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InsightRX®中群体药代动力学模型对头孢吡肟模型指导的精准给药的预测性能。

Predictive performance of population pharmacokinetic models in InsightRX® for model-informed precision dosing for Cefepime.

作者信息

König Christina, Kuti Joseph L, Fratoni Andrew J

机构信息

Center for Anti-Infective Research & Development, Hartford Hospital, Hartford, Connecticut, USA.

Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

出版信息

Pharmacotherapy. 2025 Jul;45(7):403-413. doi: 10.1002/phar.70029. Epub 2025 May 12.

Abstract

BACKGROUND

Model-informed precision dosing (MIPD) is a promising tool used to ensure therapeutic antimicrobial concentrations. Model selection and sampling strategy might lead to different pharmacokinetic (PK) parameter estimates. Herein, we assess the predictive performance for cefepime PK in two models implemented within the InsightRX software using differing sampling approaches.

METHODS

Historic cefepime PK data and individual Bayesian estimates in predominantly critically ill patients, some of whom had extracorporeal support, served as the reference standard. Two population PK models (A; B) were evaluated using four sampling scenarios: (i) trough only, (ii) midpoint only, (iii) trough + midpoint, and (iv) peak + midpoint + trough. The median prediction error (MPE) and median absolute prediction error (MAPE) were calculated for clearance (CL) and volume of central compartment (V). Predicted categorical achievement of ≥70% time that the free drug concentration was greater than the minimum inhibitory concentration [fT>MIC] was compared.

RESULTS

MAPE and MPE for CL and V resulted in variability that was dependent on model and sampling strategy. Both models' overall MPE and MAPE for CL were <±20 and <30% for all tested scenarios, respectively, with a low MPE of -2.4% to 4.4% on CL for sampling scenario 4. For V, MPE and MAPE were >±20 and >30% for the majority of test scenarios across both models, respectively. When excluding patients with extracorporeal support, MPE/MAPE for V decreased to 3.7-4.8/23.3%-34.5% and -7.9-2.5/25.2%-29.6% for model A and B, respectively. Using each model and sampling scheme, only four patients had discordant predicted achievement of ≥70% fT>MIC.

CONCLUSIONS

These two population PK models and all sampling scenarios demonstrated acceptable prediction of cefepime PK parameters and pharmacodynamic exposures; therefore, they demonstrated suitability for utilizing MIPD for cefepime therapeutic drug monitoring.

摘要

背景

模型指导的精准给药(MIPD)是一种用于确保抗菌药物治疗浓度的有前景的工具。模型选择和采样策略可能会导致不同的药代动力学(PK)参数估计值。在此,我们使用不同的采样方法评估了InsightRX软件中实施的两种模型对头孢吡肟PK的预测性能。

方法

主要为重症患者(其中一些接受体外支持)的历史头孢吡肟PK数据和个体贝叶斯估计值用作参考标准。使用四种采样方案评估了两个群体PK模型(A;B):(i)仅谷浓度,(ii)仅中点浓度,(iii)谷浓度+中点浓度,以及(iv)峰浓度+中点浓度+谷浓度。计算清除率(CL)和中央室容积(V)的中位数预测误差(MPE)和中位数绝对预测误差(MAPE)。比较预测的游离药物浓度大于最低抑菌浓度的时间≥70%[fT>MIC]的分类达成情况。

结果

CL和V的MAPE和MPE导致的变异性取决于模型和采样策略。在所有测试方案中,两个模型CL的总体MPE和MAPE分别<±20%和<30%,采样方案4中CL的MPE较低,为-2.4%至4.4%。对于V,在两个模型的大多数测试方案中,MPE和MAPE分别>±20%和>30%。排除接受体外支持的患者后,模型A和B中V的MPE/MAPE分别降至3.7 - 4.8/23.3% - 34.5%和-7.9 - 2.5/25.2% - 29.6%。使用每个模型和采样方案,只有4名患者预测的≥70% fT>MIC达成情况不一致。

结论

这两个群体PK模型和所有采样方案对头孢吡肟PK参数和药效学暴露的预测均可接受;因此,它们证明适用于利用MIPD进行头孢吡肟治疗药物监测。

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