New model predicts how sepsis changes antibiotic dosing in critical patients
Researchers have developed a computational tool that predicts how severe infection alters the body's handling of meropenem, a last-line antibiotic. The advance could help hospitals optimize drug doses for sepsis patients, potentially improving survival rates and reducing treatment failures in intensive care units.
Originaltitel: Physiologically-based pharmacokinetic modelling in sepsis: A tool to elucidate how pathophysiology affects meropenem pharmacokinetics
<p>Objectives</p><p>Applying physiologically-based pharmacokinetic (PBPK) modelling in sepsis could help to better understand how PK changes are influenced by drug- and patient-related factors. We aimed to elucidate the influence of sepsis pathophysiology on the PK of meropenem by applying PBPK modelling.</p><p>Methods</p><p>A whole-body meropenem PBPK model was developed and evaluated in healthy individuals, and renally impaired non-septic patients. Sepsis-induced physiological changes in body composition, organ blood flow, kidney function, albumin, and haematocrit were implemented according to a previously proposed PBPK sepsis model. Model performance was evaluated, and a local sensitivity analysis was conducted.</p><p>Results</p><p>The model-predicted PK metrics (AUC, C<sub>max</sub>, CL, V<sub>ss</sub>) were within 1.33-fold-error margin of published data for 87.5% of the simulated profiles in healthy individuals. In sepsis, the model provided good predictions for literature-digitised average plasma and tissue exposure data, where the model-predicted AUC was within 1.33-fold-error margin for 9 out 11 simulated study profiles. Furthermore, the model was applied to individual plasma concentration data from 52 septic patients, where the model-predicted AUC, C<sub>max</sub>, and CL had a fold-error ratio range of 0.98–1.12, with alignment of the predicted and observed variability. For V<sub>ss</sub>, the fold-error ratio was 0.81, and the model underpredicted the population variability. CL was sensitive to renal plasma clearance, and kidney volume, whereas V<sub>ss</sub> was sensitive to the unbound fraction, organ volume fraction of the interstitial compartment, and the organ volume.</p><p>Conclusions</p><p>These findings may be extended to more diverse drug types and support a more mechanistic understanding of the effect of sepsis on drug exposure.</p>