Escitalopram Personalized Dosing: A Population Pharmacokinetics Repository Method

Abstract

Escitalopram (SCIT) represents a first-line antidepressant and antianxiety medication. Pharmacokinetic studies of SCIT have demonstrated considerable interindividual variability, emphasizing the need for personalized dosing. Accordingly, we aimed to create a repository of parametric population pharmacokinetic (PPK) models of SCIT to facilitate model-informed precision dosing. In November 2022, we searched PubMed, Embase, and Web of Science for published PPK models and identified eight models. All the structural models reported in the literature were either one-or two-compartment models. In order to investigate the variances in model performance, the parameters of all PPK models were derived from the literature published. A representative virtual population, characterized by an age of 30, a body weight of 70 kg, and a BMI of 23 kg/m 2 , was generated for the purpose of replicating these models. To accomplish this, the rxode2 package in the R programming language was employed. Subsequently, we compared simulated concentration-time profiles and evaluated the impact of covariates on clearance. The most significant covariates were CYP2C19 phenotype, weight, and age, indicating that dosing regimens should be tailored accordingly. Additionally, among Chinese psychiatric patients, SCIT showed nearly double the exposure compared to other populations, specifically when considering the same CYP2C19 population restriction, which is a knowledge gap that needs further investigation. Furthermore, this repository of parametric PPK models for SCIT has a wide range of potential applications, like design miss or delay dose remedy strategies and external PPK model validation.

Development and Quality Control of a Population Pharmacokinetic Model Library for Caspofungin

“…The most influential covariate was body size, such as body weight and BSA. Three [ 15 , 19 , 34 ] studies (23.1%) found body weight closely related to CL, and five studies [ 12 , 23 , 28 , 33 , 34 ] (38.5%) indicated its impact on V d . Yang et al [ 27 ] and Niu et al [ 25 ] identified BSA as a crucial covariate that affects both CL and V d .…”

“…Literature evaluations were implemented to diligently identify and resolve any anomalies or inconsistencies pertinent to the construction of the model library [ 15 ]. The quality of the popPK study was evaluated based on a checklist with 33 items adapted from the guidelines (see Supplementary Materials ) [ 16 , 17 ].…”

Model-Informed Precision Dosing of Isoniazid: Parametric Population Pharmacokinetics Model Repository

“…The assessment of the quality of the included studies was performed by utilizing a 33-item checklist, consisting of 5 categories, as presented in Table S1, according to previous popPK systematic review quality assessment method. [19][20][21][22] This checklist was designed to assess the essential components required for the reporting of clinical pharmacokinetic (PK) studies. For each item, one point was assigned if the involved literature met the criteria, whereas incomplete data were assigned 0.5 points.…”

“…Monte-Carlo simulations can predict the effect of different factors on drug exposure and estimate the probabilities of achieving the desired treatment outcome. Previous studies have successfully applied this approach to other drugs and created model repositories, [19][20][21][22] which enable the use of model averaging/selection methods and enhance the prediction performance of MIPD. 23,24 There have been systematic reviews on the pharmacokinetic models of isoniazid, [25][26][27] but two of these studies only provided descriptive introductions to existing articles.…”