Radke Christian, Horn Dagmar, Lanckohr Christian, Ellger Björn, Meyer Michaela, Eissing Thomas, Hempel Georg
Department of Clinical Pharmacy, Institute of Pharmaceutical and Medical Chemistry, University of Muenster, Corrensstrasse 48, 48149, Muenster, Germany.
Department of Pharmacy, University Hospital of Muenster, Muenster, Germany.
Clin Pharmacokinet. 2017 Jul;56(7):759-779. doi: 10.1007/s40262-016-0475-3.
Sepsis is characterised by an excessive release of inflammatory mediators substantially affecting body composition and physiology, which can be further affected by intensive care management. Consequently, drug pharmacokinetics can be substantially altered. This study aimed to extend a whole-body physiologically based pharmacokinetic (PBPK) model for healthy adults based on disease-related physiological changes of critically ill septic patients and to evaluate the accuracy of this PBPK model using vancomycin as a clinically relevant drug.
The literature was searched for relevant information on physiological changes in critically ill patients with sepsis, severe sepsis and septic shock. Consolidated information was incorporated into a validated PBPK vancomycin model for healthy adults. In addition, the model was further individualised based on patient data from a study including ten septic patients treated with intravenous vancomycin. Models were evaluated comparing predicted concentrations with observed patient concentration-time data.
The literature-based PBPK model correctly predicted pharmacokinetic changes and observed plasma concentrations especially for the distribution phase as a result of a consideration of interstitial water accumulation. Incorporation of disease-related changes improved the model prediction from 55 to 88% within a threshold of 30% variability of predicted vs. observed concentrations. In particular, the consideration of individualised creatinine clearance data, which were highly variable in this patient population, had an influence on model performance.
PBPK modelling incorporating literature data and individual patient data is able to correctly predict vancomycin pharmacokinetics in septic patients. This study therefore provides essential key parameters for further development of PBPK models and dose optimisation strategies in critically ill patients with sepsis.
脓毒症的特征是炎症介质过度释放，这会严重影响身体组成和生理机能，而重症监护管理可能会进一步对其产生影响。因此，药物的药代动力学可能会发生显著改变。本研究旨在基于重症脓毒症患者的疾病相关生理变化，扩展一个针对健康成年人的全身生理药代动力学（PBPK）模型，并以万古霉素作为临床相关药物来评估该PBPK模型的准确性。
检索文献以获取有关脓毒症、严重脓毒症和脓毒性休克重症患者生理变化的相关信息。将汇总的信息纳入一个经过验证的健康成年人PBPK万古霉素模型。此外，根据一项包含10名接受静脉注射万古霉素治疗的脓毒症患者的研究中的患者数据，对该模型进行进一步个体化。通过将预测浓度与观察到的患者浓度-时间数据进行比较来评估模型。
基于文献的PBPK模型正确预测了药代动力学变化以及观察到的血浆浓度，特别是在考虑间质水蓄积的情况下对分布相的预测。纳入疾病相关变化后，在预测浓度与观察浓度相差30%的变异性阈值内，模型预测从55%提高到了88%。特别是，考虑到该患者群体中个体肌酐清除率数据变化很大，其对模型性能有影响。
结合文献数据和个体患者数据的PBPK建模能够正确预测脓毒症患者的万古霉素药代动力学。因此，本研究为进一步开发脓毒症重症患者的PBPK模型和剂量优化策略提供了关键参数。
