Nonlinear mixed effects modeling of the diurnal blood pressure profile in a multiracial population

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.

Circadian Rhythm of Blood Pressure of Dipper and Non-dipper Patients With Essential Hypertension: A Mathematical Modeling Approach

Blood pressure in humans presents a circadian variation profile with a morning increase, a small postprandial valley, and a deeper descent during night-time rest. Under certain conditions, the nocturnal decline in blood pressure can be reduced or even reversed (non-dipper), which is related to a significantly worse prognosis than a normal fall pattern (dipper). Despite several advances in recent years, our understanding of blood pressure's temporal structure, its sources and mechanisms is far from complete. In this work, we developed an ordinary differential equation-based mathematical model capable of capturing the circadian rhythm of blood pressure in dipper and non-dipper patients with arterial hypertension. The model was calibrated by means of global optimization, using 24-h data of systolic and diastolic blood pressure, physical activity, heart rate, blood glucose and norepinephrine, obtained from the literature. After fitting the model, the mean of the normalized error for each data point was <0.2%, and confidence intervals indicate that all parameters were identifiable. Sensitivity analysis allowed identifying the most relevant parameters and therefore inferring the most important blood pressure regulatory mechanisms involved in the non-dipper status, namely, increase in sympathetic over parasympathetic nervous tone, lower influence of physical activity on heart rate and greater influence of physical activity and glucose on the systemic vascular resistance. In summary, this model allows explaining the circadian rhythm of blood pressure and deepening the understanding of the underlying mechanisms and interactions integrating the results of previous works.

Characterization of circadian blood pressure patterns using non-linear mixed effects modeling

Characterizing the time course of baseline or pre-drug blood pressure is important in acquiring unbiased estimates of antihypertensive drug effect. In this study, we recruited 23 healthy male volunteers and measured systolic (SBP) and diastolic blood pressure (DBP) over 24 hours on an hourly basis. Using a non-linear mixed effects model, circadian rhythm observed in blood pressure measurements was described by incorporating two cosine functions with periods 24 and 12 hours. A mixture model was applied to identify subgroups exhibiting qualitatively different circadian rhythms. Our results suggested that 78% of the study population, defined as ‘dippers’, demonstrated a typical circadian profile with a morning rise and a nocturnal dip. The remaining 22% of the subjects defined as ‘non-dippers’, however, were not adequately described using the typical profile and demonstrated an elevation of blood pressure during night-time. Covariate search identified weight as being positively correlated with mesor of SBP. Visual predictive checks using 1,000 simulated datasets were performed for model validation. Observations were in agreement with predicted values in ‘dippers’, but deviated slightly in ‘non-dippers’. Our work is expected to serve as a useful reference in assessing systematic intra-day blood pressure fluctuations and antihypertensive effects as well as assessing drug safety of incrementally modified drugs.

Morning surge in blood pressure using a random-effects multiple-component cosinor model

Blood pressure (BP) fluctuates throughout the day. The pattern it follows represents one of the most important circadian rhythms in the human body. For example, morning BP surge has been suggested as a potential risk factor for cardiovascular events occurring in the morning, but the accurate quantification of this phenomenon remains a challenge. Here, we outline a novel method to quantify morning surge. We demonstrate how the most commonly used method to model 24-hour BP, the single cosinor approach, can be extended to a multiple-component cosinor random-effects model. We outline how this model can be used to obtain a measure of morning BP surge by obtaining derivatives of the model fit. The model is compared with a functional principal component analysis that determines the main components of variability in the data. Data from the Mitchelstown Study, a population-based study of Irish adults (n = 2047), were used where a subsample (1207) underwent 24-hour ambulatory blood pressure monitoring. We demonstrate that our 2-component model provided a significant improvement in fit compared with a single model and a similar fit to a more complex model captured by b-splines using functional principal component analysis. The estimate of the average maximum slope was 2.857 mmHg/30 min (bootstrap estimates; 95% CI: 2.855-2.858 mmHg/30 min). Simulation results allowed us to quantify the between-individual SD in maximum slopes, which was 1.02 mmHg/30 min. By obtaining derivatives we have demonstrated a novel approach to quantify morning BP surge and its variation between individuals. This is the first demonstration of cosinor approach to obtain a measure of morning surge.

Characterizing the time-course of antihypertensive activity and optimal dose range of fimasartan via mechanism-based population modeling

Fimasartan is a novel angiotensin II receptor blocker. Our aims were to characterize the time-course of the antihypertensive activity of fimasartan via a new population pharmacokinetic/pharmacodynamic model and to define its optimal dose range. We simultaneously modelled all fimasartan plasma concentrations and 24-h ambulatory blood pressure monitoring (ABPM) data from 39 patients with essential hypertension and 56 healthy volunteers. Patients received placebo, 20, 60, or 180mg fimasartan every 24h for 28days and healthy volunteers received placebo or 20 to 480mg as a single oral dose or as seven doses every 24h. External validation was performed using data on 560 patients from four phase II or III studies. One turnover model each was used to describe diastolic and systolic blood pressure. The input rates into these compartments followed a circadian rhythm and were inhibited by fimasartan. The average predicted (observed) diastolic blood pressure over 24-h in patients decreased by 10.1±7.5 (12.6±9.2; mean±SD)mmHg for 20mg, 14.2±7.0 (15.1±9.3) mmHg for 60mg, and 15.9±6.8 (11.5±9.9)mmHg for 180mg daily relative to placebo. The model explained the saturation of antihypertensive activity by counter-regulation at high fimasartan concentrations. Drug effect was maximal at approximately 23ng/mL fimasartan for diastolic and 12ng/mL for systolic blood pressure. The proposed mechanism-based population model characterized the circadian rhythm of ABPM data and the antihypertensive effect of fimasartan. After internal and external model validation, 30 to 60mg oral fimasartan given once daily was predicted as optimal dose range.

Pharmacokinetics and pharmacodynamics of oral mecamylamine - development of a nicotinic acetylcholine receptor antagonist cognitive challenge test using modelling and simulation

A pharmacologic challenge model with a nicotinic antagonist could be an important tool not only to understand the complex role of the nicotinic cholinergic system in cognition, but also to develop novel compounds acting on the nicotinic acetylcholine receptor. The objective was to develop a pharmacokinetic-pharmacodynamic (PKPD) model using nonlinear mixed effects (NLME) methods to quantitate the pharmacokinetics of three oral mecamylamine doses (10, 20 and 30 mg) and correlate the plasma concentrations to the pharmacodynamic effects on a cognitive and neurophysiologic battery of tests in healthy subjects. A one-compartment linear kinetic model best described the plasma concentrations of mecamylamine. Mecamylamine's estimated clearance was 0.28 ± 0.015 L min^-1. The peripheral volume of distribution (291 ± 5.15 L) was directly related to total body weight. Mecamylamine impaired the accuracy and increased the reaction time in tests evaluating short term working memory with a steep increase in the concentration-effect relationship at plasma concentrations below 100 μg L^-1. On the other hand, mecamylamine induced a decrease in performance of tests evaluating visual and fine motor coordination at higher plasma concentrations (EC₅₀ 97 μg L^-1). Systolic and diastolic blood pressure decreased exponentially after a plasma mecamylamine concentration of 80 μg L^-1, a known effect previously poorly studied in healthy subjects. The developed mecamylamine PKPD model was used to quantify the effects of nicotinic blockade in a set of neurophysiological tests in humans with the goal to provide insight into the physiology and pharmacology of the nicotinic system in humans and the possibility to optimize future trials that use mecamylamine as a pharmacological challenge.