Comparison of manual versus ambulatory blood pressure measurements with pharmacokinetic-pharmacodynamic modeling of antihypertensive compounds: application to moxonidine

Optimization of blood pressure measurement practices for pharmacodynamic analyses of tyrosine-kinase inhibitors

Blood pressure measurements form a critical component of adverse event monitoring for tyrosine kinase inhibitors, but might also serve as a biomarker for dose titrations. This study explored the impact of various sources of within-individual variation on blood pressure readings to improve measurement practices and evaluated the utility for individual- and population-level dose selection. A pharmacokinetic-pharmacodynamic modeling framework was created to describe circadian blood pressure changes, inter- and intra-day variability, changes from dipper to non-dipper profiles, and the relationship between drug exposure and blood pressure changes over time. The framework was used to quantitatively evaluate the influence of physiological and pharmacological aspects on blood pressure measurements, as well as to compare measurement techniques, including office-based, home-based, and ambulatory 24-h blood pressure readings. Circadian changes, as well as random intra-day and inter-day variability, were found to be the largest sources of within-individual variation in blood pressure. Office-based and ambulatory 24-h measurements gave rise to potential bias (>5 mmHg), which was mitigated by model-based estimations. Our findings suggest that 5-8 consecutive, home-based, measurements taken at a consistent time around noon, or alternatively within a limited time frame (e.g., 8.00 a.m. to 12.00 p.m. or 12.00 p.m. to 5.00 p.m.), will give rise to the most consistent blood pressure estimates. Blood pressure measurements likely do not represent a sufficiently accurate method for individual-level dose selection, but may be valuable for population-level dose identification. A user-friendly tool has been made available to allow for interactive blood pressure simulations and estimations for the investigated scenarios.

Cardiovascular Safety Assessment in Early-Phase Clinical Studies: A Meta-Analytical Comparison of Exposure-Response Models

Exposure‐response analysis of QT interval in clinical studies has been proposed as a thorough QT study alternative. Many exposure‐response model structures have been proposed for cardiovascular (CV) safety markers, but few studies have compared models across multiple drugs. To recommend preferred drug‐effect exposure‐response models on vital signs and electrocardiogram (ECG) intervals, an individual‐level model‐based meta‐analysis (39 studies and 1,291 subjects) compared 90 model structures. Models were selected to describe the data and cross‐validate studies on the same drug. The most commonly selected baseline model was an unstructured model (estimation of a value at each study nominal time) for all measures but blood pressure. The unstructured model estimated a better cross‐validated drug‐effect when considering all markers. A linear model was the most commonly selected to characterize drug‐effect on all markers. We propose these models as a starting point assisting with CV safety exposure‐response assessment in nondedicated small studies with healthy subjects.

A cyclic fluctuation model for 24-h ambulatory blood pressure monitoring in Chinese patients with mild to moderate hypertension

AIM

The conventional method for analyzing 24-h ambulatory blood pressure monitoring (24-h ABPM) is insufficient to deal with the large amount of data collected. The aim of this study was to develop a novel cyclic fluctuation model for 24-h ABPM in Chinese patients with mild to moderate hypertension.

METHODS

The data were obtained from 4 independent antihypertensive drug clinical trials in Chinese patients with mild to moderate hypertension. The measurements of 24-h ABPM at the end of the placebo run-in period in study 1 were used to develop the cyclic fluctuation model. After evaluated, the structural model was used to analyze the measurements in the other 3 studies. Models were fitted using NONMEM software.

RESULTS

The cyclic fluctuation model, which consisted of 2 cosine functions with fixed-effect parameters for rhythm-adjusted 24-h mean blood pressure, amplitude and phase shift, successfully described the blood pressure measurements of study 1. Model robustness was validated by the bootstrap method. The measurements in the other 3 studies were well described by the same structural model. Moreover, the parameters from all the 4 studies were very similar. Visual predictive checks demonstrated that the cyclic fluctuation model could predict the blood pressure fluctuations in the 4 studies.

CONCLUSION

The cyclic fluctuation model for 24-h ABPM deepens our understanding of blood pressure variability, which will be beneficial for drug development and individual therapy in hypertensive patients.

Model-based determination of abatacept exposure in support of the recommended dose for Japanese rheumatoid arthritis patients

The objective of this study was to provide support for a body weight-tiered dosing regimen by characterizing abatacept pharmacokinetics (PK) and the relationship between exposure and the ACR20 (American College of Rheumatology criteria for 20% improvement) response in Japanese patients with rheumatoid arthritis (RA). A population PK model was developed using NONMEM with 2,535 samples from 344 Japanese RA patients in two clinical trials. The exposure-response relationship was characterized using a Generalized Estimating Equation (GEE) logistic regression model, with time-varying actual trough concentrations and ACR20 responder rates over 6 months in a randomized, placebo-controlled phase 2 trial for stable methotrexate. Abatacept exposure was well characterized using a linear, two-compartment model, in which body weight and the empirically calculated glomerular filtration rate were significant covariates for clearance. The ACR20 response model was developed by examining the quasi-likelihood information criterion, and the cumulative logit in the final model was specified by the log-transformed trough concentration. The predicted ACR20 responder rate was consistent with the actual values in the clinical trial and this model revealed trough concentrations higher than the recommended body weight-tiered dose are unlikely to result in substantial increases in clinical efficacy. Considering that ACR20 is a longitudinal binary variable and the response to RA treatment is delayed, the GEE model was useful for predicting the probability of an ACR20 response. In conclusion, the same dosing regimen as non-Japanese patients is recommended because a body weight-tiered dosing regimen achieves similar exposures across the wide range of body weight.

Population pharmacokinetic model for daunorubicin and daunorubicinol coadministered with zosuquidar.3HCl (LY335979)

PURPOSE

The impact of zosuquidar.3HCl, an inhibitor of P-glycoprotein, on the pharmacokinetics of daunorubicin and daunorubicinol was examined in a phase I trial using a population approach. Pharmacokinetic and pharmacodynamic properties of zosuquidar.3HCl were also determined.

METHODS

The pharmacokinetics of daunorubicin and daunorubicinol were studied following daunorubicin administration on day 1 (50 mg/m2 i.v. infusion over 10 min) alone and on day 3 concomitantly with zosuquidar.3HCl (i.v. 200 or 300 mg/m2 over 6 h or 400 mg over 3 h). Of a total of 18 patients entered, 16 with acute leukemia completed the study.

RESULTS

A three-compartment pharmacokinetic model adequately described daunorubicin concentration-time profiles. Five- and four-compartment models adequately described the daunorubicin-daunorubicinol pharmacokinetics in the absence and presence of zosuquidar.3HCl, respectively. The impact of zosuquidar.3HCl on coadministered daunorubicin was minimal, with a 10% reduction in daunorubicin clearance. The model predicted a 50% decrease in daunorubicinol apparent clearance in the presence of zosuquidar.3HCl. A direct concentration-effect relationship between zosuquidar.3HCl concentrations and inhibition of rhodamine 123 (Rh123) efflux in CD56 lymphocytes was defined by a sigmoid E(max) model. The IC(50) was 31.7 microg/l. The zosuquidar.3HCl dosing regimen led to concentrations in excess of the IC(90) (169.6 microg/l) and provided maximal P-glycoprotein inhibition during the distribution phases of daunorubicin.

CONCLUSIONS

The decrease in daunorubicin and daunorubicinol clearance in the presence of zosuquidar.3HCl likely reflects inhibition of P-glycoprotein in the bile canaliculi impeding their biliary excretion. The results need to be interpreted carefully due to the sequential nature of daunorubicin administration and analysis.

THEINTEGRATION OFPHARMACOKINETICS ANDPHARMACODYNAMICS: Understanding Dose-Response

Pharmacokinetic (PK) and pharmacodynamic (PD) studies have proven to be powerful and instructive tools, particularly in elucidating important aspects of human pharmacology. Nevertheless, they remain imperfect tools in that they only allow researchers to indirectly extrapolate, through computational modeling, the dynamic processes of drug action. Furthermore, neither tool alone provides a complete nor necessarily relevant picture of drug action. This review explores the utility and applications of PK and PD in the study of drugs, provides examples of lessons learned from their application to studies of human pharmacology, points out some of their limitations, and advances the thesis that these tools ideally should be employed together in an integrated approach. As we continue to apply these tools across the continuum of age and disease, they provide a powerful means to enhance our understanding of drug action, drug interactions, and intrinsic host factors that influence pharmacologic response.