European journal of drug metabolism and pharmacokinetics · 2026
Defining Safe and Effective Cefazolin Dosing Regimens for MSSA Infections in the CNS: Leveraging Sparse Real-World Data and PBPK Modeling.
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Dubinsky Samuel, McIntyre Mark, Kim Min-Soo, Hawryluk Laura, Edginton Andrea
Аннотация
BACKGROUND AND OBJECTIVE: Infections in the central nervous system (CNS) are serious and carry a significant risk of morbidity and mortality. Though commonly used as prophylaxis for neurosurgical interventions, cefazolin as a treatment for CNS infections due to methicillin-susceptible Staphylococcus aureus (MSSA) has been debated owing to the perceived inability to achieve adequate concentrations at the site of infection. The objective of the current study was to evaluate the dose-exposure-response relationship of cefazolin in the CNS.
METHODS: To leverage sparse data of cefazolin in the cerebrospinal fluid (CSF) and derive an understanding of the dose-exposure-response profile in the CNS, a physiologically-based pharmacokinetic (PBPK) model was created in PK-Sim. Simulations were performed using standard cefazolin dosing of 2000 mg every 8 h and alternative regimens to maximize the probability of target attainment (PTA). The pharmacodynamic target used was 100% fT > MIC (100% of free drug concentrations above the minimum inhibitory concentration). Furthermore, a neurotoxicity threshold of ≥ 300 mg/L and ≥ 30 mg/L for trough concentrations was set as the safety indicator in plasma and CSF, respectively.
RESULTS: The cefazolin CSF-PBPK model was successfully validated such that predicted CSF:plasma ratios were within a 1.5-fold error compared with the observed values. In addition, the median predicted CSF:epidemiological cut-off (ECOFF) concentration ratio was 2.52, compared with an observed value of 2.8. In silico simulations demonstrate that intermittent doses of 2000 mg every 6 h or a continuous infusion of 8-10 g/day may be required to ensure 90% PTA for MSSA to a MIC ≤ 2 mg/L. Predicted plasma and CSF concentrations were well below concentrations associated with neurotoxicity.
CONCLUSIONS: This study is the first to use sparse observed CNS data to develop a mechanistic model to describe the pharmacokinetics of cefazolin in the CSF. This work supports existing research on the viability of cefazolin as a therapeutic alternative for CNS infections attributed to MSSA and can be used for future clinical trial planning.
METHODS: To leverage sparse data of cefazolin in the cerebrospinal fluid (CSF) and derive an understanding of the dose-exposure-response profile in the CNS, a physiologically-based pharmacokinetic (PBPK) model was created in PK-Sim. Simulations were performed using standard cefazolin dosing of 2000 mg every 8 h and alternative regimens to maximize the probability of target attainment (PTA). The pharmacodynamic target used was 100% fT > MIC (100% of free drug concentrations above the minimum inhibitory concentration). Furthermore, a neurotoxicity threshold of ≥ 300 mg/L and ≥ 30 mg/L for trough concentrations was set as the safety indicator in plasma and CSF, respectively.
RESULTS: The cefazolin CSF-PBPK model was successfully validated such that predicted CSF:plasma ratios were within a 1.5-fold error compared with the observed values. In addition, the median predicted CSF:epidemiological cut-off (ECOFF) concentration ratio was 2.52, compared with an observed value of 2.8. In silico simulations demonstrate that intermittent doses of 2000 mg every 6 h or a continuous infusion of 8-10 g/day may be required to ensure 90% PTA for MSSA to a MIC ≤ 2 mg/L. Predicted plasma and CSF concentrations were well below concentrations associated with neurotoxicity.
CONCLUSIONS: This study is the first to use sparse observed CNS data to develop a mechanistic model to describe the pharmacokinetics of cefazolin in the CSF. This work supports existing research on the viability of cefazolin as a therapeutic alternative for CNS infections attributed to MSSA and can be used for future clinical trial planning.