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

Autor: Baohua Xu, Ting Yang, Jianxing Zhou, You Zheng, Jingting Wang, Qingxia Liu, Dandan Li, Yifan Zhang, Maobai Liu, Xuemei Wu
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: CPT: Pharmacometrics & Systems Pharmacology, Vol 12, Iss 9, Pp 1238-1249 (2023)
Druh dokumentu: article
ISSN: 2163-8306
99220415
DOI: 10.1002/psp4.13004
Popis: Abstract Therapeutic 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 AUCss can be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.
Databáze: Directory of Open Access Journals
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