Development of a PBPK model to predict the pharmacokinetics of cefuroxime during surgery
Christer Rimmler (1), Dagmar Horn (2), Christian Lanckohr (3), Sari Ceren (3), Georg Hempel (1)
(1) Department of Pharmaceutical and Medicinal Chemistry, Clinical Pharmacy, Westfälische Wilhelms-Universität Münster, Germany, (2) Department of Pharmacy, University Hospital of Münster, Germany, (3) Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital of Münster, Germany
Objectives: The goal of this study is to predict the plasma and tissue concentrations of the cephalosporine antibiotic cefuroxime during surgery. In order to develop an adequate dose recommendation for the perioperative antibiotic prophylaxes, we included relevant changes in physiology during surgery, which may affect the pharmacokinetics of administered drugs. For this purpose, we developed and evaluated a physiologically-based pharmacokinetic (PBPK) model, using PK-Sim®/MoBi® [1].
Methods: Plasma and lung tissue concentrations were obtained from 25 patients (18 to 77 years) receiving i.v. 1.5 g Cefuroxime before start of the surgery and every 2.5 h thereafter. Based on literature data from healthy volunteers, a basic model was established. In order to consider the low albumin concentrations, the individual unbound fraction for each patient was corrected. As main parameters influencing the pharmacokinetics (Pk), the blood loss, administered fluid volume, protein shift from plasma to interstitial and the effect of anesthetic drugs, were included. These modifications were included as a linear function, calculated for each organ and subcompartment. The decrease in the mean arterial blood pressure induced by the administration of anesthetic drugs, results in a reduction of clearance processes of about 10%. Corrections of the partition coefficient and the endothelial permeability especially for the lung tissue of about 50% were necessary. In population evaluations we simulated a scale-up from the fitted tissue concentrations to interstitial concentrations.
Results: The first correction of the fraction unbound in the basic model improved the mean prediction error (MPE) from 8.1 to 4.5 %. The adjustment of the PK, triggered by the surgery, improved the model performance (MPE = 1.4% and MAPE = 29.0%), 84.5% of all predicted plasma concentration being within 50% of the observed. The lung tissue concentration could be also described adequately (MPE = 0.4% MAPE = 34.5%).
Conclusions: We were able to predict the changes of the Pk triggered by a surgery as well as the lung tissue concentration. There was no significant change of the PK triggered by a surgery, because two major effects antagonizing each other. The given dosing regimen lead to adequate interstitial and plasma concentrations for most populations. Higher deviations in the group of small individuals with a high creatinine clearance were observed.
References:
[1] Eissing, T. et al. (2011). A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Frontiers in physiology 2: 1–10.
