Physiologically based pharmacokinetic-pharmacodynamic evaluation of meropenem in CKD and hemodialysis individuals

Abstract

Objective: Chronic kidney disease (CKD) has significant effects on renal clearance of drugs. The application of antibiotics in CKD patients to achieve the desired therapeutic effect is challenging. This study aims to determine meropenem plasma exposure in the CKD population and further investigate optimal dosing regimens.Methods: A healthy adult PBPK model was established using the meropenem’s physicochemical parameters, pharmacokinetic parameters, and available clinical data, and it was scaled to the populations with CKD and dialysis. The differences between the predicted concentration, Cmax, and AUClast predicted and observed model values were assessed by mean relative deviations (MRD) and geometric mean fold errors (GMFE) values and plotting the goodness of fit plot to evaluate the model’s performance. Finally, dose recommendations for CKD and hemodialysis populations were performed by Monte Carlo simulations.Results: The PBPK models of meropenem in healthy, CKD, and hemodialysis populations were successfully established. The MRD values of the predicted concentration and the GMFE values of Cmax and AUClast were within 0.5–2.0-fold of the observed data. The simulation results of the PBPK model showed the increase in meropenem exposure with declining kidney function in CKD populations. The dosing regimen of meropenem needs to be further adjusted according to the renal function of CKD patients. In patients receiving hemodialysis, since meropenem declined more rapidly during the on-dialysis session than the off-dialysis session, pharmacodynamic evaluations were performed for two periods separately, and respective optimal dosing regimens were determined.Conclusion: The established PBPK model successfully predicted meropenem pharmacokinetics in patients with CKD and hemodialysis and could further be used to optimize dosing recommendations, providing a reference for personalized clinical medication.

Interspecies Brain PBPK Modeling Platform to Predict Passive Transport through the Blood–Brain Barrier and Assess Target Site Disposition

“…Goodness-of-fit (GoF) plots were generated to compare the calculated area under the curve (AUC) and maximum concentration (Cmax) values for both observed and predicted data in rats (plasma and CNS) and humans (plasma). Additionally, for the quantitative evaluation of each independent model for acetaminophen, oxycodone, lacosamide, ibuprofen, and levetiracetam in rats and humans, the geometric mean fold error (GMFE) [ 63 ] will be calculated using the following Equations (2) and (3). …”