Dosing time optimization of antihypertensive medications by including the circadian rhythm in pharmacokinetic-pharmacodynamic models

Abstract

Blood pressure (BP) follows a circadian variation, increasing during active hours, showing a small postprandial valley and a deeper decrease during sleep. Nighttime reduction of 10–20% relative to daytime BP is defined as a dipper pattern, and a reduction of less than 10%, as a non-dipper pattern. Despite this BP variability, hypertension’s diagnostic criteria and therapeutic objectives are usually based on BP average values. Indeed, studies have shown that chrono-pharmacological optimization significantly reduces long-term cardiovascular risk if a BP dipper pattern is maintained. Changes in the effect of antihypertensive medications can be explained by circadian variations in their pharmacokinetics (PK) and pharmacodynamics (PD). Nevertheless, BP circadian variation has been scarcely included in PK-PD models of antihypertensive medications to date. In this work, we developed PK-PD models that include circadian rhythm to find the optimal dosing time (Ta) of first-line antihypertensive medications for dipper and non-dipper patterns. The parameters of the PK-PD models were estimated using global optimization, and models were selected according to the lowest corrected Akaike information criterion value. Simultaneously, sensitivity and identifiability analysis were performed to determine the relevance of the parameters and establish those that can be estimated. Subsequently, Ta parameters were optimized to maximize the effect on BP average, BP peaks, and sleep-time dip. As a result, all selected models included at least one circadian PK component, and circadian parameters had the highest sensitivity. Furthermore, Ta with which BP>130/80 mmHg and a dip of 10–20% are achieved were proposed when possible. We show that the optimal Ta depends on the therapeutic objective, the medication, and the BP profile. Therefore, our results suggest making chrono-pharmacological recommendations in a personalized way.

Understanding the dosing-time-dependent antihypertensive effect of valsartan and aspirin through mathematical modeling

“…Dosing-time optimization of antihypertensive medications has been proposed to reduce long-term cardiovascular risk by clinical and computational studies ( 5 , 10 – 12 ). Some have shown that bedtime administration compared to awakening, improves cardiovascular risk in the long-term ( 2 , 30 ), while others found no difference ( 31 ).…”

“…The latter may be due to the different BP profiles of patients under study; i.e., a non-dipper patient probably will not show the same effect at a particular Ta compared to a dipper patient. Indeed, PK-PD models that include the circadian rhythm have shown that optimal Ta must be proposed in a personalized way ( 12 ). However, the causes and mechanisms involved in the dosing-time-dependent effect of antihypertensive medications have not been studied in depth.…”

“…On the one hand, pharmacokinetic changes are mainly produced by circadian changes in the rate of absorption, metabolism, and elimination of antihypertensive medications. Pharmacokinetic-pharmacodynamic models used to optimize the administration time of antihypertensive medications, showed that pharmacokinetic processes with lower constants (i.e., slower processes) are more dependent on dosing time than processes with higher constants ( 12 ). Therefore, the circadian dependence of the pharmacokinetic parameters of each antihypertensive medication may be different, even for those with the same mechanism of action.…”