Zbib Fatima, Deschamps Anthéa, Velly Lionel, Blin Olivier, Guilhaumou Romain, Gattacceca Florence
Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France.
Inria-Inserm COMPO Team, Centre Inria Sophia Antipolis-Méditerranée, CRCM, Inserm U1068-CNRS UMR7258-Aix-Marseille University UM105, Marseille, France.
Clin Pharmacokinet. 2025 Feb;64(2):257-273. doi: 10.1007/s40262-024-01469-x. Epub 2025 Jan 7.
Cefotaxime is a widely prescribed cephalosporin antibiotic used to treat various infections. It is mainly eliminated unchanged by the kidney through tubular secretion and glomerular filtration. Therefore, a reduction of kidney function may increase exposure to the drug and induce toxic side effects.
The objectives of this study were to develop a physiologically based pharmacokinetic (PBPK) model of cefotaxime in healthy European adults, to mechanistically describe the impact of chronic kidney disease (CKD) on cefotaxime pharmacokinetics, and to assess the applicability of the model to patients requiring intensive care.
Using PK-Sim software, we developed a PBPK model for cefotaxime, including basolateral and apical renal transporters and renal esterases, in healthy subjects and then extrapolated to patients with CKD by incorporating pathophysiological changes and reductions in activity of drug-metabolizing enzymes and transporters into the model. We then evaluated the predictive performance of the model in patients requiring intensive care using clinical routine data.
Model predictions were considered adequate in healthy subjects and patients with CKD, with predicted-to-observed area under the curve ratios within the two-fold acceptance criterion. Mean prediction error and mean absolute prediction error did not exceed ± 30 and 30%, respectively, except in patients with stage 4 CKD, where they were 70.5 and 75.6%, respectively. The model showed good predictive performance when applied to patients requiring intensive care, but its clinical applicability in this population needs to be further evaluated.
We successfully developed whole-body PBPK models to predict cefotaxime pharmacokinetics in different populations. These models represent an additional step toward improving personalized cefotaxime dosing regimens in vulnerable populations.
头孢噻肟是一种广泛应用于治疗各种感染的头孢菌素类抗生素。它主要通过肾小管分泌和肾小球滤过以原形经肾脏消除。因此，肾功能减退可能会增加药物暴露并引发毒性副作用。
本研究的目的是建立健康欧洲成年人中头孢噻肟的基于生理的药代动力学（PBPK）模型，从机制上描述慢性肾脏病（CKD）对头孢噻肟药代动力学的影响，并评估该模型对需要重症监护的患者的适用性。
使用PK-Sim软件，我们在健康受试者中建立了一个包括基底外侧和顶端肾转运体以及肾酯酶的头孢噻肟PBPK模型，然后通过将病理生理变化以及药物代谢酶和转运体活性的降低纳入模型，将其外推至CKD患者。然后，我们使用临床常规数据评估该模型在需要重症监护的患者中的预测性能。
在健康受试者和CKD患者中，模型预测被认为是充分的，曲线下面积的预测值与观测值之比在两倍接受标准范围内。除4期CKD患者外，平均预测误差和平均绝对预测误差分别不超过±30%和30%，4期CKD患者的平均预测误差和平均绝对预测误差分别为70.5%和75.6%。该模型在应用于需要重症监护的患者时显示出良好的预测性能，但其在该人群中的临床适用性需要进一步评估。
我们成功建立了全身PBPK模型以预测不同人群中头孢噻肟的药代动力学。这些模型代表了在改善脆弱人群中个性化头孢噻肟给药方案方面又迈出的一步。
