sepiapterin and its major metabolite <i>6R</i>-L-erythro-5,6,7,8-tetrahydrobiopterin (BH₄) bind to distinct variants of phenylalanine hydroxylase (PAH), which converts excess phenylalanine to tyrosine, thereby stabilizing, enhancing, and prolonging PAH activity. Sepiapterin was recently approved in Europe and the USA for the treatment of hyperphenylalaninemia patients with phenylketonuria, an inherent metabolic disease caused by PAH deficiency. A thorough QT study of sepiapterin in healthy volunteers at therapeutic (60 mg/kg) and supratherapeutic (120 mg/kg) doses was conducted to assess potential cardiovascular risks. Thirty-two participants were randomized into one of 12 sequences and received single doses of sepiapterin (60 or 120 mg/kg), moxifloxacin 400 mg, or placebo in separate periods. Sepiapterin had no effect on heart rate or cardiac conduction (PR/QRS interval). Saturable sepiapterin absorption was observed, which resulted in less than dose-proportional increase of sepiapterin and BH₄ and limited the maximum plasma concentrations clinically achievable. Using concentration-QT analysis, the placebo-corrected change from baseline in QT interval corrected using Fridericia's formula (ΔΔQTcF) was −2.11 (90% CI: −3.44, −0.79) ms at geometric mean baseline-corrected BH₄ C_max (728 ng/mL) and −1.9 (−3.25, −0.56) ms at sepiapterin C_max (2.08 ng/mL) at the supratherapeutic dose of 120 mg/kg. An effect on ΔΔQTcF exceeding 10 ms was excluded within the observed concentration range of baseline-corrected BH₄ up to 1088 ng/mL and sepiapterin up to 5.77 ng/mL. The consistency of results from this study and the previous concentration-QTc analysis based on pooled data from multiple clinical studies demonstrated the reliability of using concentration-QTc for assessing cardiovascular risks in early clinical development.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12801174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on “Model Informed Precision Dosing of Tacrolimus in Children Following Heart Transplant”","authors":"Princy Kashyap PhD,&nbsp;Manoj Kumar PhD,&nbsp;Ramenani Hari Babu PhD,&nbsp;Mahesh Kumar Gupta PhD","doi":"10.1002/jcph.70140","DOIUrl":"10.1002/jcph.70140","url":null,"abstract":"&lt;p&gt;Dear Editor,&lt;/p&gt;&lt;p&gt;We read with great interest the study by Wagstaff et al,&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; which evaluated a decision support tool (DST) based on a population pharmacokinetic (popPK) model to individualize tacrolimus dosing in pediatric heart transplant recipients. This innovative work addresses a key challenge in pediatric transplantation—the safe and timely attainment of therapeutic immunosuppression in a population marked by substantial pharmacokinetic variability. While the study represents progress toward precision dosing, several methodological and interpretive aspects merit further consideration for clinical translation.&lt;/p&gt;&lt;p&gt;The prospective evaluation of a Bayesian DST marks an important translational step beyond model development. However, the single-center design and small sample size (n = 15) limit generalizability, given the ethnically homogeneous cohort and limited genetic characterization. The use of a historical rather than concurrent control introduces potential bias from temporal changes in clinical practice.&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; Although restricting analysis to first-time pediatric transplant recipients ensures population uniformity, the post hoc exclusion of patients receiving continuous renal replacement therapy (CRRT) highlights the need for clearer inclusion criteria to ensure consistent applicability.&lt;/p&gt;&lt;p&gt;The reported 3-day reduction in time to stable therapeutic tacrolimus concentrations (&lt;i&gt;P&lt;/i&gt; = .03) is clinically meaningful. Nonetheless, the small sample and absence of randomization raise concerns about statistical stability and confounding factors such as age and concomitant antifungal use. Reporting confidence intervals for mean differences would strengthen interpretation by defining precision around estimates. While the DST's fidelity to NONMEM modeling was validated in silico,&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt; clinical performance depends on appropriate covariate weighting and sampling frequency areas underexplored in the manuscript.&lt;/p&gt;&lt;p&gt;Reliance on retrospective data for model calibration is reasonable, yet the dependence on creatinine clearance as a surrogate for tacrolimus disposition warrants further justification. As the authors note, creatinine clearance likely reflects broader physiological influences, such as hepatic perfusion, rather than renal elimination, underscoring the need for refinement of structural assumptions. Moreover, the absence of CYP3A5 genotyping during DST calibration limits predictive robustness. Incorporating pharmacogenomic data could enhance parameter individualization and reduce misdosing in expressor phenotypes.&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;Clinically, the DST offers a promising framework for model-informed precision dosing (MIPD) in pediatric transplantation. The observed reduction in time to therapeutic range may translate to shorter hospital stays, fewer blood draws, and improved graft outcomes. However, implementation outside the electronic medical record (EMR) co","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://accp1.onlinelibrary.wiley.com/doi/epdf/10.1002/jcph.70140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Estimated Kidney Function Equations for Predicting Aminoglycosides Clearance in Thai Population","authors":"Sirima Sitaruno PharmD, BCP,&nbsp;Warunsuda Sripakdee BPharm, BCP,&nbsp;Orawan Sae-lim PharmD, BCP,&nbsp;Dissaya Watthanapaisal PharmD, BCP,&nbsp;Nuntapong Boonrit PharmD, BCP,&nbsp;Kasemsiri Chandarajoti BPharm, PhD,&nbsp;Rungsun Bhurayanontachai MD,&nbsp;Sutthiporn Pattharachayakul PharmD, BCP","doi":"10.1002/jcph.70150","DOIUrl":"10.1002/jcph.70150","url":null,"abstract":"<p>Disparities in the performance of various kidney function equations in predicting aminoglycoside clearance (CL) have been identified. However, data specific to the Thai population remains limited. This study aimed to evaluate the performance of kidney function equations in estimating aminoglycoside CL in Thai patients. Data were retrospectively collected from hospitalized Thai patients who received amikacin or gentamicin over a 10-year period. Population pharmacokinetic (PK) analysis was performed using a nonlinear mixed-effects modeling approach. The association between aminoglycoside CL and kidney function, estimated by various equations, was ranked based on the magnitude of change in the Akaike Information Criterion (AIC) relative to the base model. A total of 138 adult Thai patients treated with either gentamicin (66%) or amikacin (34%) were enrolled. The non-body surface area (BSA)-indexed estimated glomerular filtration rate (eGFR) equations showed a stronger association with aminoglycoside CL compared to the 1.73 m² BSA-indexed equations. The non-BSA-indexed 2021 Chronic Kidney Disease Epidemiology Collaboration eGFR (2021 CKD-EPI eGFRcr) equation demonstrated the highest association with aminoglycoside CL. The estimated volume of distribution (V) and CL from the final model were 21.91 L and 2.62 L/h, respectively. Among the Thai population, the non-BSA-indexed 2021 CKD-EPI eGFRcr equation of the non-race demonstrated the highest performance in estimating aminoglycoside CL. Further studies are warranted to confirm these findings with other renally eliminated drugs.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145953463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Outcomes and Patient Profiles in the UK Medical Cannabis Registry: A k-Means Clustering Analysis","authors":"Simon Erridge MBBS, BSc,&nbsp;Evonne Clarke MSc, IPresc,&nbsp;Katy McLachlan MPharm, IPresc,&nbsp;Ross Coomber BSc, FRCS,&nbsp;Sushil Beri MD, MRCPCH,&nbsp;Shaheen Khan MSc, MRCP,&nbsp;Mark W. Weatherall PhD, FRCP,&nbsp;Michael W. Platt MA, FRCA, FFPM, RCA,&nbsp;James J. Rucker PhD, MRCPsych,&nbsp;Pedro A. M. Mediano MSc, PhD,&nbsp;Mikael H. Sodergren PhD, FRCS","doi":"10.1002/jcph.70151","DOIUrl":"10.1002/jcph.70151","url":null,"abstract":"<p>There is a paucity of high-quality evidence on the clinical efficacy of cannabis-based medicinal products (CBMPs). The objective of this study was to perform trajectory k-means clustering of health-related quality of life (HRQoL) outcomes in patients prescribed CBMPs to identify distinct response patterns and baseline predictors of treatment outcomes over 24 months. A cohort study of patients enrolled in the UK Medical Cannabis Registry with any qualifying indication was performed. Participants completed patient-reported outcome measures including EuroQol 5-Dimension 5-Level (EQ-5D-5L), Generalized Anxiety Disorder-7 (GAD-7), and Single-Item Sleep Quality Scale (SQS), at baseline, 1, 3, 6, 12, 18, and 24 months. Longitudinal k-means clustering was performed on EQ-5D-5L index values where the optimal number of clusters was selected via the gap statistic. Univariable and multivariable logistic regression analyses identified predictors of cluster membership. The 8945 patients were included in the analysis, from which 10 distinct trajectory clusters were identified, with eight demonstrating HRQoL improvements representing 77.72% of the cohort (n = 6952). Over 70% of participants reported improved EQ-5D-5L index values at each timepoint, whilst 54.21% (n = 4849) and 44.07% (n = 3942) achieved clinically significant improvements in GAD-7 and SQS at 24 months, respectively. Adverse events were reported by 13.65% (n = 1221) of patients, predominantly rated as mild (n = 4732; 42.31%) or moderate (n = 4860; 43.46%). Baseline patient characteristics, particularly treatment indication, severe anxiety, poor sleep quality, female sex, and cannabis-naïve status, were stronger predictors of favorable treatment response than product-specific factors.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Physiologically Based Pharmacokinetic Modeling and Simulations to Predict Antihypertensive Drug Doses in Cirrhotic Patients","authors":"Mai Tarek BSc (Pharmacy),&nbsp;Ahmed A. Ali PhD,&nbsp;Reda Biomy PhD,&nbsp;Khaled Abdelkawy PhD,&nbsp;Eman El-Khateeb PhD","doi":"10.1002/jcph.70148","DOIUrl":"10.1002/jcph.70148","url":null,"abstract":"<p>Liver cirrhosis can alter drug pharmacokinetics, often requiring dose adjustments. Physiologically based pharmacokinetic (PBPK) modeling aids in predicting these pharmacokinetic changes in cirrhosis patients. This study developed and validated PBPK models for multiple antihypertensive drugs to predict dosing across varying severities of cirrhosis. Models were initially validated in healthy volunteers, then adjusted to incorporate cirrhosis-specific pathophysiological changes. Predicted results (area under the curve [AUC] and plasma maximum concentration [Cmax]) showed good agreement with clinical data (within 2-fold). The models were further used to simulate untested cirrhotic populations and to estimate unbound plasma AUC across different disease stages, and the results were compared with the healthy population. The model predicted that the healthy doses of nifedipine 20 mg three times daily (TID), verapamil 80 mg TID, nebivolol 10 mg once daily, and diltiazem 60 mg TID should be adjusted to 44%, 41%, 49.8%, and 51% of these doses, respectively, in the mild cirrhosis population. For moderate cirrhosis, the predicted reductions were to 21%, 25%, 29.8%, and 39%, respectively. In severe cirrhosis, greater reductions to 9.9%, 19%, 12.3%, and 26%, respectively, were necessary to achieve the same unbound drug exposures as in healthy subjects. Among the studied drugs, nifedipine was the most affected and diltiazem was the least affected by cirrhosis, highlighting variability in hepatic impact across antihypertensive drugs. In the absence of dedicated clinical trials in cirrhosis for these drugs, validated PBPK models offer evidence-based insights to support clinicians in evaluating antihypertensive dosing options.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145919015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioequivalence Assessment for Intranasal Rapid-Acting Drug Products","authors":"Zhijun (Kevin) Wang PhD,&nbsp;Shein Chung Chow PhD,&nbsp;Moses S. S. Chow PharmD, FCP","doi":"10.1002/jcph.70138","DOIUrl":"10.1002/jcph.70138","url":null,"abstract":"<p>Bioequivalence assessment is critical for generic drug approval, but conventional bioequivalent criteria for identical formulations and routes may not be suitable for cross-route comparisons, especially for rapid-acting drugs. Intranasal formulations provide faster absorption and onset of action compared with oral products. At present, establishing bioequivalence across these routes remains challenging. This study proposes a novel method using partial AUCs. Partial AUC (AUC_0-ta) was defined as the AUC targeting the rapid absorption phase that better reflects therapeutic onset with ta numerically equal to T_max + 1 SD for the reference product. To address high variability in cross-route studies, the BE acceptance range for geometric mean ratios of AUC_0-ta was widened to 70%–143%. To evaluate this approach, plasma concentration data from two crossover studies comparing intranasal vardenafil (5 and 3.8 mg) with an approved oral tablet (10 mg) were analyzed. Intra- and inter-subject variabilities were estimated. Initial results indicated that bioequivalence could not be demonstrated due to high variability. However, the simulation with optimized dose selection and increased sample size (e.g., 48 subjects) shows that the 90% confidence intervals for both C_max and AUC_0-ta fell within the expanded bioequivalent limits. In contrast, total AUC failed to meet BE requirements, underscoring its limited relevance for rapid-onset, cross-route comparisons. This adapted BE approach may offer a more suitable method for intranasal and other rapid-acting products. With further validation, it could support regulatory approval and improve patient access to fast-acting therapies.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145918974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}