Evidence map›Paper›PMID 42333386›Full record

ArticleDrug design, development and therapy2026

Physiologically Based Pharmacokinetic Modeling and Therapeutic Drug Monitoring for Ertapenem Dose Optimization in Hypoalbuminemia Elderly Patients.

Xiaoyu Du, Zixuan Dong, Yumeng Li, Yin Wu, Huizhen Wu

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Article in Drug design, development and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaoyu DuSchool of Pharmacy, Graduate School of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Zixuan DongSchool of Pharmacy, Graduate School of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Yumeng LiSchool of Pharmacy, Graduate School of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Yin WuSchool of Pharmacy, Graduate School of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Huizhen WuSchool of Pharmacy, Graduate School of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.ORCID 0000-0002-5357-7343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: As a highly protein-bound, time-dependent antibiotic, the duration for which the unbound concentration of ertapenem remains above the minimum inhibitory concentration (%T>MIC) is a critical pharmacokinetic/pharmacodynamic (PK/PD) parameter. In our clinical TDM practice, most enrolled patients were elderly (mean age 62±21 years), with hypoalbuminemia present in 23/39 (59.0%), and the protein binding rate in these patients was significantly lower than literature-reported values. This study aimed to (1) establish a method for determining total and unbound ertapenem concentrations; (2) investigate factors influencing protein binding, focusing on hypoalbuminemia in the elderly; and (3) evaluate individualized dosing regimens for hypoalbuminemia elderly patients using a physiologically based pharmacokinetic (PBPK) model. Methods: Protein precipitation (for total concentration) and hollow-fiber centrifugal ultrafiltration (for unbound concentration) were used for sample pretreatment, followed by quantitative analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This method was applied to therapeutic drug monitoring (TDM) in clinical patients. A PBPK model was developed and validated using both our TDM data and published data to simulate dose-exposure relationships specifically in hypoalbuminemia elderly patients. Results: The developed method successfully quantified the total and unbound ertapenem concentrations. Clinical monitoring revealed that the protein binding rate in some patients was significantly lower than that reported in the literature. Correlation analysis indicated that albumin levels (p < 0.05) after outlier exclusion was the key factor influencing protein binding. The PBPK model demonstrated good agreement between the predicted and observed concentrations (AFE 0.78-1.26). Simulations indicated that standard doses (1 g q24h) may lead to excessive unbound exposure in hypoalbuminemia elderly patients, while 0.5 g q12h improved target attainment and reduced peak concentrations. Conclusion: Albumin level plays a pivotal role in regulating ertapenem protein binding. Standard doses are unsuitable for hypoalbuminemia elderly patients, and TDM-guided dose adjustments are necessary. The PBPK model provides a valuable tool for individualized dosing in this specific population.

Indexed as

Anti-Bacterial Agentsbeta-LactamsDrug MonitoringErtapenemHypoalbuminemiaModels, BiologicalAgedAged, 80 and overDose-Response Relationship, DrugFemaleHumansMaleMiddle AgedTandem Mass SpectrometryAnti-Bacterial Agentsbeta-LactamsErtapenemelderlyertapenemhollow fiber centrifugal ultrafiltration technologyhypoalbuminemiaPBPK modeltherapeutic drug monitoring

Identifiers

PMID42333386
PMCPMC13283395

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.