Prediction of steady-state plasma concentrations of olanzapine in Chinese Han in patients based on a retrospective population pharmacokinetic model

Purpose: To develop robust methods of establishing a population pharmacokinetics (Pop-PK) model of olanzapine, using existing hospital in-patient information, in order to predict the steady-state plasma concentration of olanzapine tablets in Chinese Han inpatients, thus providing guidance for individualized therapy for mental disorders.Methods: A retrospective study analyzing and predicting the steady-state plasma olanzapineconcentration was performed using nonlinear mixed-effect modeling (Phoenix® NLME8). The effects of ten potential covariates, including age, gender, Body Mass Index, fasting lipid, family history, alcohol and smoking status in 107 Chinese Han patients with steady-state plasma olanzapine concentration were collected from the hospital information system (HIS) in Wuhan Mental Health Center from Feb 2017 to Jul 2019.Results: The final model was validated using bootstrap and visual predictive check (VPC) and was found to fit the one-compartment mixed error model. Smoking status was found to be the only factor affecting olanzapine tablets clearance. The standard Pop-PK parameters apparent volume of distribution (VL/F) and clearance (CL/F) were 223 L and 12.4 Lꞏh-1, respectively.Conclusion: The Pop-PK model for olanzapine established with the data from HIS is effective inpredicting the plasma olanzapine tablets concentration of individual Chinese in-patients. This Pop-PK model approach can now be adapted to optimize other antipsychotic drugs.

Population Pharmacokinetic Modelling of the Complex Release Kinetics of Octreotide LAR: Defining Sub-Populations by Cluster Analysis

The aim of the study is to develop a population pharmacokinetic (PPK) model, of Octreotide long acting repeatable (LAR) formulation in healthy volunteers, which describes the highly variable, multiple peak absorption pattern of the pharmacokinetics of the drug, in individual and population levels. An empirical absorption model, coupled with a one-compartment distribution model with linear elimination was found to describe the data well. Absorption was modelled as a weighted sum of a first order and three transit compartment absorption processes, with delays and appropriately constrained model parameters. Identifiability analysis verified that all twelve parameters of the structural model are identifiable. A machine learning method, i.e., cluster analysis, was performed as pre-processing of the PK profiles, to define subpopulations, before PPK modelling. It revealed that 13% of the patients deviated considerably from the typical absorption pattern and allowed better characterization of the observed heterogeneity and variability of the study, while the approach may have wider applicability in building PPK models. The final model was evaluated by goodness of fit plots, Visual Predictive Check plots and bootstrap. The present model is the first to describe the multiple-peak absorption pattern observed after octreotide LAR administration and may be useful to provide insights and validate hypotheses regarding release from PLGA-based formulations.

A Repeated Time-to-Positive Symptoms Improvement among Malaysian Patients with Schizophrenia Spectrum Disorders Treated with Clozapine

Clozapine remains the drug of choice for resistant schizophrenia. However, its dose-response relationship is still controversial. The current investigation aimed to develop a repeated time-to-positive symptoms improvement following the onset of clozapine treatment in Malaysian schizophrenia spectrum disorder patients. Data from patients’ medical records in the Psychiatric Clinic, Penang General Hospital, were retrospectively analyzed. Several parametric survival models were evaluated using nonlinear mixed-effect modeling software (NONMEM 7.3.0). Kaplan–Meier-visual predictive check (KM-VPC) and sampling-importance resampling (SIR) methods were used to validate the final model. A total of 116 patients were included in the study, with a mean follow-up of 306 weeks. Weibull hazard function best fitted the data. The hazard of positive symptoms improvement decreased 4% for every one-year increase in age over the median of 41 years (adjusted hazard ratio (aHR), 0.96; 95% confidence intervals (95% CI), (0.93–0.98)). However, patients receiving a second atypical antipsychotic agent had four-folds higher hazard (aHR, 4.01; 95% CI, (1.97–7.17)). The hazard increased 2% (aHR, 1.02; 95% CI, (1.01–1.03)) for every 1 g increase in the clozapine six months cumulative dose over the median of 34 g. The developed model provides essential information on the hazard of positive symptoms improvement after the first clozapine dose administration, including modifiable predictors of high clinical importance.

Development of A Physiological-Based Pharmacokinetic Model to Predict Bendamustine Exposure in Paediatric Patients

Background the study aimed to predict bendamustine pharmacokinetics in paediatric patients by employing physiological-based pharmacokinetic (PBPK) model that considers age-dependent physiological maturity. Methods Using PK-Sim, a paediatric PBPK model was constructed based on a validated PBPK adult model using the recommended paediatric dose at 120 mg/m2 bendamustine intravenous (IV) infusion for 60 minutes and age-dependent mechanistic scaling. Parameter optimisation was done based on model fitting to the observed in vivo population pharmacokinetic (PK) data using the visual predictive check. The final paediatric PBPK model was extrapolated to various paediatric age categories (term newborn, infant, toddler, preschool, school-age, adolescent) for PK estimate and comparisons. The PBPK paediatric model was compared with the adult model, and PK comparisons were made for different age categories with the reference paediatric model. Results The model estimated a bendamustine fraction unbound of 4% in a paediatric patient. Renal clearance, biliary clearance and total hepatic clearance in a typical child were 1.38 mL/min/kg, 0.02 mL/min/kg and 13.76 mL/min/kg respectively. The paediatric model was comparable to the adult model. Compared to a typical child, a term newborn has the highest estimated maximum plasma concentration (Cmax) and systemic exposure (AUC0-24h), which were 1.24-fold respectively. Clearance in term newborn and infant were 1.4-1.5-fold higher than a typical child. Conclusions We developed a bendamustine PBPK model for a paediatric patient with relapsed/refractory Acute Lymphocytic Leukaemia (ALL) and Acute Myeloid Leukaemia (AML). The current model may be useful to estimate systemic exposure in paediatric for various age categories in different settings. More in vivo studies are needed in paediatric patients to challenge the robustness of this model.

Population Pharmacokinetics of Lithium in Young Pediatric Patients With Intellectual Disability

Background: Lithium is a well-established treatment for bipolar disorders and has been shown to be neuroprotective, and thus low doses might be useful for the treatment of childhood brain injury and neurological sequelae. However, pharmacokinetic (PK) data in children are limited. This study was to investigate the PKs after oral administration of low-dose lithium carbonate in young children with intellectual disability.Methods: Fifty-two children with intellectual disability aged 4–10 years old were enrolled. A series of blood samples were collected after a single-dose administration of lithium carbonate. The serum lithium concentration was measured using a validated ion chromatography assay, and the PK concentration data were modeled using a nonlinear mixed effect model in the NONMEM program.Results: The lithium concentration over time was adequately described by a two-compartment disposition, with a transient absorption and first-order elimination process. The inclusion of body weight as an allometric factor significantly improved the model fit, but age and gender were not associated with the PKs of lithium. The clearance, central volume, inter-compartmental clearance, and peripheral volume estimates from the final population PK model were 0.98 L/h, 13.1 L, 0.84 L/h, and 8.2 L for children with a body weight of 20 kg. The model evaluation suggested that there is no obvious discrepancy between the observations and predictions in the proposed model. A visual predictive check demonstrated the good predictive performance of the final model.Conclusions: The lithium PK properties in young children were similar to those in older children and adults. The proposed model can be used for further PK/PD analysis to optimize the dosage regimen of lithium in children.

Development of a Population Pharmacokinetic Model for Cyclosporine from Therapeutic Drug Monitoring Data

Aim. To develop a population pharmacokinetic model for Uruguayan patients under treatment with cyclosporine (CsA) that can be applied to TDM. Patients and Methods. A total of 53 patients under treatment with CsA were included. 37 patients with at least one pharmacokinetic profile described with four samples were considered for model building, while the remaining 16 were considered for the assessments of predictive performances. Pharmacokinetic parameter estimation was performed using a nonlinear mixed effect modelling implemented in the Monolix® software (version 2019R1, Lixoft, France); meanwhile, simulations were performed in R v.3.6.0 with the mlxR package. Results. A two-compartment model with a first-order disposition model including lag time was used as a structural model. The final model was internally validated using prediction corrected visual predictive check (pcVPC) and other graphical diagnostics. A total of 621 CsA steady-state concentrations were analyzed for model development. Population estimates for the absorption constant (ka) and lag time were 0.523 h-1 and 0.512 h, respectively; apparent clearance (CL/F) was 30.3 L/h ( relative standard error RSE ± 8.25 % ) with an interindividual variability of 39.8% and interoccasion variability of 38.0%; meanwhile, apparent clearance of distribution (Q/F) was 17.0 L/h ( RSE ± 12.1 % ) with and interindividual variability of 53.2%. The covariate analysis identified creatinine clearance (ClCrea) as an individual factor influencing the Cl of CsA. The predictive capacity of the population model was demonstrated to be effective since predictions made for new patients were accurate for C1 and C2 (MPPEs below 50%). Bayesian forecasting improved significantly in the second and third occasions. Conclusion. A population pharmacokinetic model was developed to reasonably estimate the individual cyclosporine clearance for patients. Hence, it can be utilized to individualize CsA doses for prompt and adequate achievement of target blood concentrations of CsA.

Which Analysis Approach Is Adequate to Leverage Clinical Microdialysis Data? A Quantitative Comparison to Investigate Exposure and Reponse Exemplified by Levofloxacin

Purpose Systematic comparison of analysis methods of clinical microdialysis data for impact on target-site drug exposure and response. Methods 39 individuals received a 500 mg levofloxacin short-term infusion followed by 24-h dense sampling in plasma and microdialysate collection in interstitial space fluid (ISF). ISF concentrations were leveraged using non-compartmental (NCA) and compartmental analysis (CA) via (ii) relative recovery correction at midpoint of the collection interval (midpoint-NCA, midpoint-CA) and (ii) dialysate-based integrals of time (integral-CA). Exposure and adequacy of community-acquired pneumonia (CAP) therapy via pharmacokinetic/pharmacodynamic target-attainment (PTA) analysis were compared between approaches. Results Individual AUCISF estimates strongly varied for midpoint-NCA and midpoint-CA (≥52.3%CV) versus integral-CA (≤32.9%CV) owing to separation of variability in PK parameters (midpoint-CA = 46.5%–143%CVPK, integral-CA = 26.4%–72.6%CVPK) from recovery-related variability only in integral-CA (41.0%–50.3%CVrecovery). This also led to increased variability of AUCplasma for midpoint-CA (56.0%CV) versus midpoint-NCA and integral-CA (≤33.0%CV), and inaccuracy of predictive model performance of midpoint-CA in plasma (visual predictive check). PTA analysis translated into 33% of evaluated patient cases being at risk of incorrectly rejecting recommended dosing regimens at CAP-related epidemiological cut-off values. Conclusions Integral-CA proved most appropriate to characterise clinical pharmacokinetics- and microdialysis-related variability. Employing this knowledge will improve the understanding of drug target-site PK for therapeutic decision-making.

External Evaluation of Vancomycin Population Pharmacokinetic Models at Two Clinical Centers

Background: Numerous vancomycin population pharmacokinetic models in neonates have been published; however, their predictive performances remain unknown. This study aims to evaluate their external predictability and explore the factors that might affect model performance.Methods: Published population pharmacokinetic models in neonates were identified from the literature and evaluated using datasets from two clinical centers, including 171 neonates with a total of 319 measurements of vancomycin levels. Predictive performance was assessed by prediction- and simulation-based diagnostics and Bayesian forecasting. Furthermore, the effect of model structure and a number of identified covariates was also investigated.Results: Eighteen published pharmacokinetic models of vancomycin were identified after a systematic literature search. Using prediction-based diagnostics, no model had a median prediction error of ≤ ± 15%, a median absolute prediction error of ≤30%, and a percentage of prediction error that fell within ±30% of >50%. A simulation-based visual predictive check of most models showed there were large deviations between observations and simulations. After Bayesian forecasting with one or two prior observations, the predicted performance improved significantly. Weight, age, and serum creatinine were identified as the most important covariates. Moreover, employing a maturation model based on weight and age as well as nonlinear model to incorporate serum creatinine level significantly improved predictive performance.Conclusion: The predictability of the pharmacokinetic models for vancomycin is closely related to the approach used for modeling covariates. Bayesian forecasting can significantly improve the predictive performance of models.

Population Pharmacokinetics and Dose Optimization of Ganciclovir in Critically Ill Children

Objective: The present study aims to establish a population pharmacokinetic model of ganciclovir and optimize the dosing regimen in critically ill children suffering from cytomegalovirus related disease.Methods: A total of 104 children were included in the study. The population pharmacokinetic model was developed using the Phoenix NLME program. The final model was validated by diagnostic plots, nonparametric bootstrap, visual predictive check, and normalized prediction distribution errors. To further evaluate and optimize the dosing regimens, Monte Carlo simulations were performed. Moreover, the possible association between systemic exposure and hematological toxicity were also monitored in the assessment of adverse events.Results: The ganciclovir pharmacokinetics could be adequately described by a one-compartment model with first-order elimination along with body weight and estimated glomerular filtration rate as significant covariates. As showed in this study, the typical population parameter estimates of apparent volume of distribution and apparent clearance were 11.35 L and 5.23 L/h, respectively. Simulations indicated that the current regimen at a dosage of 10 mg/kg/d would result in subtherapeutic exposure, and elevated doses might be required to reach the target ganciclovir level. No significant association between neutropenia, the most frequent toxicity reported in our study (19.23%), and ganciclovir exposure was observed.Conclusion: A population pharmacokinetic model of intravenous ganciclovir for critically ill children with cytomegalovirus infection was successfully developed. Results showed that underdosing of ganciclovir was relatively common in critically ill pediatric patients, and model-based approaches should be applied in the optimizing of empiric dosing regimens.

Semi-Mechanistic Modeling of HY-021068 Based on Irreversible Inhibition of Thromboxane Synthetase

Background: HY-021068 [4-(2-(1H-imidazol-1-yl) ethoxy)-3-methoxybenzoate], developed by Hefei Industrial Pharmaceutical Institute Co., Ltd. (Anhui, China), is a potential thromboxane synthetase inhibitor under development as an anti-platelet agent for the treatment of stroke. A semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model was developed to characterize the PK of HY-021068 and its platelet aggregation inhibitory effect in beagle dogs.Method: Beagle dogs received single oral administration of 2.5 mg/kg HY-021068 or consecutively oral administration of 5 mg/kg HY-021068 once daily for 7 days. The plasma concentration of HY-021068 and the platelet aggregation rate (PAR) were determined by liquid chromatography tandem-mass spectrometry (LC‐MS/MS) assay and a photometric method, respectively. The PK/PD data was sequentially fitted by Phoenix NLME. The PK/PD parameters of HY-021068 in beagle dogs were estimated by 2.5 and 5 mg/kg dosing on the 1st day, and then used to simulate the PAR of HY-021068 on the 7th day after 5 mg/kg dosing daily.Result: A one-compartment model with saturable Michaelis-Menten elimination was best fitted to the PK of HY-021068. A mechanistic PD model based on irreversible inhibition of thromboxane synthetase was constructed to describe the relationship between plasma concentration of HY-021068 and PAR. Diagnostic plots showed no obvious bias. Visual predictive check confirmed the stability and reliability of the model. Most of PK/PD observed data on the 7th day after 5 mg/kg dosing fell in the 90% prediction interval.Conclusion: We established a semi-mechanistic PK/PD model for characterizing the PK of HY-021068 and its anti-platelet effect in beagle dogs. The model can be used to predict the concentration and PAR under different dosage regimen of HY-021068, and might be served as a reference for dose design in the future clinical studies.