Search Results (54)

The aim of our study was to investigate the role of ABCB1 polymorphism in the pharmacokinetics of carbamazepine (CBZ) in children. The study enrolled 47 Serbian pediatric epileptic patients on CBZ treatment. Genotyping for ABCB1 1236C<T (rs1128503), 2677G<A/T (rs2032582) and 3435C<T (rs1045642) was carried out using the TaqMan method. Steady-state CBZ serum concentrations were available from our previous study, determined by high pressure liquid chromatography (HPLC). The NONMEM software and one-compartment model were used for pharmacokinetic analysis. ABCB1 1236C<T, 2677G<A/T and 3435C<T variations were found at the frequencies of 47.9%, 48.9% and 52.1%, respectively. The equation that described population clearance (CL) was CL (L/h) = 0.175 + 0.0403 × SEX + 0.0332 × ABCB1 + 0.0176 × CYP1A2 + 0.000151 × DD where SEX has a value of 1 if male and 0 if female, ABCB1 has a value of 1 if C-G-C/T-T-T and 0 if any other ABCB1 diplotype, CYP1A2 has a value of 1 if −163A/A and 0 if −163C/C or C/A, and DD is the total CBZ daily dose (mg/day). The presence of the ABCB1 1236T-2677T-3435T haplotype is associated with an increased clearance of CBZ in pediatric epileptic patients. Full article

Background/Objectives: Several population pharmacokinetic models of vedolizumab (VDZ) are available for inflammatory bowel disease (IBD) patients. However, their predictive performance in real-world clinical settings remains unknown. This study aims to externally evaluate the published VDZ pharmacokinetic models, focusing on their predictive performance and simulation-based clinical applicability. Methods: A literature search was conducted through PubMed to identify VDZ population pharmacokinetic models. A total of 114 VDZ concentrations from 106 IBD patients treated at the University Medical Center “Zvezdara”, Republic of Serbia, served as the external evaluation cohort. The predictive performance of the models was assessed using prediction- and simulation-based diagnostics. Furthermore, the models were utilized for Monte Carlo simulations to generate concentration–time profiles based on 24 covariate combinations specified within the models. Results: Four published pharmacokinetic models of VDZ were included in the evaluation. Using the external dataset, the median prediction error (MDPE) ranged from 13.82% to 25.57%, while the median absolute prediction error (MAPE) varied between 41.64% and 47.56%. None of the models fully met the combined criteria in the prediction-based diagnostics. However, in simulation-based diagnostics, pvcVPC showed satisfactory results, despite wide prediction intervals. Analysis of NPDE revealed that only the models by Rosario et al. and Okamoto et al. fulfilled the evaluation criteria. Simulation analysis further demonstrated that the median VDZ concentration remains above 12 μg/mL at week 22 during maintenance treatment for approximately 45–60% of patients with the best-case covariate combinations and an 8-week dosing frequency. Conclusions: None of the published models satisfied the combined criteria (MDPE, MAPE, percentages of prediction error within ±20% and ±30%), rendering them unsuitable for a priori predictions. However, two models demonstrated better suitability for simulation-based applications. Full article

Background/Objectives: Vedolizumab (VDZ) is approved in the treatment of patients with moderate to severe ulcerative colitis (UC) or Crohn’s disease (CD). VDZ exhibits considerable variability in its pharmacokinetic (PK) profile, and its exposure-response relationship is not yet fully understood. The aim was to investigate the variability in VDZ trough levels and PK parameters, to assess the relationship between VDZ PK and biochemical response, as well as clinical and endoscopic outcomes. Methods: We included 61 UC and 45 CD patients. Patients’ data and trough VDZ concentrations were retrospectively obtained. Population PK analysis was performed using non-linear mixed-effects modelling with NONMEM (version 7.5). Graphs and statistical analyses were performed using R (version 4.1.3). Results: In total, 116 trough VDZ concentrations from 106 patients were described by a two-compartment model. For a typical patient, clearance (CL) was estimated at 0.159 L/day, while in patients previously treated with anti-TNFα agents, VDZ CL increased by 26.4% on average. In univariate binary logistic regression, VDZ trough concentration was not statistically significant predictor of remission, whereas CL was. Moreover, combined CL and faecal calprotectin (FCP) were a statistically significant predictors of remission. The hazard ratio (HR) for CL above 0.1886 L/day was 0.35 (p = 0.05) and for FCP below 250 µg/g was 2.66 (p = 0.02) in a time-to-event analysis. Conclusions: Our population PK model incorporates the effect of prior anti-TNFα agents on CL, suggesting its association with more severe forms of IBD. VDZ CL emerged as a more robust and clinically relevant predictor of remission in IBD patients than trough concentration. Full article

Methotrexate (MTX), which presents high inter-individual variability, is part of the Brazilian Osteosarcoma Treatment Group (BOTG) protocol. This work aimed to develop a MTX population pharmacokinetic model (POPPK) for Brazilian children with osteosarcoma (OS) following the BOTG protocol to guide rescue therapy and avoid toxicity. The model was developed in NONMEM 7.4 (Icon^®) using retrospective sparse data from MTX therapeutic drug monitoring of children attending a southern Brazilian public reference hospital. Data were described by a two-compartment model using 216 MTX cycles from 32 patients (5–18 y.o.) with OS who received 12 g/m² dose/cycle. To explain inter-individual and inter-occasion variability in clearance and peripheral volume, covariates from demographic and biochemical data were evaluated. Serum creatinine was a significant covariate of MTX clearance (14.8 L/h), and the body surface area (BSA) was significant for central compartment volume (82.5 L). Inter-compartmental clearance and volume of peripheral compartment were 0.178 L/h and 5.72 L, respectively. The model adequately describes MTX exposure in Brazilian children with OS. Successful simulations were performed to predict MTX concentrations in pediatric patients above five years old with acute kidney injury and anticipate rescue therapy adjustments. Full article

Aims: The pharmacokinetic (PK) profiles of voriconazole in intensive care unit (ICU) patients differ from that in other patients. We aimed to develop a population pharmacokinetic (PopPK) model to evaluate the effects of using extracorporeal membrane oxygenation (ECMO) and continuous renal replacement therapy (CRRT) and those of various biological covariates on the voriconazole PK profile. Methods: Modeling analyses of the PK parameters were conducted using the nonlinear mixed-effects modeling method (NONMEM) with a two-compartment model. Monte Carlo simulations (MCSs) were performed to observe the probability of target attainment (PTA) when receiving CRRT or not under different dosage regimens, different stratifications of quick C-reactive protein (qCRP), and different minimum inhibitory concentration (MIC) ranges. Results: A total of 408 critically ill patients with 746 voriconazole concentration–time data points were included in this study. A two-compartment population PK model with qCRP, CRRT, creatinine clearance rate (CL_CR), platelets (PLT), and prothrombin time (PT) as fixed effects was developed using the NONMEM. Conclusions: We found that qCRP, CRRT, CL_CR, PLT, and PT affected the voriconazole clearance. The most commonly used clinical regimen of 200 mg q12h was sufficient for the most common sensitive pathogens (MIC ≤ 0.25 mg/L), regardless of whether CRRT was performed and the level of qCRP. When the MIC was 0.5 mg/L, 200 mg q12h was insufficient only when the qCRP was <40 mg/L and CRRT was performed. When the MIC was ≥2 mg/L, a dose of 300 mg q12h could not achieve ≥ 90% PTA, necessitating the evaluation of a higher dose. Full article

Zolpidem is a widely prescribed hypnotic Z-drug used to treat short-term insomnia. However, a growing number of individuals intentionally overdose on these drugs. This study aimed to develop a predictive tool for physicians to assess patients with zolpidem overdose. A population pharmacokinetic (PK) model was established using digitized data obtained from twenty-three healthy volunteers after a single oral administration of zolpidem. Based on the final PK model, a web application was developed using open-source R packages such as rxode2, nonmem2rx, and shiny. The final model was a one-compartment model with first-order absorption and elimination with PK parameters, including clearance (CL, 16.9 L/h), absorption rate constant (K_a, 5.41 h⁻¹), volume of distribution (V_d, 61.7 L), and lag time (ALAG, 0.394 h). Using the established population PK model in the current study, we developed a web application that enables users to simulate plasma zolpidem concentrations and visualize their profiles. This user-friendly web application may provide essential clinical information to physicians, ultimately helping in the management of patients with zolpidem intoxication. Full article

Clopidogrel (CLO), a pro-drug for preventing thrombotic events, undergoes rapid absorption and extensive metabolism, with approximately 85–90% converted to an inactive carboxylic acid metabolite (CLO-CA) and the remaining to an active thiol (CLO-TH). Few pharmacokinetic models for the drug and its metabolites exist, with most focusing on CLO-TH. Although CLO-CA is inactive, its predominant (compared to its parent drug and metabolites) presence in plasma underscores the importance of characterizing its formation and pharmacokinetic profile. This study aimed to characterize the process of the absorption of CLO and its conversion to CLO-CA via developing a population pharmacokinetic model. Individual participants’ data from two bioequivalence studies were utilized. Extensive blood samples were collected at predetermined intervals, including 841 concentrations of CLO and 1149 of CLO-CA. A nonlinear, mixed-effects modelling approach using NONMEM^® software (v 7.5) was applied. A one-compartment model was chosen for CLO, while a two-compartment proved optimal for CLO-CA. Absorption from the depot compartment was modeled via two transit compartments, incorporating transit rate constants (K_tr). A semi-physiological model explained the first-pass effect of CLO, integrating a liver compartment. The estimated mean transit times (MTTs) for the studies were 0.470 and 0.410 h, respectively. The relative bioavailability for each study’s generic medicine compared to the reference were 1.08 and 0.960, respectively. Based on the estimated parameters, the fractions metabolized to inactive metabolites (F_iaM_st1 and F_iaM_st2) were determined to be 87.27% and 86.87% for the two studies, respectively. The appropriateness of the final model was confirmed. Our model offers a robust framework for elucidating the pharmacokinetic profiles of CLO and CLO-CA. Full article

This study aimed to characterize the impact of extracorporeal membrane oxygenation (ECMO) on the pharmacokinetics (PK) of meropenem in neonates and children and to provide recommendations for meropenem dosing in this specific population of patients. Therapeutic drug monitoring (152 meropenem plasma concentrations) data from 45 patients (38 received ECMO) with a body weight (BW) of 7.88 (3.62–11.97) kg (median (interquartile range)) and postnatal age of 3 (0–465) days were collected. The population PK analysis was performed using NONMEM V7.3.0. Monte Carlo simulations were performed to assess the probability of target achievement (PTA) for 40% of time the free drug remained above the minimum inhibitory concentration (fT > MIC) and 100% fT > MIC. BW was found to be a significant covariate for the volume of distribution (Vd) and clearance (CL). Additionally, continuous renal replacement therapy (CRRT) was associated with a two-fold increase in Vd. In the final model, the CL and Vd for a typical patient with a median BW of 7.88 kg that was off CRRT were 1.09 L/h (RSE = 8%) and 3.98 L (14%), respectively. ECMO did not affect meropenem PK, while superimposed CRRT significantly increased Vd. We concluded that current dosing regimens provide acceptably high PTA for MIC ≤ 4 mg/L for 40% fT > MIC, but individual dose adjustments are needed for 100% fT > MIC. Full article

Bepotastine, a second-generation antihistamine for allergic rhinitis and urticaria, is widely used in all age groups but lacks appropriate dosing guidelines for pediatric patients, leading to off-label prescriptions. We conducted this study to propose an optimal dosing regimen for pediatric patients based on population pharmacokinetic (popPK) and physiologically based pharmacokinetic (PBPK) models using data from two previous trials. A popPK model was built using NONMEM software. A one-compartment model with first-order absorption and absorption lag time described our data well, with body weight incorporated as the only covariate. A PBPK model was developed using PK-Sim software version 10, and the model well predicted the drug concentrations obtained from pediatric patients. Furthermore, the final PBPK model showed good concordance with the known properties of bepotastine. Appropriate pediatric doses for different weight and age groups were proposed based on the simulations. Discrepancies in recommended doses from the two models were likely due to the incorporation of age-dependent physiological factors in the PBPK model. In conclusion, our study is the first to suggest an optimal oral dosing regimen of bepotastine in pediatric patients using both approaches. This is expected to foster safer and more productive use of the drug. Full article

L-4-[(¹⁰B)]Boronophenylalanine (BPA) is an amino acid analogue with a boron-10 moiety. It is most widely used as a boron carrier in boron neutron capture therapy. In this study, a Bayesian predictive platform of blood boron concentration based on a BPA pharmacokinetic (PK) model was developed. This platform is user-friendly and can predict the individual boron PK and optimal time window for boron neutron capture therapy in a simple way. The present study aimed to establish a PK model of L-4-boronophenylalanine and develop a Bayesian predictive platform for blood boron PKs for user-friendly estimation of boron concentration during neutron irradiation of neutron capture therapy. Whole blood boron concentrations from seven previous reports were graphically extracted and analyzed using the nonlinear mixed-effects modeling (NONMEM) approach. Model robustness was assessed using nonparametric bootstrap and visual predictive check approaches. The visual predictive check indicated that the final PK model is able to adequately predict observed concentrations. The Shiny package was used to input real-time blood boron concentration data, and during the following irradiation session blood boron was estimated with an acceptably short calculation time for the determination of irradiation time. Finally, a user-friendly Bayesian estimation platform for BPA PKs was developed to optimize individualized therapy for patients undergoing BNCT. Full article

The aim of the study is to develop a population pharmacokinetic (PopPK) model and to investigate the influence of CYP3A5/CYP3A4 and ABCB1 single nucleotide polymorphisms (SNPs) on the Tacrolimus PK parameters after LCP-Tac formulation in stable adult renal transplant patients. The model was developed, using NONMEM v7.5, from full PK profiles from a clinical study (n = 30) and trough concentrations (C₀) from patient follow-up (n = 68). The PK profile of the LCP-Tac formulation was best described by a two-compartment model with linear elimination, parameterized in elimination (CL/F) and distributional (CL_D/F) clearances and central compartment (Vc/F) and peripheral compartment (Vp/F) distribution volumes. A time-lagged first-order absorption process was characterized using transit compartment models. According to the structural part of the base model, the LCP-Tac showed an absorption profile characterized by two transit compartments and a mean transit time of 3.02 h. Inter-individual variability was associated with CL/F, Vc/F, and Vp/F. Adding inter-occasion variability (IOV) on CL/F caused a statistically significant reduction in the model minimum objective function MOFV (p < 0.001). Genetic polymorphism of CYP3A5 and a cluster of CYP3A4/A5 SNPs statistically significantly influenced Tac CL/F. In conclusion, a PopPK model was successfully developed for LCP-Tac formulation in stable renal transplant patients. CYP3A4/A5 SNPs as a combined cluster including three different phenotypes (high, intermediate, and poor metabolizers) was the most powerful covariate to describe part of the inter-individual variability associated with apparent elimination clearance. Considering this covariate in the initial dose estimation and during the therapeutic drug monitoring (TDM) would probably optimize Tac exposure attainments. Full article

Background: Limited pharmacotherapy and the failure of conventional treatments in complex pathologies in children lead to increased off-label use of rituximab. We aimed to characterize the time course of CD19+ B lymphocytes (CD19+) under treatment with intravenous rituximab in children with neurologic and autoimmune diseases and to evaluate the impact of covariates (i.e., demographics, diagnosis and substitution between innovator and biosimilar product) on rituximab pharmacodynamics and disease activity. Methods: Pre- and post-drug infusion CD19+ in peripheral blood were prospectively registered. A population pharmacodynamic model describing the time course of CD19+ was developed with NONMEM v7.4. Simulations of three different rituximab regimens were performed to assess the impact on CD19+. Logistic regression analysis was performed to identify predictors of clinical response recorded through disease activity scores. Results: 281 measurements of CD19+ lymphocyte counts obtained from 63 children with neurologic (n = 36) and autoimmune (n = 27) diseases were available. The time course of CD19+ was described with a turn-over model in which the balance between synthesis and degradation rates is disrupted by rituximab, increasing the latter process. The model predicts half-lives (percent coefficient of variation, CV(%)) of rituximab and CD19+ of 11.6 days (17%) and 173.3 days (22%), respectively. No statistically significant effect was found between any of the studied covariates and model parameters (p > 0.05). Simulations of different regimens showed no clinically significant differences in terms of CD19+ repopulation times. A trend towards a lack of clinical response was observed in patients with lower CD19+ repopulation times and higher areas under the CD19+ versus time curve. Conclusions: Rituximab pharmacodynamics was described in a real-world setting in children suffering from autoimmune and neurologic diseases. Diagnosis, substitution between innovator rituximab and its biosimilars or type of regimen did not affect rituximab-induced depletion of CD19+ nor the clinical response in this cohort of patients. According to this study, rituximab frequency and dosage may be chosen based on clinical convenience or safety reasons without affecting CD19+ repopulation times. Further studies in larger populations are required to confirm these results. Full article

Perampanel is a promising antiepileptic drug (AED) for refractory epilepsy treatment due to its innovative mechanism of action. This study aimed to develop a population pharmacokinetic (PopPK) model to be further used in initial dose optimization of perampanel in patients diagnosed with refractory epilepsy. A total of seventy-two plasma concentrations of perampanel obtained from forty-four patients were analyzed through a population pharmacokinetic approach by means of nonlinear mixed effects modeling (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic profiles of perampanel. Interpatient variability (IPV) was entered on clearance (CL), while the residual error (RE) was modeled as proportional. The presence of enzyme-inducing AEDs (EIAEDs) and body mass index (BMI) were found as significant covariates for CL and volume of distribution (V), respectively. The mean (relative standard error) estimates for CL and V of the final model were 0.419 L/h (5.56%) and 29.50 (6.41%), respectively. IPV was 30.84% and the proportional RE was 6.44%. Internal validation demonstrated an acceptable predictive performance of the final model. A reliable population pharmacokinetic model was successfully developed, and it is the first enrolling real-life adults diagnosed with refractory epilepsy. Full article

Intranasal delivery is a non-invasive mode of administration, gaining popularity due to its potential for targeted delivery to the brain. The anatomic connection of the nasal cavity with the central nervous system (CNS) is based on two nerves: olfactory and trigeminal. Moreover, the high vasculature of the respiratory area enables systemic absorption avoiding possible hepatic metabolism. Due to these physiological peculiarities of the nasal cavity, compartmental modeling for nasal formulation is considered a demanding process. For this purpose, intravenous models have been proposed, based on the fast absorption from the olfactory nerve. However, most of the sophisticated approaches are required to describe the different absorption events occurring in the nasal cavity. Donepezil was recently formulated in the form of nasal film ensuring drug delivery in both bloodstream and the brain. In this work, a three-compartment model was first developed to describe donepezil oral brain and blood pharmacokinetics. Subsequently, using parameters estimated by this model, an intranasal model was developed dividing the administered dose into three fractions, corresponding to absorption directly to the bloodstream and brain, as well as indirectly to the brain expressed through transit compartments. Hence, the models of this study aim to describe the drug flow on both occasions and quantify the direct nose-to-brain and systemic distribution. Full article

Pharmacometrics and the utilization of population pharmacokinetics play an integral role in model-informed drug discovery and development (MIDD). Recently, there has been a growth in the application of deep learning approaches to aid in areas within MIDD. In this study, a deep learning model, LSTM-ANN, was developed to predict olanzapine drug concentrations from the CATIE study. A total of 1527 olanzapine drug concentrations from 523 individuals along with 11 patient-specific covariates were used in model development. The hyperparameters of the LSTM-ANN model were optimized through a Bayesian optimization algorithm. A population pharmacokinetic model using the NONMEM model was constructed as a reference to compare to the performance of the LSTM-ANN model. The RMSE of the LSTM-ANN model was 29.566 in the validation set, while the RMSE of the NONMEM model was 31.129. Permutation importance revealed that age, sex, and smoking were highly influential covariates in the LSTM-ANN model. The LSTM-ANN model showed potential in the application of drug concentration predictions as it was able to capture the relationships within a sparsely sampled pharmacokinetic dataset and perform comparably to the NONMEM model. Full article