Evaluation of Approaches to Deal with Low-Frequency Nuisance Covariates in Population Pharmacokinetic Analyses

Covariate modeling in pharmacometrics: General points for consideration

Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

External Evaluation of Population Pharmacokinetic Models for High-Dose Methotrexate in Adult Patients with Hematological Tumors

Currently, numerous population pharmacokinetic (popPK) models for methotrexate (MTX) have been published for estimating PK parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high-dose MTX (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The software package NONMEM was used to perform an external evaluation for each model, including prediction-based diagnosis, simulation-based diagnosis, and Bayesian forecasting. The simulation-based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, 7 candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. The published popPK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our data set. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.

External evaluation of population pharmacokinetic models for voriconazole in Chinese adult patients with hematological malignancy

OBJECTIVES

Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities.

METHODS

The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations.

RESULTS

A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given.

CONCLUSIONS

The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice.

Evaluation of pharmacogenomics and hepatic nuclear imaging-related covariates by population pharmacokinetic models of irinotecan and its metabolites

BACKGROUND

Body surface area (BSA)-based dosing of irinotecan (IR) does not account for its pharmacokinetic (PK) and pharmacodynamic (PD) variabilities. Functional hepatic nuclear imaging (HNI) and excretory/metabolic/PD pharmacogenomics have shown correlations with IR disposition and toxicity/efficacy. This study reports the development of a nonlinear mixed-effect population model to identify pharmacogenomic and HNI-related covariates that impact on IR disposition to support dosage optimization.

METHODS

Patients had advanced colorectal cancer treated with IR combination therapy. Baseline blood was analysed by Affymetrix DMET™ Plus Array and, for PD, single nucleotide polymorphisms (SNPs) by Sanger sequencing. For HNI, patients underwent ^99mTc-IDA hepatic imaging, and data was analysed for hepatic extraction/excretion parameters. Blood was taken for IR and metabolite (SN38, SN38G) analysis on day 1 cycle 1. Population modelling utilised NONMEM version 7.2.0, with structural PK models developed for each moiety. Covariates include patient demographics, HNI parameters and pharmacogenomic variants.

RESULTS

Analysis included (i) PK data: 32 patients; (ii) pharmacogenomic data: 31 patients: 750 DMET and 22 PD variants; and (iii) HNI data: 32 patients. On initial analysis, overall five SNPs were identified as significant covariates for CL_SN38. Only UGT1A3_c.31 T > C and ABCB1_c.3435C > T were included in the final model, whereby CL_SN38 reduced from 76.8 to 55.1%.

CONCLUSION

The identified UGT1A3_c.31 T > C and ABCB1_c.3435C > T variants, from wild type to homozygous, were included in the final model for SN38 clearance.

Population Pharmacokinetics and Pharmacodynamics of Apixaban Linking Its Plasma Concentration to Intrinsic Activated Coagulation Factor X Activity in Japanese Patients with Atrial Fibrillation

Apixaban is used in the prevention and treatment of patients with deep vein thrombosis or pulmonary embolism, and in the prevention of stroke or systemic embolism in patients with nonvalvular atrial fibrillation (AF). In this study, we aimed to elucidate intrinsic factors affecting efficacy of apixaban by conducting population pharmacokinetic and pharmacodynamic analysis using data from 81 Japanese AF patients. The intrinsic FXa activity was determined to assess the pharmacodynamic effect of apixaban. The pharmacokinetic and pharmacodynamic profiles were described based on a one-compartment model with first-order absorption and a maximum inhibitory model, respectively. Pharmacokinetic and pharmacodynamic analysis was conducted using a nonlinear mixed effect modeling program. The population pharmacokinetic parameters of apixaban were fixed at the reported values in our recent study. The population mean of half-maximal inhibitory concentration (IC₅₀) of apixaban was estimated to be 45.3 ng/mL. The population mean IC₅₀ decreased 27.7% for patients with heart failure, but increased 55% for patients with a medical history of cerebral infarction. In contrast, no covariates affected the population mean of baseline of intrinsic FXa activity (BASE) and maximum effect (I_max) value of apixaban. The population mean of BASE and I_max value were estimated to be 40.2 and 38.4 nmol/min/mg protein, respectively. The present study demonstrates for the first time that the co-morbidity of heart failure as well as the medical history of cerebral infarction are an intrinsic factor affecting the pharmacodynamics of apixaban.

Postoperative complications as a predictor for survival after liver transplantation - proposition of a prognostic score

BACKGROUND

Liver transplantation is major surgery with a high risk of complications. Existing scoring systems for evaluating complications after surgery are not specific for liver transplantation. Nor are they designed to evaluate the relation to recipient survival or graft loss. We wished to uncover the relation between postoperative complications and one-year risk of death or retransplantation, and to develop a prognostic score for complications based on our findings.

METHOD

The study was a retrospective cohort study including 253 adult liver recipients. Thirty-days postoperative complications were registered using the Clavien-Dindo classification. A prognostic score was developed based on types, severity, and quantity of complications.

RESULTS

A total of 1113 complications occurred in 233 (92.1%) of the patients. One-year mortality or graft loss was associated with graft, biliary, surgical, systemic, pulmonary, cardiovascular, renal, and infectious complication but not with neurologic or gastrointestinal complications. The developed score was more accurate in predicting the outcome than both the modified Clavien-Dindo score and the Comprehensive Complication Index.

CONCLUSION

Types, severity, and quantity of different postoperative complications after liver transplantation are not equally important. The proposed score may focus attention on treating or preventing complications with strong relation to recipient mortality or graft loss.

Population pharmacokinetics and pharmacogenomics of apixaban in Japanese adult patients with atrial fibrillation

AIMS

This study aimed to analyse the effects of genetic polymorphisms in drug transporters and metabolizing enzymes, and clinical laboratory data on the pharmacokinetic parameters of apixaban.

METHODS

Data were collected from 81 Japanese patients with atrial fibrillation. Pharmacogenomic data were stratified by ABCB1, ABCG2 and CYP3A5 polymorphisms. The pharmacokinetic profile of apixaban was described by a one-compartment model with first-order absorption. Population pharmacokinetic analysis was conducted using a nonlinear mixed effect modelling (NONMEM™) program.

RESULTS

The nonlinear relationship between oral clearance (CL/F) of apixaban and creatinine clearance (Ccr) was observed. The population mean of CL/F for a typical patient (Ccr value of 70 ml min^-1 ) with the CYP3A5*1/*1 and ABCG2 421C/C or C/A genotypes was estimated to be 3.06 l h^-1 . When Ccr values were set to the typical value, the population mean of CL/F was 1.52 times higher in patients with the CYP3A5*1/*1 genotype compared with patients with the CYP3A5*1/*3 or *3/*3 genotype, while the population mean of CL/F was 1.49 times higher in patients with the ABCG2 421C/C or C/A genotype compared with patients with the ABCG2 421A/A genotype. However, no covariates affected the population mean of the apparent volume of distribution (Vd/F) of apixaban. The population mean of Vd/F was estimated to be 24.7 l.

CONCLUSION

The present study suggests that the ABCG2 421A/A and CYP3A5*3 genotypes and renal function are intrinsic factors affecting apixaban pharmacokinetics. These findings may provide useful information for precision medicine using apixaban, to avoid the risk of adverse reactions.

Population pharmacokinetic analysis of tacrolimus in Chinese myasthenia gravis patients

The importance of tacrolimus in the treatment of myasthenia gravis (MG) as a substitute for corticosteroid-dependent immunosuppressive therapy is increasing. Thus far, however, no population pharmacokinetic (PopPK) analysis of tacrolimus in treating MG patients has been published. This article aimed to construct a PopPK model of tacrolimus for Chinese MG patients with the goal of improving its performance in MG treatment. A total of 253 trough concentration records were obtained from 83 Chinese MG patients. The effects of demographics, lifestyle and health status, biochemical test data, disease progression and treatment-related information (including co-administered medications) as covariates on the various parameters were investigated. The covariate selection was based on biological plausibility, clinical significance, statistical significance and reduction in inter-individual variability (IIV). Bootstrap and normalized prediction distribution error (NPDE) analysis were performed to validate the final model. A one-compartment PopPK model with first-order elimination and a fixed absorption phase was constructed. The estimated apparent oral clearance (CL/F) and apparent oral volume of distribution (V/F) were 3.6 L/h and 1700 L, respectively, in the MG patients. Hematocrit and blood urea nitrogen were identified as two covariates that significantly influenced the CL/F. Immunoglobulin treatment (PRO) also had the potential to influence V/F, which was consistent with the clinical observations and the high protein-binding property of tacrolimus. Other covariates including age, weight, gender and co-administered medications had no obvious influence on CL/F or V/F. The first PopPK model of tacrolimus in MG patients was established. The identified covariates were of biological plausibility and clinical importance to help individualize the dosing schedule in MG patients.