Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.
CPT Pharmacometrics Syst Pharmacol. 2023 Oct;12(10):1541-1552. doi: 10.1002/psp4.13032. Epub 2023 Sep 18.
This study aimed to characterize apixaban pharmacokinetics (PKs) and its variability in a real-world clinical setting of hospitalized patients using a population PK (PopPK) approach. Model-based simulations helped to identify factors that affect apixaban exposure and their clinical significance. A classic stepwise strategy was applied to determine the best PopPK model for describing typical apixaban PKs in hospitalized patients from the OptimAT study (n = 100) and evaluating the associated variability and influencing factors. Apixaban exposure under specific conditions was assessed using the final model. A two-compartment model with first-order absorption and elimination best described the data. The developed PopPK model revealed a major role of renal function and a minor role of P-glycoprotein phenotypic (P-gp) activity in explaining apixaban variability. The final model indicated that a patient with stage 4 chronic kidney disease (creatinine clearance [CLcr] = 15-29 mL/min) would have a 45% higher drug exposure than a patient with normal renal function (CLcr >90 mL/min), with a further 12% increase if the patient was also a poor metabolizer of P-gp. A high interindividual variability in apixaban PKs was observed in a real-life setting, which was partially explained by renal function and by P-gp phenotypic activity. Target apixaban concentrations are reached under standard dosage regimens, but overexposure can rapidly occur in the presence of cumulative factors warranting the development of a predictive tool for tailoring apixaban exposure and its clinical utility in at-risk patients.
本研究旨在采用群体药代动力学（PopPK）方法描述住院患者真实临床环境中阿哌沙班的药代动力学（PKs）及其变异性。基于模型的模拟有助于确定影响阿哌沙班暴露的因素及其临床意义。应用经典逐步策略，确定了用于描述 OptimAT 研究（n=100）中住院患者典型阿哌沙班 PKs 的最佳 PopPK 模型，并评估了相关的变异性和影响因素。使用最终模型评估特定条件下阿哌沙班的暴露情况。具有一级吸收和消除的两室模型最能描述数据。所开发的 PopPK 模型表明，肾功能是解释阿哌沙班变异性的主要因素，而 P-糖蛋白表型（P-gp）活性的作用较小。最终模型表明，患有 4 期慢性肾脏病（肌酐清除率[CLcr] = 15-29 mL/min）的患者的药物暴露量比肾功能正常（CLcr >90 mL/min）的患者高 45%，如果患者也是 P-gp 的弱代谢者，则药物暴露量会进一步增加 12%。在真实生活环境中观察到阿哌沙班 PKs 的个体间变异性很大，部分原因是肾功能和 P-gp 表型活性。在标准剂量方案下可以达到目标阿哌沙班浓度，但在累积因素存在的情况下，可能会迅速出现药物暴露过度，因此需要开发一种预测工具来调整阿哌沙班的暴露及其在高危患者中的临床应用。
