Critically ill patients are susceptible to serious infections due to their compromised conditions and extensive use of medical devices, often requiring empiric broad-spectrum antimicrobial therapy. Failure of antimicrobial therapy in this vulnerable population has a direct impact on the patient’s survival; hence, selecting the optimal dosage is critical. This population, however, exhibits complex and diverse disease-related physiological changes that can markedly alter antimicrobial disposition. Inflammatory cytokines overexpressed in the systemic inflammatory response syndrome increase vascular permeability, leading to higher volume of distribution for hydrophilic antimicrobials. These cytokines also downregulate metabolic enzyme activities, reducing the clearance of their substrates. Hypoalbuminemia can increase the volume of distribution and clearance of highly protein-bound antimicrobials. Acute kidney injury decreases, while augmented renal clearance increases the clearance of antimicrobials primarily excreted by the kidneys. Furthermore, continuous renal replacement therapy and extracorporeal membrane oxygenation used in critical illness substantially affect antimicrobial pharmacokinetics. The complex interplay of multiple factors observed in critically ill patients poses a significant challenge in predicting the pharmacokinetics of antimicrobials. Therapeutic drug monitoring is the most effective tool to address this issue, and is proactively recommended for vancomycin, teicoplanin, aminoglycosides, voriconazole, β-lactams, and linezolid in critically ill patients. To streamline this process, model-informed precision dosing is expected to promote personalized medicine for this population.

The appropriate use of antibiotics is crucial and involves selecting an optimal dosing regimen based on pharmacokinetic (PK) and pharmacodynamic (PD) indicators. Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool that integrates drugs’ physicochemical properties with anatomical and physiological data to predict PK behavior. In pediatric populations, PBPK modeling accounts for developmental changes in organ function, making it particularly useful for optimizing antibiotic dosing across different age groups, from neonates to adolescents. In recent decades, PBPK modeling has been widely applied to predict antibiotic disposition in pediatric patients for various clinical and research purposes. Model-informed precision dosing (MIPD) is an evolving approach that enhances traditional therapeutic drug monitoring by integrating multiple information sources into a mathematical framework. By incorporating PBPK modeling, MIPD could offer a more optimized antibiotic dosing that accounts for PK/PD parameters at the site of infection, improving therapeutic outcomes while minimizing toxicity. This review summarizes currently published pediatric PBPK modeling studies on antibiotics, covering various objectives such as evaluating drug–drug interactions, PK/PD analyses in targeted tissues, predicting PK in specific populations (e.g., maternal/fetal, renal impairment, obesity), and PK predictions for preterm neonates. Based on these reports, the review discusses the implications of PBPK modeling for MIPD in pediatric antibiotic therapy.