Population Pharmacokinetics and Pharmacodynamics of Chloroquine in a Plasmodium vivax Volunteer Infection Study

Abstract

Chloroquine has been used for the treatment of malaria for > 70 years; however, chloroquine pharmacokinetic (PK) and pharmacodynamic (PD) profile in Plasmodium vivax malaria is poorly understood. The objective of this study was to describe the PK/PD relationship of chloroquine and its major metabolite, desethylchloroquine, in a P. vivax volunteer infection study. We analyzed data from 24 healthy subjects who were inoculated with bloodstage P. vivax malaria and administered a standard treatment course of chloroquine. The PK of chloroquine and desethylchloroquine was described by a two-compartment model with first-order absorption and elimination. The relationship between plasma and whole blood concentrations of chloroquine and P. vivax parasitemia was characterized by a PK/PD delayed response model, where the equilibration half-lives were 32.7 hours (95% confidence interval (CI) 27.4-40.5) for plasma data and 24.1 hours (95% CI 19.0-32.7) for whole blood data. The estimated parasite multiplication rate was 17 folds per 48 hours (95% CI 14-20) and maximum parasite killing rate by chloroquine was 0.213 hour −1 (95% CI 0.196-0.230), translating to a parasite clearance half-life of 4.5 hours (95% CI 4.1-5.0) and a parasite reduction ratio of 400 every 48 hours (95% CI 320-500). This is the first study that characterized the PK/PD relationship between chloroquine plasma and whole blood concentrations and P. vivax clearance using a semimechanistic population PK/PD modeling. This PK/PD model can be used to optimize dosing scenarios and to identify optimal dosing regimens for chloroquine where resistance to chloroquine is increasing. Globally, 225 million cases of malaria have been reported with 7.5 million cases due to Plasmodium vivax. 1 Malaria causes an estimated 405,000 deaths worldwide in which 67% involve children aged under 5 years. 1 Chloroquine was the cornerstone of malaria treatment but the spread of drug resistance has rendered chloroquine ineffective for the treatment of P. falciparum malaria in almost all

Investigational Treatments for COVID‐19 may Increase Ventricular Arrhythmia Risk Through Drug Interactions

“…To more accurately incorporate clinical drug concentrations, we implemented models based on quantitative PK studies on these drugs. 9,10,11,12 Simulations with a model developed for lopinavir + ritonavir therapy, 10 shown in Fig 2A, predict higher lopinavir concentrations with combination therapy (400 mg/100 mg twice daily) than with lopinavir therapy alone (400 mg twice daily). This occurs due to PK interactions whereby ritonavir inhibits lopinavir clearance.…”

“…The AZ PK model 11 was a three‐compartment model with first‐order absorption, lag time, and first‐order elimination, and this model calculated free drug concentrations directly. Finally, a PK model for CQ plasma concentrations was recently published using data from 24 healthy subjects 12 . This model consists of two‐compartments, with first‐order absorption and elimination.…”

“…The former can be studied with pharmacometrics approaches, whereas the latter can be addressed with quantitative systems pharmacology (QSP) models that explicitly incorporate drug mechanisms of action. Both PK and QSP simulations are likely to become particularly important for proposed COVID-19 treatments because: (1) adverse cardiac events, including QT prolongation, have been associated with several of these drugs, 6,7,8 (2) drug disposition has previously been characterized for most of the drugs being considered for treatment; 9,10,11,12 (3) modeling of pharmacological effects on cardiac electrophysiology, including adverse events, is a mature area of research; 13,14,15 and (4) QSP models can simulate the effects of drugs applied in different context, thereby allowing for the effects of factors such as comorbidities to be considered.…”

“…To link drug concentrations in the QSP simulations with free plasma drug concentrations that are likely to be observed in patients, we used PK models to simulate drug disposition of either azithromycin, 11 choloroquine 12 or lopinavir + ritonavir. 10 These models, implemented as published, allowed us to simulate temporal changes in either total or free plasma concentrations with different dosing regimens.…”

“…Finally, a PK model for chloroquine plasma concentrations was recently published using data from 24 healthy subjects. 12 This model consists of twocompartments, with first-order absorption and elimination. Because chloroquine has been shown to accumulate in target tissues, including the heart, we also used results from a physiologically-based PK model 9 developed in Simcyp (Version 18, Certara, UK).…”