Final Population Pharmacokinetic Model Research Articles

2529. Population pharmacokinetic models for cefepime and enmetazobactam derived from pooled Phase 1 to Phase 3 clinical studies

Abstract Background The investigational β-lactam/β-lactamase inhibitor combination of cefepime (FEP)/enmetazobactam (ENM) met criteria for non-inferiority and superiority compared to piperacillin/tazobactam in a phase 3 clinical trial of adult patients with complicated urinary tract infections (cUTI)/acute pyelonephritis (AP). In this study, a population pharmacokinetic (PK) model is presented that describes FEP and ENM plasma PK in adult cUTI/AP patients. Methods Plasma PK samples were analyzed from participants receiving FEP (n=588) and ENM (n=649) in three phase 1 (n=132), and single phase 2 (n=43) and phase 3 (n=488) clinical trials. Population PK parameters were assessed and the relationship between different covariates and model parameters were investigated. The effect of infection on disposition was assessed by testing disease covariates on fixed and random effects for all PK parameters. Results A two-compartment model with linear clearance of FEP (5.95 L/h) and ENM (7.68 L/h) from the central compartment best described the PK of both compounds. Common covariates for both compounds were de-indexed estimated glomerular filtration rate (eGFR), age, and body weight while ENM PK covariates also included cUTI infection and sex. Simulations showed that the only covariate requiring dose adjustment was renal function. The final model simultaneously described FEP and ENM plasma PK, which enabled estimates of the correlation of the random effects between PK parameters. Clearances and volumes of distribution (Vd) were strongly correlated within individuals between the two compounds (correlation coefficients >0.9). Variability was higher in cUTI patients although differences in mean ENM or FEP exposures between healthy subjects and cUTI patients were negligible. The total Vd was 16.9 L for FEP and 20.6 L for ENM. Clearance of both agents was found to depend on de-indexed eGFR (covariate coefficients ≥0.83), suggesting that renal filtration is the predominant clearance mechanism. The terminal elimination half-life was 2.2 h for FEP and 2.0 h for ENM. Final population PK model population parameter estimates for cefepime and enmetazobactam determined from the pooled phase 1 to phase 3 clinical studies Conclusion The population PK models for FEP and ENM predict exposures in cUTI patients, including subjects with renal impairment. These models support Monte-Carlo simulations and target attainment estimations in adult cUTI/AP patients. Disclosures Adam Belley, PhD, Allecra Therapeutics SAS: Advisor/Consultant Patrick Velicitat, MD, Allecra Therapeutics SAS: Salary

Population Pharmacokinetic and Pharmacodynamic Analysis of Navtemadlin in Patients with Relapsed and Refractory (R/R) Myelofibrosis (MF) and Other Myeloid or Solid Tumor Malignancies

Background:Murine double minute 2 (MDM2), a key negative regulator of the tumor suppressor protein p53, is overexpressed in malignancies such as MF and Merkel cell carcinoma (MCC). Navtemadlin is a potent, selective, orally available MDM2 inhibitor that overcomes MDM2 dysregulation by restoring p53 activity and inducing apoptosis of TP53WT tumors. Navtemadlin has been tested in 21- or 28-day treatment cycles, with 5 or 7 consecutive days of dosing per cycle. Navtemadlin elicits plasma concentration-dependent increases in serum macrophage inhibitory cytokine-1 (MIC-1). An increase in MIC-1 relative to baseline MIC-1 serum concentration is a key pharmacodynamic (PD) marker of response to navtemadlin treatment (Zhang et al. Xenobiotica 2022). A population pharmacokinetic (PK) model was developed, based on patients with R/R MF (N=113, NCT03662126); MCC (N=35, NCT03787602); solid tumors and multiple myeloma (ST/MM N=105, Gluck et al. Invest New Drugs 2019); R/R acute myeloid leukemia (AML, N=35, Erba et al. Blood Adv 2019); and healthy volunteers (HV, N=30, Wong et al. Clin Pharmacol Drug Dev 2022).The objectives wereto characterize navtemadlin PK and covariate effects and compare steady-state (SS) PK and PD across cancer types. Methods:A two-compartment PK model with first-order absorption and elimination was estimated using NONMEM ® (first-order conditional estimation with interaction). Four transit compartments captured absorption. Inter-subject variability was modeled as lognormal. A stepwise covariate search used forward addition (p<0.05) followed by backward elimination (p<0.01). Log-transformed SS MIC-1 ratio to baseline (fold ratio) was tested in a fixed-effects linear regression model with respect to SS exposures, with baseline MIC-1 as the covariate. The final population PK and MIC-1 models were evaluated by inspection of parameter tables, by overlaying model predictions with observed data, and by standard residual diagnostics. Results:The PK estimation used 5,282 concentrations from 318 subjects, including 1,415 concentrations in 113 patients with R/R MF. Tumor type affected absorption rate (median, 0.635/hr in MCC; slower vs other types), apparent clearance (median, 8.90 L/hr in MCC; lower vs other types), and apparent central volume (median, 64.4 L in MCC; similar to AML, but lower vs other types) (Table 1). Accordingly, simulated SS area under the curve (AUCss) differed across populations in the order MCC>AML>MF>ST/MM = HV (Figure 1). Covariate analysis indicated median AUC increased with the inflammation marker C-reactive protein, by 21% at 90 th percentile CRP, and with age, by 5% at 90 th percentile age of 75 y, compared to the median, 66 y. Men had 24% lower relative bioavailability than women. Taking navtemadlin with food slowed absorption by 10% but had no impact on AUCss. Other tested covariates, including body weight, creatinine clearance, aspartate transaminase, alanine transaminase, bilirubin, albumin, alpha 1-acid glycoprotein, race, UGT1A1 genotype, recent ruxolitinib treatment in MF, and CYP3A4 inducer/inhibitor concomitant medications, were not significant. Median MIC-1 fold ratio increased with navtemadlin AUCss. Higher baseline MIC-1 resulted in lower SS MIC-1 fold ratio. Median baseline MIC-1 differed by tumor type. In R/R MF, baseline MIC-1 was 2,297 ng/L and SS fold ratio of MIC-1 was 7.79 (N=91). In MCC, baseline MIC-1 was 1,718 ng/L and SS fold ratio of MIC-1 was 16.7 (N=29). In R/R MF, higher baseline spleen volume was also associated with lower SS MIC-1 fold ratio. Exposure-MIC-1 relationships in R/R MF and MCC were generally similar to other tumor types and HV populations (Allard et al. Hemasphere 2019; Zhang et al. Xenobiotica 2022). Conclusions:Tumor type influenced navtemadlin exposure with simulated exposure in R/R MF patients at the selected Phase 3 dose of 240 mg comparable to exposures in MCC patients at 180 mg, the selected Phase 2 dose for that indication. Cancer-associated inflammation and/or treatment history, as well as age and female sex, may increase navtemadlin exposure. The PD marker MIC-1 responds to navtemadlin in a concentration-dependent fashion. The overall SS fold change of MIC-1 PD responses was lower in disease states or subjects with higher baseline MIC-1. These studies demonstrate potent, dose-dependent PK/PD responses following p53 activation with the novel MDM2 inhibitor, navtemadlin, across diverse tumor types.

A new pharmacokinetic model of urinary methotrexate to assess adherence in rheumatoid arthritis

Background and objectivesMethotrexate (MTX) is the first-line therapy for rheumatoid arthritis (RA). While therapeutic adherence is essential to successful management, no objective MTX assay is currently available. Using population pharmacokinetic modelling (PopPK), our objective was to describe the urinary MTX (MTXu) kinetics in treated patients and to evaluate its abilities to assess the MTX-adherence. MethodsThe association between urinary methotrexate level and methotrexate administration was assessed using a generalized linear model. Then, a population pharmacokinetic model was developed based on data from 59 patients using with Monolix 2021. R2. Simulations were run to establish a reference kinetic profile and evaluate the proportion of samples predicted as true positives. ResultsCompared to the control group, multivariate analysis showed that MTXu was independently associated with methotrexate administration (p < 0.0001) with a sensitivity and specificity greater than 99%. The final PopPK model selected was a two-compartment model with first-order absorption and elimination. Internal and external validation of the model met all predefined criteria. When using an analytical assay with a LOQ equal to 1 nM, the proportion of samples predicted as true positives is over 90%, as a function of MTX dose (7.5–25 mg/week) and post-administration sampling days (1–7 days). ConclusionWe developed a pharmacokinetic model able to describe expected patterns of urinary methotrexate. This allowed us to propose a new objective test of MTX adherence, which could help in routine practice to differentiate patients who are truly unresponsive to methotrexate from those who are unresponsive because of non-adherence.

The cycle effect quantified: reduced tumour uptake in subsequent cycles of [177Lu]Lu-HA-DOTATATE during peptide receptor radionuclide therapy.

Clear evidence regarding the effect of reduced tumour accumulation in later peptide receptor radionuclide therapy (PRRT) cycles is lacking. Therefore, we aimed to quantify potential cycle effects for patients treated with [177Lu]Lu-HA-DOTATATE using a population pharmacokinetic (PK) modelling approach. A population PK model was developed using imaging data from 48 patients who received multiple cycles of [177Lu]Lu-HA-DOTATATE. The five-compartment model included a central, kidney, spleen, tumour and lumped rest compartment. Tumour volume and continued use of long-acting somatostatin analogues (SSAs) were tested as covariates in the model. In addition, the presence of a cycle effect was evaluated by relating the uptake rate in a specific cycle as a fraction of the (tumour or organ) uptake rate in the first cycle. The final PK model adequately captured observed radioactivity accumulation in kidney, spleen and tumour. A higher tumour volume was identified to increase the tumour uptake rate, where a twofold increase in tumour volume resulted in a 2.3-fold higher uptake rate. Also, continued use of long-acting SSAs significantly reduced the spleen uptake rate (68.4% uptake compared to SSA withdrawal (10.5% RSE)). Lastly, a cycle effect was significantly identified, where tumour uptake rate decreased to 86.9% (5.3% RSE) in the second cycle and even further to 79.7% (5.6% RSE) and 77.6% (6.2% RSE) in the third and fourth cycle, respectively, compared to cycle one. Using a population PK modelling approach, the cycle effect of reduced tumour uptake in subsequent PRRT cycles was quantified. Our findings implied that downregulation of target receptors is probably not the major cause of the cycle effect, due to a plateau in the decrease of tumour uptake in the fourth cycle.

Population Pharmacokinetic Analysis of Follicle-Stimulating Hormone During Ovarian Stimulation: Relation with Weight, Prolactin and Gene Polymorphism in THADA and ADIPOQ.

Personalisation strategies of ovarian stimulation for in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatments using exogenous follicle-stimulating hormone (FSH) have been extensively studied over the past 20 years. This research aimed to develop a FSH population pharmacokinetic (PPK) model taking into account the contribution of gene polymorphisms in Chinese reproductive-age women. Data from 173 patients undergoing GnRH agonist down-regulation long protocols of IVF/ICSI treatment were collected. PPK analysis was subsequently conducted using the nonlinear mixed-effect model (NONMEM) software. Several covariates, including 18 single nucleotide polymorphisms, demographic factors and biological characteristics, were evaluated. The final PPK model was extensively validated using bootstrapping and normalised prediction error distribution, as well as external validation on an independent group of 35 patients. FSH PPK was accurately described by a one-compartment model with first-order absorption. The typical population value of apparent clearance was estimated to be 0.81 L/h [relative standard errors (RSE) 5.3%] with an inter-individual variability (IIV) of 16.0%. The typical apparent distribution volume was 8.36 L (RSE 9.7%, 59.7% IIV), and the absorption rate constant was estimated to be 0.0444 h-1 (RSE 9.1%). Body weight, basal prolactin concentration and the gene ADIPOQ (rs1501299) showed a significant covariate effect on the FSH clearance rate and exposure concentration. Genotypes of THADA (rs12478601) significantly influenced the distribution volume. Simulation results indicated that patients with the TT genotype of THADA (rs12478601) required a longer time to reach steady state and had less fluctuation in FSH levels. Model evaluations showed that the final model accurately and precisely described the observed data and demonstrated effective prediction performance. PPK models of FSH have been developed, which could potentially be used for FSH dosage individualisation in the clinical setting. This study has been registered with the Chinese Clinical Trials Registry (ChiCTR2100049142).

Population Pharmacokinetic Modeling of Dolutegravir to Optimize Pediatric Dosing in HIV-1-Infected Infants, Children, and Adolescents.

HIV treatment options remain limited in children. Dolutegravir is a potent and well-tolerated, once-daily HIV-1 integrase inhibitor recommended for HIV-1 infection in both adults and children down to 4 weeks of age. To support pediatric dosing of dolutegravir in children, we used a population pharmacokinetic model with dolutegravir data from the P1093 and ODYSSEY clinical trials. The relationship between dolutegravir exposure and selected safety endpoints was also evaluated. A population pharmacokinetic model was developed with data from P1093 and ODYSSEY to characterize the pharmacokinetics and associated variability and to evaluate the impact of pharmacokinetic covariates. The final population pharmacokinetic model simulated exposures across weight bands, doses, and formulations that were compared with established adult reference data. Exploratory exposure-safety analyses evaluated the relationship between dolutegravir pharmacokinetic parameters and selected clinical laboratory parameters and adverse events. A total of N = 239 participants were included, baseline age ranged from 0.1 to 17.5 years, weight ranged from 3.9 to 91 kg, 50% were male, and 80% were black. The final population pharmacokinetic model was a one-compartment model with first-order absorption and elimination, enabling predictions of dolutegravir concentrations in the pediatric population across weight bands and doses/formulations. The predicted geometric mean trough concentration was comparable to the adult value following a 50-mg daily dose of dolutegravir for all weight bands at recommended doses. Body weight, age, and formulation were significant predictors of dolutegravir pharmacokinetics in pediatrics. Additionally, during an exploratory exposure-safety analysis, no correlation was found between dolutegravir exposure and selected safety endpoints or adverse events. The dolutegravir dosing in children ≥ 4 weeks of age on an age/weight-band basis provides comparable exposures to those historically observed in adults. Observed pharmacokinetic variability was higher in this pediatric population and no additional safety concerns were observed. These results support the weight-banded dosing of dolutegravir in pediatric participants currently recommended by the World Health Organization.

Population pharmacokinetics of topiramate in Chinese children with epilepsy.

Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy. The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies. In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW⁄11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW⁄11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW⁄11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate. The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

Individualized Delivery of Vancomycin by Model-Informed Bayesian Dosing Approach to Maintain an AUC24 Target in Critically Ill Patients

Introduction: Monitoring of AUC24 was updated recommendation in the guideline for the therapeutic drug monitoring (TDM) of vancomycin in Chinese pharmacological society published in 2020. Vancomycin pharmacokinetic profiles are diverse and unique in critically ill patients because of the drastic variability of the patients’ physiological parameters, while the study for population pharmacokinetic (PPK) models in Chinese critically ill patients has been rarely reported. The objectives of this study were to construct a PPK model to describe the pharmacokinetic characteristics of vancomycin in critically ill patients and to individualize vancomycin dosing by model-informed Bayesian estimation for maintenance of AUC24 target at 400–650 mg h/L recommended by the 2020 guideline. Methods: Vancomycin with different dosing was administered intravenously over 1 h for critically ill patients, TDM was started at 48 h or 72 h since initiation of vancomycin therapy for patients. Blood samples were collected from patients for trough concentrations or Cmax. Vancomycin concentrations were determined by high-performance liquid chromatography method with ultraviolet detection. PPK model was performed using the nonlinear mixed-effect model (NONMEM®). Individual PK parameters for critically ill patients treated with vancomycin were estimated using a post hoc empirical Bayesian method based on the final PPK model. AUC24 was calculated as the total daily dose divided by the clearance (L/h). Results: The PPK of vancomycin was determined by a one-compartment model with creatinine clearance as fixed effects. The PK estimates in the final model generally agreed with the median estimates and were contained within the 95% CI generated from the bootstrap results, indicating good precision and stability in the final model. The visual predictive check plots showed the adequate predictive performance of the final PK model and supported a good model fit. The model-informed Bayesian estimation was used to predict the AUC24 of critically ill patient by the acquired TDM results, and the dosing adjustment by maintenance of AUC24 at 400–650 mg h/L had made a great therapeutic effect for the case. Conclusion: This study established a PPK model of vancomycin in Chinese critically ill patients, and individualized dosing of vancomycin by model-informed Bayesian estimation to maintain an AUC24 target at 400–650 mg h/L has been successfully applied in clinic. This result supports the continued use of model-informed Bayesian estimation to vancomycin treatment in critically ill patients.

Population pharmacokinetics of oxcarbazepine active metabolite in Chinese children with epilepsy.

Oxcarbazepine (OXC) is an antiepileptic drug whose efficacy is largely attributed to its monohydroxy derivative metabolite (MHD). Nevertheless, there exists significant inter-individual variability in both the pharmacokinetics and therapeutic response of this drug. The objective of this study is to explore the impact of patients' characteristics and genetic variants on MHD clearance in a population pharmacokinetic (PPK) model of Chinese pediatric patients with epilepsy. The PPK model was developed using a nonlinear mixed effects modeling method based on 231 MHD plasma concentrations obtained from 185 children with epilepsy. The one-compartment model and combined residual model were established to describe the pharmacokinetics of MHD. Forward addition and backward elimination were employed to evaluate the impact of covariates on the model parameters. The model was evaluated using goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. In the two final PPK models, age, estimated glomerular filtration rate (eGFR), and a combined genotype of six variants (rs1045642, rs2032582, rs7668282, rs2396185, rs2304016, rs1128503) were found to significantly reduce inter-individual variability for MHD clearance. The inter-individual clearance equals to 1.38 × (Age/4.74)0.29 × (eGFR/128.66)0.25 × eθABCB-UGT-SCN-INSR for genetic variants included model and 1.30 × (Age/4.74)0.30 × (eGFR/128.66)0.23 for model without genetic variants. The precision of all parameters was deemed acceptable, and the model exhibited good predictability while remaining stable and effective. Conclusion: Age, eGFR, and genotype may play a significant role in MHD clearance in children with epilepsy. The developed PPK models hold potential utility in facilitating oxcarbazepine dose adjustment in pediatric patients. What is Known: • The adjustment of the oxcarbazepine regimen remains difficult due to the considerable inter- and intra-individual variability of oxcarbazepine pharmacokinetics. • Body weight and co-administration with enzyme-inducing antiepileptic drugs emerge as the most influential factors contributing to the pharmacokinetics of MHD. What is New: • A positive correlation was observed between eGFR and the clearance of MHD in pediatric patients with epilepsy. • We explored the influence of genetic polymorphisms on MHD clearance and identified a combined genotype (ABCB-UGT-SCN-INSR) that exhibited a significant association with MHD concentration.

Significant Effects of Renal Function on Mycophenolic Acid Total Clearance in Pediatric Kidney Transplant Recipients with Population Pharmacokinetic Modeling.

Mycophenolic acid (MPA) is an immunosuppressant commonly prescribed in pediatric kidney transplantation to prevent graft rejection. Large variabilities in MPA plasma exposures have been observed in this population, which could result in severe adverse effects. The majority of the MPA pharmacokinetic data have been reported in adult populations, whereas information in pediatric patients is still very limited. The objective of this study was to establish a novel, nonlinear mixed-effects model for MPA and investigate the clinical variables affecting MPA population pharmacokinetics in pediatric kidney transplant recipients. Data were collected retrospectively from pediatric kidney transplant patients (≤ 18 years when MPA concentrations were initially collected; on oral administration of mycophenolate mofetil) in Calgary, Alberta, Canada. Nonlinear mixed-effect modeling was conducted using stochastic approximation expectation-maximization in Monolix 2021R2 (Lixoft SAS, France) to determine population pharmacokinetic estimates, interindividual variabilities, and interoccasional variabilities. Covariate models were constructed using the Model Proposal function in Monolix in conjunction with a systematic stepwise inclusion/elimination protocol. The best model was selected based on objective function values, relative standard errors, goodness-of-fit plots, prediction-corrected visual predictive checks, and numerical predictive checks. A total of 50 pediatric kidney transplant patients (25 female) with 219 MPA plasma concentration-time profiles were included. The average age (± standard deviation) and posttransplant time for the sample population were 12.8 ± 4.8 years and 762 ± 1160 days, respectively. The majority of study subjects (i.e., > 85% based on all occasions) were co-administered tacrolimus. A two-compartment, first-order absorption with lag time and linear elimination structural model with lognormal distributed proportional residual errors best described the MPA concentration-time data. The absorption rate constant (2.52 h-1 or 0.042 min-1), lag time (0.166 h or 9.96 min), volumes of distributions of the central (22.8 L) and peripheral (216 L) compartments, and intercompartment clearance (17.6 Lh-1 or 0.293 Lmin-1) were consistent with literature values; whereas total MPA clearance (0.72 Lh-1 or 0.012 Lmin-1) was relatively reduced, likely due to the general lack of cyclosporine interactions and the stabilized graft functions from significantly longer posttransplant time in our sample population. Of the clinical variables tested, only estimated glomerular filtration rate (eGFR) was identified a significant covariate affecting total MPA clearance with a positive, exponential relationship. The final population pharmacokinetic model was successfully evaluated/validated using a variety of complementary methods. We have successfully constructed and validated a novel population pharmacokinetic model of MPA in pediatric kidney transplant patients. A positive, nonlinear relationship between eGFR and total MPA clearance identified in our model is likely attributed to multiple concurrent mechanisms, which warrant further systematic investigations.

Population Pharmacokinetics of Oral Azacitidine, and Exposure-Response Analysis in Acute Myeloid Leukemia.

Oral azacitidine (oral-AZA) maintenance is approved for adults with acute myeloid leukemia (AML) in remission post-intensive chemotherapy, not proceeding to hematopoietic stem cell transplantation. This study aimed to develop a population pharmacokinetic (PopPK) model to characterize oral-AZA concentration-time profiles in patients with AML, myelodysplastic syndrome, or chronic myelomonocytic leukemia. PopPK-estimated exposure parameters were used to evaluate exposure-response relationships in the phase III QUAZAR AML-001 study. The PopPK dataset comprised 286 patients with 1,933 evaluable oral-AZA concentration records. The final PopPK model was a one-compartment model with first-order absorption incorporating an absorption lag time and first-order elimination. Regression analyses identified two oral-AZA exposure parameters (area under the plasma concentration-time curve at steady state (AUCss ); maximum plasma concentration (Cmax )) as statistically significant predictors for relapse-free survival (hazard ratio (HR) = 0.521, P < 0.001; HR = 0.630, P = 0.013; respectively), and AUCss as a significant predictor for overall survival (HR = 0.673, P = 0.042). The probability of grade ≥ 3 neutropenia was significantly increased with increases in AUCss (odds ratio (OR) = 5.71, 95% confidence interval (CI) = 2.73-12.62, P < 0.001), cumulative AUC through cycles 1 to 6 (OR = 2.71, 95% CI = 1.76-4.44, P < 0.001), and Cmax at steady-state (OR = 2.38, 95% CI = 1.23-4.76, P = 0.012). A decreasing trend was identified between AUCss and relapse-related schedule extensions, vs. an increasing trend between AUCss and event-related dose reductions. As the majority (56.8%) of patients required no dose modifications, and the proportions requiring schedule extension (19.4%) or dose reduction (22.9%) were almost equal, oral-AZA 300 mg once daily for 14 days is the optimal dosing schedule balancing survival benefit and safety risk.

Establishing Population Pharmacokinetic Model for Ethambutol on Pulmonary Tuberculosis Patients

The population pharmacokinetic model of ethambutol with covariates was built from data from 136 pulmonary tuberculosis patients recruited from 3 hospitals: Hanoi Lung Hospital, Central Hospital 74, and Central Lung Hospital. Blood samples were obtained on the 10-14th day after initiation of treatment for plasma drug analysis by LC-MS/MS method. Time - concentration data were processed by the method of non-linear mixed effect modeling on MONOLIX 2021R1 software. The final population pharmacokinetic model is a two-compartment model, sequential zero (with prior lag time Tk01) followed by first-order absorption, and linear elimination. The volumes of distribution of the central and peripheral compartments were respectively 6.73 L and 1250 L; the clearance value Cl was 45.8 L/h. Janmahasatian’s Fat-free mass and age were found to be influential to the inter-individual variability of clearance.

Population pharmacokinetic modeling of treosulfan and rationale for dose recommendation in children treated for conditioning prior to allogeneic hematopoietic stem cell transplantation

Intravenously infused treosulfan was evaluated in adult and pediatric patients for conditioning regimen prior to allogeneic hematopoietic stem cell transplantation. A population pharmacokinetic (PK) model was initially developed on 116 adult and pediatric PK profiles from historical trials, to support treosulfan dose recommendations for children in 2 prospective trials. The aim was to assess and update the initial population PK model by inclusion of additional 83 pediatric PK profiles from these 2 trials. The final population PK model was 2-compartmental with dosing in the central compartment, linear elimination, and inter-compartmental clearance. Inter-individual variability was included on clearance (CL), central volume (V1), peripheral volume (V2), and inter-compartmental clearance (Q). The final model described an effect of the body surface area (BSA) on CL, V1, V2, and Q. The final model resulted in a modified dose recommendation for children and advises treosulfan doses of 10 g/m2, 12 g/m2, and 14 g/m2 for BSAs of <0.4 m2, ≥0.4 to <0.9 m2, and ≥0.9 m2, respectively. This simplified BSA-dependent dose recommendation was developed for children, ensuring a well comparable treosulfan exposure as a dose of 14 g/m2 in adults – irrespective of their age and without applying individual therapeutic drug monitoring.

Population Pharmacokinetic Modeling Using Polymyxin B Free Plasma Concentrations From Published Reports and Evaluation of Dosage Regimens Based on Monte Carlo Simulation in Critically Ill Patients.

A population pharmacokinetic(pop PK) model of polymyxin B was developed using nonlinear mixed-effects (NONMEM) modeling based on free plasma concentrations to determine whether dose adjustment is required in critically ill patients. One thousand pharmacokinetic profiles for virtual patients with a body weight of 70kg were simulated using Monte Carlo simulation at different dose scenarios, and area under the concentration-time curve of free drug (fAUC) was computed. The probability of target attainment (PTA) at each minimum inhibitory concentration (MIC) was calculated using fAUC/MIC as a pharmacokinetic/pharmacodynamic (PK/PD) index. The final population PK model was a 2-compartment model. PTA showed that 3.5mg/kg/day regimens of polymyxin B effectively achieved the fAUC/MIC target of 10 (one log10 kill) against Pseudomonas aeruginosa strains with MICof 1mg/L or less (PTA,90.7% or greater), while the dose regimen were ineffective against strains with an MIC of 2mg/L or greater (PTA, 56.9% or less). For Klebsiella pneumoniae, the fAUC/MIC target of 17.4 (one log10 kill) was achieved in more than 90.4% of cases for MICof 0.5mg/L or less with 3 mg/kg/day regimens. However, the PTA decreased dramatically as MICs increased above 1mg/L (PTA,56.1% or less). The polymyxin B dosage regimen of 3.5mg/kg/day and 3mg/kg/day are sufficient to treat P. aeruginosa infections with an MIC of 1mg/L or less and K. pneumoniae infections with an MIC of 0.5mg/L or less, respectively. The current recommended dose (1.5-3mg/kg/day) of polymyxin B appears inadequate to attain the PK/PD target for therapeutic efficacy against infections caused by P. aeruginosa and K. pneumoniae isolates when MIC is above the values.

Population Pharmacokinetic Analyses for Tebipenem after Oral Administration of Pro-Drug Tebipenem Pivoxil Hydrobromide.

Tebipenem pivoxil hydrobromide (TBP-PI-HBr) is an oral (PO) carbapenem pro-drug that is converted to the active moiety tebipenem in the enterocytes. Tebipenem has activity against multidrug-resistant Gram-negative pathogens, including extended-spectrum beta lactamase-producing Enterobacterales, and is being developed for the treatment of patients with complicated urinary tract infections (cUTI) and acute pyelonephritis (AP). The objectives of these analyses were to develop a population pharmacokinetic (PK) model for tebipenem using data from three phase 1 studies and one phase 3 study and to identify covariates that described the variability in tebipenem PK. Following construction of the base model, a covariate analysis was conducted. The model was then qualified by performing a prediction-corrected visual predictive check and evaluated by using a sampling-importance-resampling procedure. The final population PK data set was composed of data from 746 subjects who provided 3,448 plasma concentrations, including 650 patients (1,985 concentrations) with cUTI/AP. The final population PK model that best described tebipenem PK was found to be a two-compartment model with linear, first-order elimination and two transit compartments to describe the rate of drug absorption after PO administration of TBP-PI-HBr. The relationship between renal clearance (CLR) and creatinine clearance (CLcr), the most clinically significant covariate, was described using a sigmoidal Hill-type function. No dose adjustments are warranted on the basis of age, body size, or sex as none of these covariates were associated with substantial differences in tebipenem exposure in patients with cUTI/AP. The resultant population PK model is expected to be appropriate for model-based simulations and assessment of pharmacokinetic-pharmacodynamic relationships for tebipenem.

Population Pharmacokinetics of Posaconazole in Immune-Compromised Children and Assessment of Target Attainment in Invasive Fungal Disease.

Posaconazole (PSZ) is a triazole antifungal for the management of invasive fungal disease (IFD) in adults and children. Although PSZ is available as an intravenous (IV) solution, oral suspension (OS) and delayed-release tablets (DRTs), OS is the preferred formulation for pediatric use because of potential safety concerns associated with an excipient in the IV formulation and difficulty in swallowing intact tablets by children. However, poor biopharmaceutical characteristics of the OS formulation leads to an unpredictable dose-exposure profile of PSZ in children, potentially risking therapeutic failure. The goal of this study was to characterize the population pharmacokinetics (PK) of PSZ in immunocompromised children and assess therapeutic target attainment. Serum concentrations of PSZ were collected retrospectively from records of hospitalized patients. A population PK analysis was performed in a nonlinear mixed-effects modeling framework with NONMEM (v7.4). The PK parameters were scaled to body weight, then potential covariate effects were assessed. The final PK model was used to evaluate recommended dosing schemes through simulation of target attainment (as a percentage of the population having steady-state trough concentrations above the recommended target) using Simulx (v2021R1). Repeated measurement data of 202 serum concentrations of total PSZ were acquired from 47 immunocompromised patients between 1 and 21 years of age receiving PSZ either intravenously or orally, or both. A one-compartment PK model with first-order absorption and linear elimination best fit the data. The estimated absolute bioavailability (95% confidence interval) for suspension (Fs) was 16% (8-27%), which was significantly lower than the reported tablet bioavailability (Ft) [67%]. Fs was reduced by 62% and 75% upon concomitant administration with pantoprazole (PAN) and omeprazole (OME), respectively. Famotidine resulted in a reduction of Fs by only 22%. Both fixed dosing and weight-based adaptive dosing provided adequate target attainment when PAN or OME were not coadministered with the suspension. The results of this study revealed that both fixed and weight-based adaptive dosing schemes can be appropriate for target attainment across all PSZ formulations, including suspension. Additionally, covariate analysis suggests that concomitant proton pump inhibitors should be contraindicated during PSZ suspension dosing.

Population pharmacokinetics and exposure-response analysis of a single dose of sotrovimab in the early treatment of patients with mild to moderate COVID-19.

Sotrovimab is a recombinant human monoclonal antibody that has been shown to prevent progression to hospitalization or death in non-hospitalized high-risk patients with mild to moderate coronavirus disease 2019 following either intravenous (i.v.) or intramuscular (i.m.) administration. Population pharmacokinetic (PopPK) and exposure-response (ER) analyses were performed to characterize single dose sotrovimab pharmacokinetics (PK) and the relationship between exposure and response (probability of progression), as well as covariates that may contribute to between-participant variability in sotrovimab PK and efficacy following i.v. or i.m. administration. Sotrovimab PK was described by a two-compartment model with linear elimination; i.m. absorption was characterized by a sigmoid absorption model. PopPK covariate analysis led to the addition of the effect of body weight on systemic clearance and peripheral volume of distribution, sex on i.m. bioavailability and first-order absorption rate (KA), and body mass index on KA. However, the magnitude of covariate effect was not pronounced and was therefore not expected to be clinically relevant based on available data to date. For ER analysis, sotrovimab exposure measures were predicted using the final PopPK model. An ER model was developed using the exposure measure of sotrovimab concentration at 168 h that described the relationship between exposure and probability of progression within the ER dataset for COMET-TAIL. The number of risk factors (≤1 vs. >1) was incorporated as an additive shift on the model-estimated placebo response but had no impact on overall drug response. Limitations in the ER model may prevent generalization of these results to describe the sotrovimab exposure-progression relationship across severe acute respiratory syndrome-coronavirus 2 variants.

Voriconazole exposure is influenced by inflammation: A population pharmacokinetic model.

Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM. To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care. Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots. In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (Vmax). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean Vmax was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates. This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately.

Population pharmacokinetics and dosing optimisation of imipenem in critically ill patients

ObjectiveThe objective of this study was to explore factors that affect the clearance of imipenem in critically ill patients and to provide a dosing regimen for such patients.MethodsA prospective open-label...

Population pharmacokinetics of nalbuphine in patients undergoing general anesthesia surgery.

Purpose: The aim of this study was to build a population pharmacokinetics (PopPK) model of nalbuphine and to estimate the suitability of bodyweight or fixed dosage regimen. Method: Adult patients who were undergoing general anesthetic surgery using nalbuphine for induction of anesthesia were included. Plasma concentrations and covariates information were analyzed by non-linear mixed-effects modeling approach. Goodness-of-fit (GOF), non-parametric bootstrap, visual predictive check (VPC) and external evaluation were applied for the final PopPK model evaluation. Monte Carlo simulation was conducted to assess impact of covariates and dosage regimens on the plasma concentration to nalbuphine. Results: 47 patients aged 21-78years with a body weight of 48-86kg were included in the study. Among them, liver resection accounted for 14.8%, cholecystectomy for 12.8%, pancreatic resection for 36.2% and other surgeries for 36.2%. 353 samples from 27 patients were enrolled in model building group; 100 samples from 20 patients were enrolled in external validation group. The results of model evaluation showed that the pharmacokinetics of nalbuphine was adequately described by a two-compartment model. The hourly net fluid volume infused (HNF) was identified as a significant covariate about the intercompartmental clearance (Q) of nalbuphine with objective function value (OFV) decreasing by 9.643 (p < 0.005, df = 1). Simulation results demonstrated no need to adjust dosage based on HNF, and the biases of two dosage methods were less than 6%. The fixed dosage regimen had lower PK variability than the bodyweight regimen. Conclusion: A two-compartment PopPK model adequately described the concentration profile of nalbuphine intravenous injection for anesthesia induction. While HNF can affect the Q of nalbuphine, the magnitude of the effect was limited. Dosage adjustment based on HNF was not recommended. Furthermore, fixed dosage regimen might be better than body weight dosage regimen.