Clinical Pharmacokinetics最新文献

Background and objective: Targeted liposomal doxorubicin (TLD-1) is a novel PEGylated liposomal doxorubicin (PLD) with optimized formulation characteristics, developed to improve the benefit-risk profile of PLD. This randomized intrapatient crossover amendment to the phase 1 SAKK 65/16 trial (NCT03387917) compared the pharmacokinetics (PK) of TLD-1 and Caelyx™ and included a pooled analysis of safety and preliminary antitumor activity at the recommended phase 2 dose (RP2D).

Methods: Patients with advanced breast or platinum-resistant ovarian cancer in the comparative PK part were randomized to receive TLD-1 in cycle 1 and Caelyx™ in cycle 2, or vice versa, followed by TLD-1 thereafter. Both formulations were administered intravenously at 40 mg/m² and PK was assessed using non-compartmental analysis. Safety and antitumor activity were analyzed across 23 patients treated with TLD-1 at the RP2D, including 13 from the comparative PK part and 10 from the published dose-escalation part.

Results: In 10 evaluable patients from the comparative PK part, TLD-1 showed higher encapsulated doxorubicin exposure (AUC_0-inf: 3222 vs 2139 mg·h/L) and longer median half-life (118 vs 70 h) than Caelyx™. Severe treatment-related events occurred in 43% of patients (10/23) in the full RP2D cohort, most commonly grade 3 palmar-plantar erythrodysesthesia, oral mucositis, and anemia (2 patients each). The investigator-assessed objective response rate was 8.7% (2/23), with partial responses in patients with breast cancer.

Conclusions: Targeted liposomal doxorubicin demonstrated prolonged systemic circulation and low variability in liposomal drug release, likely due to its formulation characteristics. At 40 mg/m² every 3 weeks, TLD-1 was well tolerated and showed modest preliminary antitumor activity in advanced breast cancer.

Clinicaltrials:

Gov identifier: NCT03387917, registered 2017-11-21.

Background and objective: Population pharmacokinetic (popPK) models in pediatric patients are essential to optimize dosing and ensure therapeutic efficacy. However, study designs are often not fully optimized, leaving room to improve efficiency, which is an important goal in this population, where patients are limited and resources scarce. The aim of the present work is to optimize study designs for the development of popPK models for teicoplanin, piperacillin and meropenem in pediatric patients, with or without continuous kidney replacement therapy (CKRT), to achieve greater model precision while reducing patient burden and economic cost.

Methods: Methodology based on the optimization of the Fisher information matrix (FIM) was followed, using the $DESIGN option in NONMEM 7.5. A previously developed model was selected for each of the antibiotics. The number of subjects in the optimized designs was fixed to 28 patients (14 with and 14 without CKRT). It was assumed that only plasma samples were extracted from patients without CKRT, while prefilter, postfilter, and effluent samples could be extracted simultaneously from patients undergoing CKRT. Sensitivity to different proportions of patients with and without CKRT was tested. The optimized designs were evaluated through simulation and re-estimation procedures, including the impact of covariates.

Results: The number of sampling times per individual needed to achieve precise parameter estimates was 3 in teicoplanin, 4 in piperacillin, and 6 in meropenem. The optimized designs reduced the total number of samples per patient by 25, 51, and 21% for teicoplanin, piperacillin, and meropenem, respectively, compared with the original studies used in the previous studies. The resulting samples were taken during 0-40 h from the beginning of the study in teicoplanin and piperacillin, while in the case of meropenem optimal sampling times went between 0-64 h. The optimized designs remained robust under different proportions of patients with and without CKRT and under different covariate values.

Conclusions: This work emphasizes the importance of optimizing study designs to improve accuracy and precision in the model parameters while reducing the number of samples needed. This is a relevant advantage especially when dealing with critically ill pediatric patients.

Objectives: To develop and validate a physiologically based pharmacokinetic (PBPK) population model for the Chinese obese population.

Methods: A Chinese adult population database was established in PK-Sim through recalibration of the East Asian population database, using newly collected anatomical and physiological data from Chinese adults. All three drugs (dexmedetomidine, omeprazole, and propofol) possessing Chinese obese population PK data were selected, with their PBPK models then developed and validated using matched clinical data. These models with the fixed drug-specific parameters were applied to the Chinese adult database to simulate drug concentrations, with results compared with the built-in East Asian database. Then, physiological parameters were adjusted using real-world and literature data from Chinese patients with obesity to establish a Chinese obese adult database. Similarly, drug concentrations in this population were simulated and compared with the simulation results based on the published White obese population database.

Results: The predicted C_max and AUC_last values were within 0.5-2 fold of the observed values, demonstrating all drug models were validated. The Chinese adult database showed superior accuracy to the East Asian database (90% versus 75% of AUC_last and 80% versus 70% of C_max within 0.8-1.25 fold). Similarly, the Chinese obese database outperformed the White obese database (83% versus 33% for AUC_last and 33% versus 0% for C_max within 0.8-1.25 fold).

Conclusions: The validated drug models, combined with the Chinese adult and obese adult databases, reliably predicted drug concentrations in Chinese adults and adults with obesity, outperforming the East Asian population database and White obese population database.

Background: Therapeutic drug monitoring (TDM) is a tool used for dose optimization to achieve therapeutic concentrations associated with improved outcomes. However, evidence supporting its benefits for tuberculosis (TB) treatment remains limited. This scoping review evaluated clinical studies on TDM and its impact on TB treatment outcomes.

Methods: A scoping review was performed using a systematic search in PubMed, Embase, Web of Science, ClinicalTrials.gov, and the World Health Organization (WHO) Clinical Trials Registry for interventional and observational studies published until 3 May 2025. We included studies evaluating TDM in adults or children treated for drug-susceptible or drug-resistant TB at any setting worldwide, which reported treatment outcomes, adverse events, or clinical/microbiological surrogate markers. The PRISMA guidelines for scoping reviews were followed to report the findings.

Results: Of the 5820 studies screened by title and abstract, 31 studies from 10 countries were eligible for inclusion in this review. No published clinical trials on the implementation of TDM were identified, although two are currently ongoing. Overall, compared with the non-TDM group, TDM was associated with faster culture conversion (mean 34 versus 49 days), shorter treatment duration (mean 32 versus 36 weeks) and fewer adverse events. Although all included studies reported high treatment success rates (ranging from 67% to 100%), no statistically significant differences were observed in end-of-treatment outcomes between TDM and non-TDM groups. Dose adjustments guided by TDM were recommended by all included studies, despite variability in results.

Conclusions: Observational data suggest that TDM in TB treatment was associated with improved effectiveness and fewer adverse events. However, further investigation through well-controlled studies is needed to minimize potential bias and justify its routine use.

Background: The euglycemic clamp technique is a standard method for assessing the pharmacokinetics (PK) and pharmacodynamics (PD) of insulin biosimilars compared to their reference products. Despite similar pharmacokinetic profiles, differences in the pharmacodynamic profiles between a basal insulin biosimilar and its reference product are not uncommon. This study aimed to identify potential factors contributing to this phenomenon.

Methods: Data were collected from euglycemic clamp studies comparing the PK/PD profiles of an insulin degludec biosimilar (BioIDeg) and the reference product, Tresiba. The ratio of the area under the curve of IDeg from 0 to 24 h (AUC_IDeg,0-24h) for BioIDeg to Tresiba was calculated. Subjects with an AUC_IDeg,0-24h ratio of 0.9 to 1.1 were enrolled and categorized based on the AUC_GIR,0-24h ratio (Group A: AUC_GIR,0-24h ratio < 0.80 or > 1.25; Group B: 0.80 ≤ AUC_GIR,0-24h ratio ≤ 1.25). Differences between groups and treatments were analyzed.

Results: Fifty-eight healthy subjects were included, with 20 in group A and 38 in group B. Significant differences were found in target blood glucose (BG), basal C-peptide, AUC_IDeg,0-12h, AUC_IDeg,0-24h, and target BG variations. Logistic regression analysis identified variations in target BG (standardized odds ratio 1.384, P=0.038) as an independent factor.

Conclusion: Variations in target BG might contribute to PD variability of long-acting insulin preparations in euglycemic clamp settings in healthy individuals.

Background: Oxcarbazepine (OXZ) is an antiepileptic drug whose pharmacological effect is primarily mediated by its active metabolite, 10-monohydroxy derivative (MHD). OXZ is approved for use in adults and children older than 2 years with an age- and body weight-tiered dosing recommendation, but dosing guidance for children with obesity is lacking.

Objective: This work aimed to assess the dosing requirements of OXZ in children with obesity to support label extension.

Methods: Two multicenter studies (NCT01431326 and NCT02993861) were conducted in patients receiving standard-of-care OXZ therapy. Participants ≥ 2 years of age with a body mass index ≥ 95th percentile were classified as obese. Plasma concentrations were measured by a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) assay. Nonlinear mixed effects modeling was performed using NONMEM 7.4 to characterize the population pharmacokinetics of OXZ and MHD simultaneously. Simulations were performed to compare MHD systemic exposure in children ≥ 2 years of age with and without obesity.

Results: One hundred study participants with a median (range) age of 9 years (44 days-20.90 years) contributed 425 plasma concentrations of OXZ (n = 212) and MHD (n = 213). Fifty-two percent of the participants had obesity. A one-compartment joint parent-metabolite model with linear input-output and bi-directional transformation between OXZ and MHD best characterized the pharmacokinetics. Body size was the only covariate affecting pharmacokinetics, and a fat-free mass-based metric termed pharmacokinetic weight (PKWT) best characterized that effect allometrically. Simulation results revealed that the current dosing regimen of OXZ can produce comparable exposure of MHD in children ≥ 2 years of age with and without obesity.

Conclusion: A model-informed analysis confirms that the current pediatric dosing regimen of OXZ applies to children in general, regardless of their obesity status.

Background and objective: Achieving optimal antibacterial dosing in critically ill patients is challenging owing to the pathophysiological changes that alter drug pharmacokinetics. Extracorporeal membrane oxygenation (ECMO) further complicates pharmacokinetics, hypothesized to act as another pharmacokinetic compartment influencing drug concentrations. Ensuring therapeutic antibacterial concentrations is crucial to prevent treatment failure and resistance. This systematic review aimed to identify and evaluate published population pharmacokinetic studies of antibacterials in critically ill adult ECMO patients.

Methods: A systematic search of PubMed, Embase, and Cochrane databases was conducted from database inception to March 2025. Studies were included if they were population pharmacokinetic analyses of antibacterial agents in adult (aged ≥ 18 years) ECMO patients; non-compartmental analyses and non-antibacterial agents were excluded. Data on study characteristics, patient demographics, ECMO parameters, pharmacokinetic models, and covariates were extracted.

Results: The search yielded 31 eligible population pharmacokinetic studies. Most studies indicated that ECMO-specific variables (mode, flow rate, oxygenator type) did not significantly influence the pharmacokinetics of the majority of antibacterials. Instead, pharmacokinetic variability was primarily driven by critical illness-related factors, notably renal function and presence of renal replacement therapy. Dosing recommendations frequently highlighted the need for individualized therapy and therapeutic drug monitoring.

Conclusions: Our findings indicate that ECMO itself does not consistently alter the pharmacokinetics of most antibacterials in critically ill adult patients. Observed pharmacokinetic variability and subsequent dosing recommendations are primarily attributable to critical illness factors. Therapeutic drug monitoring is recommended to optimize exposure but minimize toxicity. Further prospective studies with standardized reporting of covariates and clinical endpoints are needed to enhance the evidence base.

Clinical trial registration: PROSPERO Registration and date: CRD420251165914 (15 October, 2025).

Background and objective: Propofol is commonly used in critically ill patients on extracorporeal membrane oxygenation (ECMO). Although ECMO may theoretically affect drug pharmacokinetics (PK) through various mechanisms, data on propofol PK in this context remain scarce, with only one small recent study available. Our aim was to assess the impact of ECMO on propofol PK in a larger cohort.

Methods: We conducted a prospective, bicentric observational PK study in critically ill patients with and without ECMO (controls). Critically ill adults receiving a continuous infusion of propofol were eligible for inclusion. Controls were selected to ensure similarity with ECMO patients. We collected a maximum of eight samples per patient over 9 h. We analysed plasma samples using a high-performance liquid chromatography coupled to tandem mass spectrometry validated method. We developed a population pharmacokinetic (popPK) model using a classical stepwise approach with nonlinear mixed effects modelling software.

Results: A total of 40 patients, 20 with and 20 without ECMO, contributed 300 samples. A two-compartment model best described the data, with body weight affecting clearance. ECMO had no substantial impact on propofol PK. The final popPK model parameter estimates with between-subject variability were as follows: clearance 68 L/h (34%), intercompartmental clearance 26 L/h, and central and peripheral volumes of distribution 1.2 L/kg (230%) and 1.4 L/kg, respectively. A proportional error model best described the residual unexplained variability (13%).

Conclusions: Our popPK analysis shows that propofol PK does not differ between critically ill patients with and without ECMO and confirms a high PK variability in this population.