Published Population Pharmacokinetic Research Articles

Development and application of a population pharmacokinetic model repository for caffeine dose tailoring in preterm infants

ABSTRACT Background Considerable interindividual variability for the pharmacokinetics of caffeine in preterm infants has been demonstrated, emphasizing the importance of personalized dosing. This study aimed to develop and apply a repository of currently published population pharmacokinetic (PopPK) models of caffeine in preterm infants to facilitate model-informed precision dosing (MIPD). Research design and methods Literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases. Relevant publications were screened, and their quality was assessed. PopPK models were reestablished to develop the model repository. Covariate effects were evaluated and the concentration–time profiles were simulated. An online simulation and calculation tool was developed as an instance. Results Twelve PopPK models were finally included in the repository. Preterm infants’ age and body size, especially the postnatal age and current weight, were identified as the most clinically critical covariates. Simulated blood concentration–time profiles across these models were comparable. Caffeine citrate-dose regimen should be adjusted according to the age and body size of preterm infants. The developed online tool can be used to facilitate clinical decision-making. Conclusions The first developed repository of PopPK models for caffeine in preterm infants has a wide range of potential applications in the MIPD of caffeine.

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C2h), as an indicator of safety and efficacy, are important for optimizing therapy. The objective of this study was to establish machine learning (ML) models to predict the C2h, that can be used for establishing an individualized dosing regimen in clinical practice. Published population pharmacokinetic (PopPK) models for adults were searched based on PubMed and ultimately four reliable models were selected for simulating individual C2h datasets under different conditions (demographics, genotype, ethnicity, etc.). Machine learning models were trained on simulated C2h obtained from the four PopPK models. Five different algorithms were used for ML model building to predict C2h. Real-world data were used for predictive performance evaluations. Virtual trials were used to compare ML-optimized doses with PopPK model-optimized doses. Categorical boosting (CatBoost) exhibited the highest prediction ability. Target C2h can be predicted using the ML model combined with the dosing regimen and three covariates (N-acetyltransferase 2 [NAT2] genotypes, weight and race [Asians and Africans]). Real-world data validation results showed that the ML model can achieve an overall prediction accuracy of 93.4%. Using the final ML model, the mean absolute prediction error value decreased by 45.7% relative to the average of PopPK models. Using the ML-optimized dosing regimen, the probability of target attainment increased by 43.7% relative to the PopPK model-optimized dosing regimens. Machine learning models were developed with great predictive performance, which can be used to determine the individualized initial dose of isoniazid in adult patients.

Pharmacokinetic Consideration of Venetoclax in Acute Myeloid Leukemia Patients: A Potential Candidate for TDM? A Short Communication.

Venetoclax (VNX)-based regimens have demonstrated significantly favorable outcomes in patients with acute myeloid leukemia (AML) and are now becoming the standard treatment. Tyrosine kinase inhibitors are administered at a fixed dose, irrespective of body surface area or weight. For such orally targeted therapies, real-world data have highlighted a larger pharmacokinetic (PK) interindividual variability (IIV) than expected. Even if VNX PKs have been well characterized and described in the literature, only 1 clinical trial-based PK study has been conducted in patients with AML. This study aimed to evaluate the PK of VNX in AML patients. We retrospectively analyzed all patients treated with a combination of VNX-azacitidine between January and July 2022 at our center, using at least 1 available VNX blood sample. Based on a previously published population PK model, individual PK parameters were estimated to evaluate the exposure and IIV. and Discussion. Twenty patients received VNX in combination with azacitidine, according to the PK data. A total of 93 plasma concentrations were collected. The dose of VNX was 400 mg, except in 7 patients who received concomitant posaconazole (VNX 70 mg). The patients' weight ranged from 49 kg to 108 kg (mean = 78 kg). Mean individual clearance was 13.5 ± 9.4 L/h with mean individual daily area under the concentration-time curves of 35.8 mg.h/L with significant IIV (coefficient of variation = 41.1%). Ten patients were still alive (8 in complete response), but all experienced at least 1 hematological toxicity of grade ≥ 3. Based on the observed large PK variability in the data from our real-world AML patients, the risk of drug interactions and the recommended fixed-dosage regimen of VNX therapeutic drug monitoring may be useful.

Association between busulfan exposure and survival in patients undergoing a CD34+ selected stem cell transplantation.

Busulfan is an alkylating drug routinely used in conditioning regimens for allogeneic hematopoietic cell transplantation (allo-HCT). A myeloablative conditioning regimen, including busulfan, is commonly used in patients undergoing T-cell depletion (TCD) and allo-HCT, but data on optimal busulfan pharmacokinetic (PK) exposure in this setting are limited. Between 2012 and 2019, busulfan PK was performed to target an area under the curve exposure between 55 and 66mg× h/L over 3days using a noncompartmental analysis model. We retrospectively re-estimated busulfan exposure following the published population PK (popPK) model (2021) and correlated it with outcomes. To define optimal exposure, univariable models were performed with P splines, wherein hazard ratio (HR) plots were drawn, and thresholds were found graphically as the points at which the confidence interval crossed 1. Cox proportional hazard and competing risk models were used for analyses. 176 patients were included, with a median age of 59 years (range, 2-71). Using the popPK model, the median cumulative busulfan exposure was 63.4mg× h/L (range, 46.3-90.7). The optimal threshold was at the upper limit of the lowest quartile (59.5mg× h/L). 5-year overall survival (OS) with busulfan exposure ≥59.5 vs <59.5mg× h/L was 67% (95%CI, 59-76) vs 40% (95%CI, 53-68), respectively (P= .02), and this association remained in a multivariate analyses (HR, 0.5; 95%CI, 0.29; 0.88; P= .02). In patients undergoing TCD allo-HCT, busulfan exposure is significantly associated with OS. The use of a published popPK model to optimize exposure may significantly improve the OS.

Establishment and Evaluation of a Parametric Population Pharmacokinetic Model Repository for Ganciclovir and Valganciclovir.

Ganciclovir and valganciclovir are used for prophylaxis and treatment of cytomegalovirus infection. However, there is great interindividual variability in ganciclovir's pharmacokinetics (PK), highlighting the importance of individualized dosing. To facilitate model-informed precision dosing (MIPD), this study aimed to establish a parametric model repository of ganciclovir and valganciclovir by summarizing existing population pharmacokinetic information and analyzing the sources of variability. (2) Methods: A total of four databases were searched for published population PK models. We replicated these models, evaluated the impact of covariates on clearance, calculated the probability of target attainment for each model based on a predetermined dosing regimen, and developed an area under the concentration-time curve (AUC) calculator using maximum a posteriori Bayesian estimation. (3) Results: A total of 16 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area) and renal function. The results show that 5 mg/kg/12 h of ganciclovir could make the AUC0-24h within 40-80 mg·h/L for 50.03% pediatrics but cause AUC0-24h exceeding the exposure thresholds for toxicity (120 mg·h/L) in 51.24% adults. (4) Conclusions: Dosing regimens of ganciclovir and valganciclovir should be adjusted according to body size and renal function. This model repository has a broad range of potential applications in MIPD.

Transferability of Published Population Pharmacokinetic Models for Apixaban and Rivaroxaban to Subjects with Obesity Treated for Venous Thromboembolism: A Systematic Review and External Evaluations.

Apixaban and rivaroxaban have first-line use for many patients needing anticoagulation for venous thromboembolism (VTE). The pharmacokinetics of these drugs in non-obese subjects have been extensively studied, and, while changes in pharmacokinetics have been documented in obese patients, data remain scarce for these anticoagulants. The aim of this study was to perform an external validation of published population pharmacokinetic (PPK) models of apixaban and rivaroxaban in a cohort of obese patients with VTE. A literature search was conducted in the PubMed/MEDLINE, Scopus, and Embase databases following the PRISMA statement. External validation was performed using MonolixSuite software, using prediction-based and simulation-based diagnostics. An external validation dataset from the university hospitals of Brest and Rennes, France, included 116 apixaban pharmacokinetic samples from 69 patients and 121 rivaroxaban samples from 81 patients. Five PPK models of apixaban and 16 models of rivaroxaban were included, according to the inclusion criteria of the study. Two of the apixaban PPK models presented acceptable performances, whereas no rivaroxaban PPK model did. This study identified two published models of apixaban applicable to apixaban in obese patients with VTE. However, none of the rivaroxaban models evaluated were applicable. Dedicated studies appear necessary to elucidate rivaroxaban pharmacokinetics in this population.

Effect of Predicted Fludarabine Lymphodepletion Exposure on Clinical Outcomes in Myeloma Patients Undergoing BCMA-CAR-T: An Exploratory Analysis from CARTITUDE-1

Background: BCMA-targeted chimeric antigen receptor-engineered (anti-BCMA CAR) T-cell therapy has demonstrated favorable clinical outcomes in relapsed and refractory multiple myeloma (RRMM). Lymphodepleting (LD) chemotherapy including fludarabine (Flu) is hypothesized to promote expansion and persistence of CAR-T cells. Flu exhibits wide pharmacokinetic (PK) variability, with increased exposure as calculated by population PK model correlating with improved outcomes after anti-CD19+ CAR-T (Fabrizio VA, Blood Advances, 2022 & Dekker L. et al, Blood Advances, 2022). Using clinical data from patients enrolled in the CARTITUDE-1 clinical trial (NCT03548207, N=97), a phase 1b/2 study assessing ciltacabtagene autoleucel (cilta-cel) in patients with RRMM, we hypothesized that the developed population PK model may predict outcomes after cilta-cel in myeloma. Methods: Patients in the trial received a single cilta-cel infusion 5 to 7 days after fludarabine 30 mg/m2 and cyclophosphamide 300 mg/m2 for 3 consecutive days. Patients were excluded if they received any LD other than Flu/Cy or had any missing data needed to predict Flu exposure. Predicted exposure (pAUC) of Flu was determined by applying a population approach where eGFR is a covariate for Flu clearance and body weight is a covariate for Flu clearance and volume of distribution (Langenhorst JB, Clinical Pharmacokinetics, 2019). Individual Flu PK profiles and exposure metrics (Cmax, Ctrough and AUC0-72h) were simulated for each patient and were correlated with anti-BCMA CAR-T kinetics and efficacy (IMWG response, PFS and OS). Pearson/Spearman correlation coefficient was used to estimate the association between Flu PK parameters and LD effect, reflected by endogenous T cell changes (prior to versus post-LD), and CAR-T kinetics. Parametric t-test was used as the primary analysis and Mann-Whitney as the sensitivity analysis to determine if Flu AUC was associated with whether the patient can achieve stringent complete response (sCR) or not. PFS and OS rates were compared between 2 patient groups stratified by dichotomized LD exposure (AUC above and below the median). Results: We first investigated if there was variability in the two significant covariates of Flu PK in our cohort- body weight and eGFR. The eGFR distribution indicated large variability (mean=94.2, CV%=33.5) with 50 (51.5%) patients having renal dysfunction (eGFR <90 ml/min/1.73m2). Body weight ranged from 39 to 125.6 kg. The Flu pAUC in the entire population varied by 3.1-fold and the median was found to be 19.4 mg x h/L (IQR, 16.7-21.4; Figure 1A). No apparent association between Flu pAUC and CAR-T expansion and persistence was observed. Predicted peak Flu concentration (p=0.052) and AUC (p=0.058) appear to be slightly higher in sCR patients than non-sCR patients with significant overlapping (Figure 1B). Kaplan-Meier plot of PFS/OS (data cutoff: approximately 12 months of the last patient after CAR-T infusion) suggested no apparent association with LD exposure (p= 0.093 and 0.4 respectively). Analysis is ongoing to determine if there is an association between Flu pAUC and CRS/ICANS with results to be presented at the conference. Conclusions: Although we did not measure Flu blood levels, we report for the first time the application of a previously published population PK model to simulate Flu exposure in a prospective cohort of myeloma patients undergoing anti-BCMA CAR-T therapy. Predicted peak Flu concentration and AUC appears to be slightly higher in sCR patients than non-sCR patients and there was no apparent correlation with CART kinetics or PFS/OS. Our data suggests a trend in Flu exposure predicting PFS but this needs to be further validated with additional data and analysis. Because the actual individual Flu exposure may deviate from the predicted population mean, a definitive analysis will require measurement of Flu blood levels prospectively with lymphodepletion to confirm potential relationships between Flu AUC, CART expansion & persistence, and CART clinical activity. Figure 1. Distribution of Model-predicted Flu AUC0-72h (A). Boxplots of Peak Flu Concentration and Flu pAUC (B) with Stringent Complete Response. Boxplot shows the minimum, 25th quartile, median, 75th quartile, and maximum of the data. Symbols represent individual simulated data points in (B). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Hydroxyurea Pharmacokinetics and Fetal Hemoglobin Response in Ugandan Children with Sickle Cell Anemia

Introduction Over 300,000 infants are born with sickle cell anemia (SCA) in Africa every year, and the under-5 mortality of this population is estimated to be 50-90% without treatment. Hydroxyurea is a safe, oral medication that decreases morbidity and mortality in SCA by increasing protective fetal hemoglobin (HbF) production and reducing inflammation. Hydroxyurea dosing to maximum tolerated dose (MTD) offers the optimal treatment with greatest laboratory responses and clinical benefits. Patients have variable hydroxyurea absorption and elimination rates, so the traditional approach to determining MTD is through incremental dose escalation to achieve mild myelosuppression and reduction in absolute neutrophil count (ANC). In the United States, pharmacokinetic (PK)-guided dosing of hydroxyurea for children with SCA has been shown to decrease time to MTD and to augment treatment responses, with most patients achieving over 30% HbF. Maximizing clinical benefits and minimizing logistical burdens of dosing hydroxyurea would be advantageous for areas with high SCA prevalence, but PK parameters of African children with SCA who might have higher rates of malnutrition, infections, and organ damage that affect drug absorption, distribution, and clearance are yet to be determined. Here we describe hydroxyurea PK exposure-response in Ugandan children with SCA from the Optimizing Hydroxyurea Therapy in Children with Sickle Cell Anemia In Malaria Endemic Areas: The NOHARM MTD Study (NOHARM MTD, NCT03128515). Methods NOHARM MTD was a randomized controlled trial that compared dosing strategies between hydroxyurea at fixed, weight-based dosing (~20 mg/kg/day) and dose escalation to MTD in children with SCA living in Uganda. NOHARM MTD participants underwent PK testing after 18 months of treatment. Children were administered their prescribed hydroxyurea dose in the morning at clinic, and blood was obtained by fingerstick using Mitra® microsampler devices after 20, 60, and 180 minutes. The microsampler devices were frozen at -80C in Uganda and then transported to Cincinnati Children's Hospital for analysis of hydroxyurea concentration via liquid chromatography with tandem mass spectrometry. Using our previously published population PK model, individual hydroxyurea exposures expressed as area-under-the-curve (AUC) were generated by Bayesian estimation using the PK modeling software NONMEM (Version 7.5, ICON Development Solutions, Ellicott City, USA). A hydroxyurea exposure-response analysis was completed with HbF% as the primary pharmacodynamic outcome. Results A total of 90 NOHARM MTD participants completed PK testing; samples from 12 were excluded from full analysis due to an elevated baseline concentration suggesting the participant already received the daily hydroxyurea dose before PK testing (9), supraphysiologic concentration (1), or mislabeling (2). PK profiles were analyzed for the remaining 78 participants (mean age 6.5 years, SD 0.9); of these, 41 were on fixed dose hydroxyurea and 37 were at MTD with mean doses of 18.7 mg/kg/day (SD 1.6) and 28.3 mg/kg/day (SD 4.3), respectively (Table). Those at MTD had a higher AUC with a significantly higher %HbF (mean 19% HbF on fixed dose vs 29% at MTD, p=0.0002) and lower ANC (mean 4.7 x109/L at fixed dose vs 3.2 at MTD, p=0.0045). Eighteen participants (23%) had malnutrition with a body mass index Z-score less than -1.0, and 12 (15%) participants had renal hyperfiltration with an estimated glomerular filtration rate over 150 mL/min/1.73m2; neither condition was associated with differences in AUC. Conclusion This study demonstrates the feasibility of collecting hydroxyurea PK data with timed, sparse sampling in Uganda, and the exposure-response analysis confirms that higher hydroxyurea exposure in Ugandan children with SCA is associated with greater induction of protective HbF and reduction in ANC. Malnutrition and glomerular hyperfiltration did not affect hydroxyurea exposure in this cohort. Further studies of PK-guided dosing to optimize response and time to response in this population are needed. Future directions include building capacity for local analysis of hydroxyurea concentrations using HPLC technology, real-time dose calculation via a PK model-informed algorithm, and prospective evaluation of PK-guided dosing. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Challenges associated with test dose pharmacokinetic predictions of high dose melphalan exposure in patients with multiple myeloma

AimTo evaluate the accuracy of melphalan test dose pharmacokinetic (PK) predictions of the subsequent high dose (HDM) area under the concentration-versus-time curve (AUC) and to identify sources of prediction error (PE).MethodsA prospective multicentre PK study was conducted in 40 myeloma patients of median age 60 (range:35–71) years using a 20 mg/m2 test dose administered 1–3 days prior to HDM (predominantly 180 mg/m2). PK data were collected post the test and high doses to compare predicted versus actual AUCs determined using the trapezoidal rule. Test and high dose infusion concentration, volume and duration and the time from preparation to infusion were compared using the paired Wilcoxin rank sign test. The impact of Melphalan administration parameters on PE was evaluated using the Mann–Whitney test. The predictive capacity of a previously published population PK (PopPK) model was also examined.ResultsPredicted HDM AUC was within 15% of the observed values in only 63% of patients when analysed using the trapezoidal rule and 70% of patients using PopPK. Test dose infusion concentration, volume, duration and time from preparation to infusion were significantly lower than for HDM (p < 0.005). Test dose administration within 15 min of reconstitution (n = 5) was associated with significantly lower PE than administration times of 16–60 min (n = 22), p < 0.05. Test and HDM infusion concentrations were lower in patients with large PE (> ± 15%), but the differences were not significant (p = 0.078, 0.228, respectively).ConclusionTest dose PK has the potential to predict subsequent HDM exposure to achieve a target AUC once melphalan administration parameters are optimised to account for stability issues in the formulation.

Towards Precision Dosing of Clozapine in Schizophrenia: External Evaluation of Population Pharmacokinetic Models and Bayesian Forecasting.

Therapeutic drug monitoring and treatment optimization of clozapine are recommended, owing to its narrow therapeutic range and pharmacokinetic (PK) variability. This study aims to assess the clinical applicability of published population PK models by testing their predictive performance in an external data set and to determine the effectiveness of Bayesian forecasting (BF) for clozapine treatment optimization. Available models of clozapine were identified, and their predictive performance was determined using an external data set (53 patients, 151 samples). The median prediction error (PE) and median absolute PE were used to assess bias and inaccuracy. The potential factors influencing model predictability were also investigated. The final concentration was reestimated for all patients using covariates or previously observed concentrations. The 7 included models presented limited predictive performance. Only 1 model met the acceptability criteria (median PE ≤ ±20% and median absolute PE ≤30%). There was no difference between the data used for building the models (therapeutic drug monitoring or PK study) or the number of compartments in the models. A tendency for higher inaccuracy at low concentrations during treatment initiation was observed. Heterogeneities were observed in the predictive performances between the subpopulations, especially in terms of smoking status and sex. For the models included, BF significantly improved their predictive performance. Our study showed that upon external evaluation, clozapine models provide limited predictive performance, especially in subpopulations such as nonsmokers. From the perspective of model-informed prediction dosing, model predictability should be improved using updating or metamodeling methods. Moreover, BF substantially improved model predictability and could be used for clozapine treatment optimization.

Ulcerative Colitis and Acute Severe Ulcerative Colitis Patients Are Overlooked in Infliximab Population Pharmacokinetic Models: Results from a Comprehensive Review.

Ulcerative colitis (UC) is part of the inflammatory bowels diseases, and moderate to severe UC patients can be treated with anti-tumour necrosis α monoclonal antibodies, including infliximab (IFX). Even though treatment of UC patients by IFX has been in place for over a decade, many gaps in modelling of IFX PK in this population remain. This is even more true for acute severe UC (ASUC) patients for which early prediction of IFX pharmacokinetic (PK) could highly improve treatment outcome. Thus, this review aims to compile and analyse published population PK models of IFX in UC and ASUC patients, and to assess the current knowledge on disease activity impact on IFX PK. For this, a semi-systematic literature search was conducted, from which 26 publications including a population PK model analysis of UC patients receiving IFX therapy were selected. Amongst those, only four developed a model specifically for UC patients, and only three populations included severe UC patients. Investigations of disease activity impact on PK were reported in only 4 of the 14 models selected. In addition, the lack of reported model codes and assessment of predictive performance make the use of published models in a clinical setting challenging. Thus, more comprehensive investigation of PK in UC and ASUC is needed as well as more adequate reports on developed models and their evaluation in order to apply them in a clinical setting.

Nifurtimox for Treatment of Chagas Disease in Pediatric Patients: the Challenges of Applying Pharmacokinetic-Pharmacodynamic Principles to Dose Finding

Theantiparasitic drug nifurtimox was approved in the USA in 2020 for the treatment of patients with Chagas disease aged less than 18 years and weighing at least 2.5 kg, based on outcomes from the phase 3 CHICO study. Accordingly, pediatric patients with Chagas disease take nifurtimox thrice daily with food at one of two body weight–adjusted dose ranges. We investigated possible relationships between pharmacokinetic (PK) data, and pharmacodynamic efficacy and safety data collected in an analysis population of 111 participants in CHICO, using a published population PK model to estimate nifurtimox exposure at the patient level. Pediatric exposure to nifurtimox was benchmarked against levels of nifurtimox exposure known to be effective in adults with Chagas disease. Given the complex dosing regimen for nifurtimox, we also modeled nifurtimox exposure associated with simpler dosing strategies. We found no relationship between exposure to nifurtimox and efficacy measures (e.g., serological response to treatment), or between exposure and safety outcomes (including typical adverse events, e.g., headache, decreased appetite, nausea/vomiting). The analysis population appeared to represent the overall CHICO population based on the similarity of their baseline characteristics and the profiles of adverse events in the two groups. Modeled exposure based on the dosing regimen in CHICO was within the reference range derived from phase 1 data in adults. The relationship between nifurtimox exposure and cure is complex; a simplified pediatric dosing regimen is unlikely to be beneficial.Graphical abstract

Machine learning algorithms to estimate everolimus exposure trained on simulated and patient pharmacokinetic profiles.

Everolimus is an immunosuppressant with a small therapeutic index and large between‐patient variability. The area under the concentration versus time curve (AUC) is the best marker of exposure but measuring it requires collecting many blood samples. The objective of this study was to train machine learning (ML) algorithms using pharmacokinetic (PK) profiles from kidney transplant recipients, simulated profiles, or both types, and compare their performance for everolimus AUC0‐12h estimation using a limited number of predictors, as compared to an independent set of full PK profiles from patients, as well as to the corresponding maximum a posteriori Bayesian estimates (MAP‐BE). XGBoost was first trained on 508 patient interdose AUCs estimated using MAP‐BE, and then on 500–10,000 rich interdose PK profiles simulated using previously published population PK parameters. The predictors used were: predose, ~1 h, and ~2 h whole blood concentrations, differences between these concentrations, relative deviations from theoretical sampling times, morning dose, patient age, and time elapsed since transplantation. The best results were obtained with XGBoost trained on 5016 simulated profiles. AUC estimation achieved in an external dataset of 114 full‐PK profiles was excellent (root mean squared error [RMSE] = 10.8 μg*h/L) and slightly better than MAP‐BE (RMSE = 11.9 μg*h/L). Using more profiles (n = 10,035) did not improve the ML algorithm performance. The contribution of mixing patient and simulated profiles was significant only when they were in balanced numbers, with ~500 for each (RMSE = 12.5 μg*h/L), compared with patient data alone (RMSE = 18.0 μg*h/L).

Pharmacokinetics of Cefepime in Children on Extracorporeal Membrane Oxygenation: External Model Validation, Model Improvement and Dose Optimization.

Cefepime is a first-line therapy for Gram-negative infections in children on extracorporeal membrane oxygenation. Cefepime pharmacokinetics (PK) in children on extracorporeal membrane oxygenation still needs to be better established. This was a prospective single-center PK study. A maximum of 12 PK samples per patient were collected in children <18 years old on extracorporeal membrane oxygenation who received clinically indicated cefepime. External validation of a previously published population PK model was performed by applying the model in a new data set. The predictive performance of the model was determined by calculating prediction errors. Because of poor predictive performance, a revised model was developed using NONMEM and a combined data set that included data from both studies. Dose-exposure simulations were performed using the final model. Optimal dosing was judged based on the ability to maintain free cefepime concentrations above the minimal inhibitory concentration (MIC) for 68% and 100% of the dosing interval. Seventeen children contributed 105 PK samples. The mean (95% CI) and median (interquartile range) prediction errors were 33.7% (19.8-47.7) and 17.5% (-22.6 to 74.4). A combined data set was created, which included 33 children contributing 310 PK samples. The final improved 2-compartment model included weight and serum creatinine on clearance and oxygenator day and blood transfusion on volume of the central compartment. At an MIC of 8 mg/L, 50 mg/kg/dose every 8 hours reached target concentrations. Dosing intervals of 8 hours were needed to reach adequate concentrations at an MIC of 8 mg/L. Longer dosing intervals were adequate with higher serum creatinine and lower MICs.

In silico evaluation of limited sampling strategies for individualized dosing of extended half-life factor IX concentrates in hemophilia B patients

PurposeHemophilia B is a bleeding disorder, caused by a factor IX (FIX) deficiency. Recently, FIX concentrates with extended half-life (EHL) have become available. Prophylactic dosing of EHL-FIX concentrates can be optimized by assessment of individual pharmacokinetic (PK) parameters. To determine these parameters, limited sampling strategies (LSSs) may be applied. The study aims to establish adequate LSSs for estimating individual PK parameters of EHL-FIX concentrates using in silico evaluation.MethodsMonte Carlo simulations were performed to obtain FIX activity versus time profiles using published population PK models for N9-GP (Refixia), rFIXFc (Alprolix), and rIX-FP (Idelvion). Fourteen LSSs, containing three or four samples taken within 8 days after administration, were formulated. Bayesian analysis was applied to obtain estimates for clearance (CL), half-life (t1/2), time to 1% (Time1%), and calculated weekly dose (Dose1%). Bias and precision of these estimates were assessed to determine which LSS was adequate.ResultsFor all PK parameters of N9-GP, rFIXFc and rIX-FP bias was generally acceptable (range: −5% to 5%). For N9-GP, precision of all parameters for all LSSs was acceptable (< 25%). For rFIXFc, precision was acceptable for CL and Time1%, except for t1/2 (range: 27.1% to 44.7%) and Dose1% (range: 12% to 29.4%). For rIX-FP, all LSSs showed acceptable bias and precision, except for Dose1% using LSS with the last sample taken on day 3 (LSS 6 and 10).ConclusionBest performing LSSs were LSS with samples taken at days 1, 5, 7, and 8 (N9-GP and rFIXFc) and at days 1, 4, 6, and 8 (rIX-FP), respectively.

Elevated MICs of Susceptible Antipseudomonal Cephalosporins in Non-Carbapenemase-Producing, Carbapenem-Resistant Pseudomonas aeruginosa: Implications for Dose Optimization.

The present study evaluated the in vitro potency of ceftazidime and cefepime among carbapenem-resistant Pseudomonas aeruginosa isolates collected as part of a global surveillance program and assessed the pharmacodynamic implications using previously published population pharmacokinetics. When susceptible, MICs resulted at the high end of distribution for both ceftazidime and cefepime, thus 6 g/day was required to achieve optimal pharmacodynamic profiles. These findings should be considered in the clinic and for the application of CLSI susceptibility breakpoints.

Application of a dual mechanistic approach to support bilastine dose selection for older adults.

The objective of this study was to evaluate bilastine dosing recommendations in older adults and overcome the limitation of insufficient data from phase I studies in this underrepresented population. This was achieved by integrating bilastine physicochemical, in vitro and in vivo data in young adults and the effect of aging in the pharmacology by means of two alternative approaches: a physiologically‐based pharmacokinetic (PBPK) model and a semi‐mechanistic population pharmacokinetic (Senescence) model. Intestinal apical efflux and basolateral influx transporters were needed in the PBPK model to capture the observations from young adults after single i.v. (10 mg) and p.o. (20 mg) doses, supporting the hypothesis of involvement of gut transporters on secretion. The model was then used to extrapolate the pharmacokinetics (PKs) to elderly subjects considering their specific physiology. Additionally, the Senescence model was develop starting from a published population PK) model, previously applied for pediatrics, and incorporating declining functions on different physiological systems and changes in body composition with aging. Both models were qualified using observed data in a small group of young elderlies (N = 16, mean age = 68.69 years). The PBPK model was further used to evaluate the dose in older subjects (mean age = 80 years) via simulation. The PBPK model supported the hypothesis that basolateral influx and apical efflux transporters are involved in bilastine PK. Both, PBPK and Senescence models indicated that a 20 mg q.d. dose is safe and effective for geriatrics of any age. This approach provides an alternative to generate supplementary data to inform dosing recommendations in under‐represented groups in clinical trials.

Validation of a perioperative population factor VIII pharmacokinetic model with a large cohort of pediatric hemophilia a patients.

AimsPopulation pharmacokinetic (PK) models are increasingly applied to perform individualized dosing of factor VIII (FVIII) concentrates in haemophilia A patients. To guarantee accurate performance of a population PK model in dose individualization, validation studies are of importance. However, external validation of population PK models requires independent data sets and is, therefore, seldomly performed. Therefore, this study aimed to validate a previously published population PK model for FVIII concentrates administrated perioperatively.MethodsA previously published population PK model for FVIII concentrate during surgery was validated using independent data from 87 children with severe haemophilia A with a median (range) age of 2.6 years (0.03–15.2) and body weight of 14 kg (4–57). First, the predictive performance of the previous model was evaluated with MAP Bayesian analysis using NONMEM v7.4. Subsequently, the model parameters were (re)estimated using a combined dataset consisting of the previous modelling data and the data available for the external validation.ResultsThe previous model underpredicted the measured FVIII levels with a median of 0.17 IU mL−1. Combining the new, independent and original data, a dataset comprising 206 patients with a mean age of 7.8 years (0.03–77.6) and body weight of 30 kg (4–111) was obtained. Population PK modelling provided estimates for CL, V1, V2, and Q: 171 mL h−1 68 kg−1, 2930 mL 68 kg−1, 1810 mL 68 kg−1, and 172 mL h−1 68 kg−1, respectively. This model adequately described all collected FVIII levels, with a slight median overprediction of 0.02 IU mL−1.ConclusionsThis study emphasizes the importance of external validation of population PK models using real‐life data.

Limited sampling strategies for accurate determination of extended half-life factor VIII pharmacokinetics in severe haemophilia A patients.

Extended half-life (EHL) factor VIII (FVIII) products may decrease the burden of prophylactic treatment in haemophilia A by reducing infusion frequency. However, these products still exhibit wide inter-patient variability and benefit from pharmacokinetic (PK) tailoring. Identify limited sampling strategies for rFVIIIFc, an EHL FVIII product, that produce accurate estimates of PK parameters and relevant troughs. We performed a limited sampling analysis on simulated populations of adults, adolescents, and children based on published population PK data. Sampling strategies were evaluated by comparing the error in estimates of half-life, clearance, and trough levels, to a full 6-sample design. Furthermore, we assessed the impact of incorporating knowledge about prior doses, and the day of the PK study within the regimen. We also evaluated the potential inappropriate dose adjustment rate (IDAR) among the modelled sampling strategies. Many sampling strategies, including several 2-sample designs, accurately predicted the PK and exposure measures (median absolute error <10%). When samples are only collected during a single visit (i.e., predose+peak), inclusion of prior dose information reduces median half-life error from >20% to ~5% for adults/adolescents. In this same scenario, appropriate scheduling of the PK study decreases likelihood of unmeasurable predose samples, reducing median error on the 72-h trough from 25% to <12% in the youngest population. The PK of rFVIIIFc can be accurately estimated using only peak and trough samples, provided that knowledge of prior doses is incorporated and the PK study is planned on an appropriate day within the dosing regimen.

Population pharmacokinetic analysis of bisoprolol in type 2 diabetic patients with hypertension

Given that it has been reported that type 2 diabetes mellitus may affect the pharmacokinetics of a large number of drugs and that there are still no published population pharmacokinetic (PopPK) analyses in routinely treated patients with hypertension and type 2 diabetes mellitus as comorbid condition, the aim of this study was to determine PK variability of bisoprolol in 70 Serbian patients using the PopPK approach. PopPK analysis was conducted using a nonlinear mixed effects model (NONMEM), version 7.3.0 (Icon Development Solutions). In our patients, a total daily dose of bisoprolol ranged from 1.25 to 10mg. The drug was administrated orally as a single daily dose or in two divided doses per day. A wide range of the drug concentrations were noted (1-103ng/mL) in the population consisted of the adult patients with type 2 diabetes mellitus. From a total of 21 separately assessed covariates, our results indicated that only creatinine clearance could have a potential impact on the variability of the clearance of bisoprolol. Routine assessment of renal function should be carried out before the initiation of treatment with bisoprolol in order to individualize the dose and to prevent possible accumulation and adverse drug reactions.