Model informed clinical care in surgical and critically ill patients

Healthcare-associated infections (HAIs) remain a significant cause of illness and death among hospitalized patients, particularly those undergoing surgery or treated in intensive care units (ICUs). Among the most common and serious infections are surgical site infections (SSIs) and ICU-acquired infections such as pneumonia, bloodstream infections, and intra-abdominal infections. Although antibiotics like cefazolin, ampicillin-sulbactam, and piperacillin-tazobactam are routinely used in these settings, current dosing recommendations often do not account for real-world patient variability. These ?-lactam antibiotics are characterized by short half-lives and primarily renal clearance, requiring precise redosing to maintain therapeutic concentrations. This dissertation applies pharmacometric modeling to improve antibiotic dosing through a model-informed clinical care (MICC) approach, with the aim of supporting more effective and individualized treatment strategies for surgical and critically ill patients.

For surgical patients, prophylactic antibiotics are administered to prevent SSIs. Cefazolin and ampicillin-sulbactam are common choices, with recommended intraoperative redosing intervals of 4 and 2 hours, respectively. However, adherence to these guidelines especially for ampicillin-sulbactam is often poor, in part due to concerns about toxicity and uncertainty regarding the clinical benefit of frequent redosing. This project developed validated methods to quantify plasma concentrations of cefazolin, ampicillin, and sulbactam and used population pharmacokinetic (PopPK) modeling to evaluate their pharmacokinetics during surgery. Simulations were performed across varying procedure lengths and levels of kidney function to assess whether standard redosing practices maintain drug concentrations above the minimum inhibitory concentration (fT>MIC), a key pharmacodynamic target. The findings support more tailored redosing strategies, particularly in longer surgeries or in patients with altered renal clearance.

In critically ill ICU patients, the pharmacokinetics of piperacillin-tazobactam are highly variable due to physiological changes such as augmented renal clearance, fluid shifts, and multisystem organ failure. Standard empiric dosing often fails to achieve adequate drug exposure, especially in patients with fluctuating renal function or those receiving continuous renal replacement therapy (CRRT). Using opportunistic sampling and clinical data, PopPK models were developed to predict drug levels in ICU patients under various dosing strategies. Simulations comparing intermittent, extended, and continuous infusions identified regimens that consistently achieved therapeutic targets across renal function categories. These results inform empiric dosing protocols that can be initiated early in ICU care and refined as more patient-specific data become available.

By quantifying both total and unbound drug concentrations and simulating patient-specific pharmacokinetics, this project demonstrates how MICC can improve the precision of antibiotic therapy. The work highlights the clinical implications of short antibiotic half-lives and underscores the need for individualized redosing in patients at high risk for infection. These findings provide a framework for refining existing dosing guidelines and advancing antimicrobial stewardship in surgical and critical care settings.