Clinical Pharmacokinetics最新文献

{"title":"Clinical Pharmacokinetics and Pharmacodynamics of Remimazolam.","authors":"Bas T de Jong, Douglas J Eleveld, Keira P Mason, Michel M R F Struys","doi":"10.1007/s40262-025-01548-7","DOIUrl":"10.1007/s40262-025-01548-7","url":null,"abstract":"<p><p>Remimazolam is a benzodiazepine with a high affinity for the γ-aminobutyric acid type A-receptor thereby inducing sedation and amnesia. It is a short-acting drug, has a fast onset, short duration of action, and a predictable recovery profile. Remimazolam is metabolized mainly into CNS7054. In recent years, numerous population pharmacokinetic and combined pharmacokinetic/pharmacodynamic studies have been published. This narrative review aims to give an overview of and insight into pharmacokinetic/pharmacodynamic models and related clinical effects. Body weight, age and American Society of Anesthesiologists classification, sex, hepatic function, and extracorporeal circulation have been shown to significantly impact remimazolam pharmacokinetics. Body mass index, race, concomitant opioid administration, and a CNS7054-induced tolerance effect may be covariates. The labeling of remimazolam is not consistent worldwide as it has been approved for general anesthesia and/or sedation in different countries. To date, remimazolam is only approved by the intravenous route. Remimazolam has been approved for general anesthesia and/or sedation. The incidence of postoperative nausea and vomiting seems higher compared with propofol, yet pain on injection is less common. One study has published population pharmacokinetics in children. Reports on alternative methods to intravenous administration have been sparse.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1263-1282"},"PeriodicalIF":4.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12414031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144674017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Malnutrition and Its Effect on Drug Pharmacokinetics: A Clinical Perspective.","authors":"Nokwanda N Ngcobo","doi":"10.1007/s40262-025-01558-5","DOIUrl":"10.1007/s40262-025-01558-5","url":null,"abstract":"<p><p>Malnutrition significantly alters the pharmacokinetics of medications, particularly in vulnerable populations such as children, pregnant women, elderly individuals, and individuals in low- and middle-income countries. These populations are often more vulnerable to the effects of malnutrition because of physiological, metabolic and socioeconomic factors. Changes in body composition, organ function and plasma protein levels associated with malnutrition can impact drug absorption, distribution, metabolism and excretion. In malnourished individuals, decreased serum albumin levels may increase the free (unbound) fraction of highly protein-bound acidic drugs, potentially elevating the risk of toxicity. However, this relationship is not universally straightforward, as it depends on the drug's protein-binding characteristics, hepatic and renal function, volume of distribution and compensatory changes in drug clearance. In addition, malnutrition's effects on liver enzymes, such as cytochrome P450 isoforms, and kidney function can result in unpredictable drug clearance, particularly for narrow-therapeutic-index medications. Emerging evidence also highlights the interplay between malnutrition and pharmacogenomics, with genetic variations further modulating drug metabolism and response. Addressing these complexities requires the development of tailored dosing regimens and adaptive therapeutic strategies to optimise treatment outcomes in these at-risk groups. This review accentuates the critical need for more robust research to inform clinical guidelines and improve health equity in managing malnourished populations globally.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1283-1293"},"PeriodicalIF":4.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12414074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144834339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Pharmacokinetic and Pharmacodynamic Modelling and Simulation for Nedosiran Clinical Development and Dose Guidance in Pediatric Patients with Primary Hyperoxaluria Type 1.","authors":"Steven Zhang, Pablo Gamallo, Verity Rawson","doi":"10.1007/s40262-025-01540-1","DOIUrl":"10.1007/s40262-025-01540-1","url":null,"abstract":"<p><strong>Background and objectives: </strong>Nedosiran (Rivfloza^®) is an RNA interference (RNAi) therapy approved for individuals aged ≥ 2 years with primary hyperoxaluria type 1 (PH1), a rare autosomal-recessive disorder causing renal failure and systemic oxalosis. Nedosiran silences lactate dehydrogenase (LDH) mRNA in hepatocytes, reducing oxalate levels. This study evaluated the model-informed clinical development of nedosiran to support proposed doses in children aged 2 to < 12 years with PH1.</p><p><strong>Methods: </strong>A population pharmacokinetic/pharmacodynamic (Pop-PK/PD) model characterizing the plasma concentration-time profile of nedosiran and its effect on the spot urine oxalate-to-creatinine ratio (Uox/Cr) was developed using data from six trials. Simulations assessed spot Uox/Cr reduction in children aged 2 to < 12 years for the proposed dosing regimen versus those aged ≥ 12 years weighing ≥ 50 kg with similar renal function.</p><p><strong>Results: </strong>The datasets included 2087 PK (N = 148) and 668 spot Uox/Cr (N = 41, with PH1) observations. Body weight, estimated glomerular filtration rate (eGFR), and PH type were covariates in the PK model, with body weight in low and high percentiles affecting nedosiran exposures. Moderate renal impairment (eGFR 30-59 mL/min/1.73 m²) increased exposure, while only age was significant for baseline Uox/Cr in the PD model. Simulations showed similar Uox/Cr reduction and times to maximum effect in children aged 2 to < 12 years, treated once-monthly (Q1M) with 3.5 mg/kg, compared to those aged ≥ 12 years treated Q1M with 170 mg.</p><p><strong>Conclusions: </strong>Simulations based on the final Pop-PK/PD model support the 3.5 mg/kg Q1M dosing regimen in children aged 2 to < 12 years with PH1 and relatively intact kidney function (eGFR ≥30 mL/min/1.73 m²).</p><p><strong>Trial registration: </strong>Trials are registered at ClinicalTrials.gov with study numbers NCT03392896 (PHYOX1), NCT03847909 (PHYOX2), NCT04042402 (PHYOX3), and NCT05001269 (PHYOX8) and at EudraCT with study numbers 2018-003098-91 (PHYOX2) and 2018-003099-10 (PHYOX3).</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1395-1411"},"PeriodicalIF":4.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12414044/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methodological Techniques Used in Machine Learning to Support Individualized Drug Dosing Regimens Based on Pharmacokinetic Data: A Scoping Review.","authors":"Janthima Methaneethorn, Khanita Duangchaemkarn, Brad Reisfeld, Sohaib Habiballah","doi":"10.1007/s40262-025-01547-8","DOIUrl":"10.1007/s40262-025-01547-8","url":null,"abstract":"<p><strong>Background and objective: </strong>Individualized drug dosing is a highly effective strategy for optimizing therapeutic outcomes, especially for drugs with high inter-individual variability. Population pharmacokinetic modeling is a widely used approach to characterize inter-individual variability in therapeutic drug monitoring. However, the development of population pharmacokinetic models is labor intensive and requires significant technical expertise. Machine learning (ML) represents a promising alternative for personalized drug dosing strategies. Despite numerous studies applying ML in this context, no previous work has comprehensively reviewed and compared their methodologies and predictive performance. This scoping review addresses this gap in the existing literature with the aim to examine the methodological approaches used in ML-based pharmacokinetic modeling for dose optimization.</p><p><strong>Methods: </strong>Five databases were systematically searched from their inception to May 2025. Studies comparing predictions of drug concentrations or pharmacokinetic parameters between ML and population pharmacokinetic models were included. Studies published in non-English language, reviews, protocols, or studies that did not employ ML models for individualized dose regimens or treatment plans were excluded.</p><p><strong>Results: </strong>Fifty-eight studies were included. We found that boosting-based models, tree-based models, instance-based, and regression-based models were the most commonly used ML approaches. Approximately 31% of the studies integrated ML with population pharmacokinetic models, while the remainder developed stand-alone ML models. Inconsistencies in reporting were evident, as only 60% of the studies detailed their feature selection methods. Model evaluation approaches also varied: 47% of ML models used internal test sets, while the remainder employed external datasets or mixed approaches. In terms of predictive accuracy, ML models performed comparably to or better than population pharmacokinetic models, especially for drugs with significant pharmacokinetic variability.</p><p><strong>Conclusions: </strong>This review identifies substantial heterogeneity in ML modeling approaches, feature selection, and model evaluation. To enhance the reproducibility and clinical applicability of ML models in individualized drug dosing, standardization in reporting and methodological practices is essential.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1295-1330"},"PeriodicalIF":4.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144854763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid Population Pharmacokinetic-Machine Learning Modeling to Predict Infliximab Pharmacokinetics in Pediatric and Young Adult Patients with Crohn's Disease.","authors":"Kei Irie, Phillip Minar, Jack Reifenberg, Brendan M Boyle, Joshua D Noe, Jeffrey S Hyams, Tomoyuki Mizuno","doi":"10.1007/s40262-025-01564-7","DOIUrl":"https://doi.org/10.1007/s40262-025-01564-7","url":null,"abstract":"<p><strong>Background and objective: </strong>Population pharmacokinetic (PK) model-based Bayesian estimation is widely used for dose individualization, particularly when sample availability is limited. However, its predictive accuracy can be compromised by factors such as misspecified prior information, intra-patient variability, and uncertainties in PK variations. In this study, we developed a hybrid approach that combines machine learning (ML) with population PK-based Bayesian methods to improve the prediction of infliximab concentrations in children with Crohn's disease.</p><p><strong>Methods: </strong>We calculated prediction errors between Bayesian-estimated and observed infliximab concentrations from 292 measurements across 93 patients. Incorporating clinical patient features, we explored various ML algorithms, including linear regression, random forest, support vector regression, neural networks, and XGBoost to correct the Bayesian-based prediction errors. The predictive performance of these ML models was assessed using root mean square error (RMSE) and mean prediction error (MPE) with 5-fold cross-validation.</p><p><strong>Results: </strong>For Bayesian estimation alone, the RMSE and MPE were 4.8 µg/mL and - 0.67 µg/mL, respectively. Among the ML algorithms, the XGBoost model demonstrated the best performance, achieving an RMSE of 3.78 ± 0.85 µg/mL and an MPE of - 0.03 ± 0.69 µg/mL in 5-fold cross-validation. The ML-corrected Bayesian estimation significantly reduced the absolute prediction error compared with Bayesian estimation alone.</p><p><strong>Conclusion: </strong>This hybrid population PK-ML approach provides a promising framework for improving the predictive performance of Bayesian estimation, with the potential for continuous learning from new clinical data to enhance dose individualization.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Preliminary Bronchodilation Effect on Aerosol Delivery from a Dry Powder Inhaler for Patients with Chronic Obstructive Pulmonary Disease with Suboptimal Peak Inspiratory Flow Rate.","authors":"Mohamed Ismail Hassan, Nabila Ibrahim Laz, Yasmin M Madney, Mohamed E A Abdelrahim, Hadeer S Harb","doi":"10.1007/s40262-025-01560-x","DOIUrl":"https://doi.org/10.1007/s40262-025-01560-x","url":null,"abstract":"<p><strong>Background: </strong>Suboptimal peak inspiratory flow rates (PIFR) are common in patients with chronic obstructive pulmonary disease (COPD), hindering effective medication dispersion and aerosol delivery. This study aimed to assess whether administering a preliminary bronchodilator dose via a pressurized metered-dose inhaler (pMDI) improves aerosol drug delivery via dry powder inhaler (DPI) in patients with COPD with suboptimal PIFR (< 60 L/min), compared with those with optimal PIFR (≥ 60 L/min).</p><p><strong>Methods: </strong>Overall, 24 patients with COPD were evaluated. PIFR was measured using the In-Check Dial^© G16, dividing patients into optimal and suboptimal groups. All patients received a 200 µg dose of salbutamol via Diskus^® DPI. Patients with COPD with suboptimal PIFR received two puffs (100 µg each) preceded by a preliminary salbutamol dose administered via pMDI^®. Urine salbutamol levels (USAL30) and salbutamol that was eluted from filters (SALF) were measured after 30 min to assess lung deposition through high-performance liquid chromatography (HPLC).</p><p><strong>Results: </strong>Patients with COPD with suboptimal PIFR without a preliminary dose had significantly lower USAL30 than the optimal group (4.99% versus 6.18%, p = 0.013). A preliminary dose improved USAL30 in the suboptimal group but did not reach statistical significance (5.45% versus 4.99%, p = 0.071).</p><p><strong>Conclusions: </strong>A significant difference in aerosol drug delivery was observed between optimal and suboptimal groups without a preliminary dose, suggesting that inhaler selection in patients with COPD may need to be individualized on the basis of inspiratory flow capability. Administering a preliminary dose of pMDI^® before using a DPI minimally affects the suboptimal inhalation through DPI.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunoglobulin G Receptors (FcγR), in Addition to Target-Antigen and Neonatal Fc Receptor (FcRn), Influence Rituximab Pharmacokinetics.","authors":"David Ternant, Olivier Le Tilly, Guillaume Cartron, Céline Desvignes, Amina Bensalem, Denis Mulleman, Theodora Bejan-Angoulvant, Valérie Gouilleux-Gruart, Gilles Paintaud","doi":"10.1007/s40262-025-01549-6","DOIUrl":"https://doi.org/10.1007/s40262-025-01549-6","url":null,"abstract":"<p><strong>Introduction: </strong>Rituximab, an anti-cluster of differentiation (CD)-20 monoclonal antibody, is used in the treatment of non-Hodgkin lymphoma (NHL), chronic lymphocytic leukemia, and rheumatoid arthritis. The pharmacokinetics of rituximab have been reported to be target mediated, but this alone may not fully explain the nonlinear decay of its concentrations over time.</p><p><strong>Objective: </strong>This study aimed to explore the potential role of immunoglobulin (Fc gamma receptor; FcγR) and neonatal Fc receptor (FcRn) in the disposition of rituximab.</p><p><strong>Methods: </strong>Concentration-time data from 108 patients with NHL, 118 with chronic lymphocytic leukemia, and 90 with rheumatoid arthritis were collected to refine a two-compartment population pharmacokinetic model with target-mediated drug disposition and irreversible binding approximation. Non-specific rituximab elimination was described using an intercompartment FcRn-mediated disposition model. Additionally, rituximab was assumed to bind to FcγR-expressing cells in both central and peripheral compartments; its disposition resulting from these mechanisms was described using quasi-steady-state interaction models.</p><p><strong>Results: </strong>The FcRn-mediated disposition model provided a satisfactory description of the data and was further improved by incorporating central and peripheral FcγR quasi-steady-state interaction models with steady-state dissociation constants estimated at 586 and 418 nM, respectively. CD19 cell count was related to target-mediated elimination rate constant (p = 1.7 × 10^-8) and inversely related to non-specific elimination (assessed by estimated FcRn amount, p = 2.1 × 10^-8). In patients with NHL, FcγR levels in central and peripheral compartments increased with baseline metabolic tumor volume (p = 7.0 × 10^-6 and p = 5.0 × 10^-28, respectively).</p><p><strong>Conclusion: </strong>The pharmacokinetics of rituximab are mediated both by Fab (target) interactions and by FcγR and FcRn interactions.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144854762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Tacrolimus Population Pharmacokinetic Model for Adult Allogeneic Hematopoietic Cell Transplant Recipients Provides Clinical Opportunities for Precision Dosing.","authors":"Tyler C Dunlap, Jing Zhu, Daniel L Weiner, Ryan M Kemper, Susanna C DeVane, Feiyun Ma, Veronica Nguyen, James M Coghill, Viet Dang, Tatjana Grgic, Katarzyna Jamieson, Jordan Miller, Jennifer Myers, Tejendra Patel, Marcie Riches, Jonathan S Serody, Morgan Trepte, Benjamin G Vincent, William A Wood, Jonathan R Ptachcinski, J Ryan Shaw, Eric Weimer, Paul M Armistead, Daniel J Crona","doi":"10.1007/s40262-025-01529-w","DOIUrl":"https://doi.org/10.1007/s40262-025-01529-w","url":null,"abstract":"<p><strong>Background: </strong>Tacrolimus is a cornerstone of acute graft-versus-host disease (aGVHD) prophylaxis in allogeneic hematopoietic cell transplant (allo-HCT) recipients. However, a narrow therapeutic index and high interindividual variability in pharmacokinetics (PK) make starting dose selection a major challenge in clinical practice.</p><p><strong>Methods: </strong>Data from two PK studies conducted at the University of North Carolina Medical Center (UNCMC) were used to develop an oral tacrolimus population pharmacokinetic (popPK) model specific to adult allo-HCT recipients. Monte Carlo simulations were performed to compare the likelihood of achieving the UNCMC institutional target trough concentration range (ITR) (5-10 ng/mL) on the day of transplant (D0) under the current institutional dosing protocol, dosing recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC), and model-derived dosing recommendations.</p><p><strong>Results: </strong>In total, 290 allo-HCT recipients contributed a total of 906 PK samples to the final analysis. A two-compartment popPK model adequately described the PK data. Population typical values of apparent clearance (TVCL/F) for 70 kg individuals receiving reduced intensity conditioning were 0.33 L/h/kg for CYP3A5 poor metabolizers (PMs) and 0.70 L/h/kg for intermediate and normal metabolizers (IMs and NMs). The probability of the population-level average D0 trough concentration being within the UNCMC ITR under the current UNCMC weight-based dosing protocol, CPIC-based, and model-derived dosing strategies were estimated to be 37%, 45%, and 76%, respectively. CYP3A5 IMs and NMs were predicted to require a 100% dose increase relative to CYP3A5 PMs.</p><p><strong>Conclusions: </strong>We propose a new oral tacrolimus dosing strategy for adult allo-HCT recipients, which suggests the current weight-based dosing paradigm is insufficient. This new strategy includes CYP3A5 metabolizer phenotypes and conditioning regimen intensity, and could increase the percentage of allo-HCT recipients achieving target concentrations on D0.</p><p><strong>Clinical trial registration number: </strong>Clinicaltrials.gov NCT04645667.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144820705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rifampicin Exposure in Tuberculosis Patients with Comorbidities in Sub-Saharan Africa: Prioritising Populations for Treatment-A Systematic Review and Meta-analysis.","authors":"Bibie Said, Yuan Pétermann, Patrick Howlett, Monia Guidi, Yann Thoma, Violet Dismas Kajogoo, Margaretha Sariko, Scott K Heysell, Jan-Willem Alffenaar, Emmanuel Mpolya, Stellah Mpagama","doi":"10.1007/s40262-025-01537-w","DOIUrl":"10.1007/s40262-025-01537-w","url":null,"abstract":"<p><strong>Background and objectives: </strong>Emerging evidence suggests that comorbidities like human immunodeficiency virus (HIV) infection, diabetes mellitus (DM), and malnutrition in tuberculosis (TB) patients can alter drug concentrations, thereby affecting the treatment outcomes. For these populations, personalised strategies such as therapeutic drug monitoring (TDM) may be essential. We investigated the variations of drug levels within comorbid populations and analysed the differences in patterns observed between sub-Saharan Africa (SSA) and non-SSA regions.</p><p><strong>Methods: </strong>We performed a systematic review and meta-analysis of rifampicin drug pharmacokinetics (PK) through searches of major databases from 1980 to December 2023. A random-effects meta-analysis model using R-studio version 4.3.2 was conducted to estimate pooled serum rifampicin exposure (area under the concentration-time curve [AUC], and peak maximum concentration [C_max]) between patients with TB-HIV infection, and TB-DM.</p><p><strong>Results: </strong>From 3300 articles screened, 24 studies met inclusion criteria, contributing 33 comorbidity subgroups for meta-analysis. In SSA, 14 subgroups assessed rifampicin PK in TB-HIV, 1 in TB-DM, and none in TB-malnutrition. The pooled mean C_max was below the recommended range (8-24 mg/L) for all subgroups. For TB-HIV, the pooled C_max was 5.59 mg/L, 95% CI (4.59-6.59), I² = 97% for SSA populations and 5.59 mg/L, 95% CI (3.65; 6.59) for non-SSA populations. The C_max for TB-DM in SSA (9.60 ± 4.4 mg/L) exceeded non-SSA (4.27 mg/L, 95% CI [2.77-5.76]). The lowest AUC was in TB-HIV (SSA, 29.09 mg/L h, 95% CI [21.06; 37.13, I² = 91%]). High variability and heterogeneity (I² >90%) were observed, with most studies (20/23) showing low bias.</p><p><strong>Conclusion: </strong>Our results emphasise the need for individualised dosing and targeted TDM implementation among TB-HIV and TB-DM populations on rifampicin in SSA. Although all populations exhibited low C_max levels, TB-HIV populations may be prioritised as AUC levels were lowest. In clinical settings in SSA, C_max-based TDM is more practical, but AUC can be used in treatment where feasible.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1149-1163"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144552431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacokinetics of Binimetinib in Participants with Hepatic Impairment.","authors":"Joseph Piscitelli, Erik Hahn, Lance Wollenberg, Renae Chavira, Laurence Del Frari, Micaela B Reddy","doi":"10.1007/s40262-025-01509-0","DOIUrl":"10.1007/s40262-025-01509-0","url":null,"abstract":"<p><strong>Background and objective: </strong>Binimetinib is approved for multiple indications at a therapeutic dose of 45 mg twice a day (BID), in combination with encorafenib. A clinical hepatic impairment (HI) study was designed to evaluate the pharmacokinetics (PK), safety, and tolerability of a single oral dose of binimetinib in participants with mild, moderate, and severe HI compared with demographically matched healthy participants with respect to age, gender, and body weight.</p><p><strong>Methods: </strong>Participants were enrolled according to National Cancer Institute (NCI) classification criteria for hepatic function based on their total bilirubin and aspartate aminotransferase levels at screening. Participants enrolled into Group 1 (normal hepatic function) were matched to participants enrolled into Groups 2, 3, and 4 (mild, moderate, and severe HI, respectively) with respect to age, gender, and body weight. Dose-normalized PK parameters were evaluated because of a difference in doses for the severe HI group compared to the other groups, with the dose reduction due to the increased exposures observed in the moderate HI group.</p><p><strong>Results: </strong>Among 27 PK evaluable participants, changes in binimetinib dose-normalized PK parameters C_max/D and AUC_inf/D were minimal in participants with mild HI compared to the normal hepatic function group. Both the moderate and severe HI groups had significant changes as AUC_inf/D increased by 81% and 111%, respectively, compared to the normal hepatic function group. Unbound AUC_last/D for the moderate and severe HI groups increased by 280% and 248% compared to the normal hepatic function group, respectively.</p><p><strong>Conclusion: </strong>Based on these findings on total and unbound exposures, dose reductions are recommended for binimetinib in cancer patients with moderate and severe HI.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov NCT02050815, registered 29 January 2014.</p>","PeriodicalId":10405,"journal":{"name":"Clinical Pharmacokinetics","volume":" ","pages":"1217-1230"},"PeriodicalIF":4.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263732/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144474138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}