Saliva as a noninvasive sampling matrix for therapeutic drug monitoring of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation: A prospective population pharmacokinetic and simulation study

Author:

Xu Baohua12,Yang Ting3,Zhou Jianxing12ORCID,Zheng You12,Wang Jingting4,Liu Qingxia12ORCID,Li Dandan12,Zhang Yifan5,Liu Maobai1,Wu Xuemei1ORCID

Affiliation:

1. Department of Pharmacy Fujian Medical University Union Hospital Fuzhou Fujian China

2. School of Pharmacy Fujian Medical University Fuzhou Fujian China

3. Department of Hematology Fujian Medical University Union Hospital Fuzhou Fujian China

4. College of Pharmacy University of Michigan Ann Arbor Michigan USA

5. Shanghai Institute of Materia Medica, Chinese Academy of Sciences Shanghai China

Abstract

AbstractTherapeutic drug monitoring (TDM) of busulfan (BU) is currently performed by plasma sampling in patients undergoing hematopoietic stem cell transplantation (HSCT). Saliva samples are considered a noninvasive TDM matrix. Currently, no salivary population pharmacokinetics (PopPKs) model for BU available. This study aimed to develop a PopPK model that can describe the relationship between plasma and saliva kinetics in patients receiving intravenous BU. The performance of the model in predicting the area under the concentration‐time curve at steady state (AUCss) based on saliva samples is evaluated. Sixty‐six patients with HSCT were recruited and administered 0.8 mg/kg BU intravenously. A PopPK model for saliva and plasma was developed using the nonlinear mixed effects model. Bayesian maximum a posteriori (MAP) optimization was used to estimate the model's predictive performance. Plasma and saliva PKs were adequately described with a one‐compartment model and a scaled central compartment. Body surface area correlated positively with both clearance and apparent volume of distribution (Vd), whereas alkaline phosphatase correlated negatively with Vd. Simulations demonstrated that the percentage root mean squared prediction error and lower and upper limits of agreements reduced to 10.02% and −16.96% to 22.86% based on five saliva samples. Saliva can be used as an alternative matrix to plasma in TDM of BU. The AUCsscan be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.

Publisher

Wiley

Subject

Pharmacology (medical),Modeling and Simulation

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