Population Pharmacokinetic Models of Ampicillin-Sulbactam Among Adult Patients with Infectious Diseases: A Systematic
Mohananasunthari Poornachandran1, Sabariah Noor Harun1, Teh Sin Yin2
1School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia.
Background:
Ampicillin-sulbactam is the first-line treatment for pneumonia, aspiration pneumonia, and infections caused by Acinetobacter baumannii . Several population pharmacokinetic (PK) studies have evaluated the intravenous administration of ampicillin-sulbactam in adults. This systematic review aimed to compare published PK models and identify covariates influencing ampicillin-sulbactam PKs.
Methods:
A comprehensive literature search was conducted using PubMed and Scopus from inception to March 2025. Relevant articles from reference lists were also incorporated. This review included all population PK models of ampicillin-sulbactam administered intravenously in adult patients with various health conditions.
Results:
Five studies were reviewed, using a two-compartment model for ampicillin-sulbactam. The PK profiles of ampicillin and sulbactam were found to be similar, with comparable CL and V d across all selected studies. Ampicillin clearance ranged from 5.58 to 11.03 L/h, whereas sulbactam clearance ranged from 4.79 to 10.50 L/h. The volume of distribution varied from 11.78 to 19.12 L for ampicillin and from 13.89 to 16.77 L for sulbactam. Interindividual variability of ampicillin-sulbactam PK parameters varied across the included studies. Creatinine clearance (CLcr), serum creatinine (SCr), body surface area, body weight, and heart failure were found to be significant covariates affecting the PK parameters.
Conclusions:
Ampicillin-sulbactam clearance is primarily influenced by renal function (CLcr and SCr) and disease status. None of the studies performed external validation of the developed PK model. This review highlights the PK variability of ampicillin-sulbactam and the need for further research to refine dosing strategies and improve model reliability for clinical application.
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