Pharmacometrics as a tool to individualize treatment with anti-infective drugs

Abstract

The pharmacometrics models, such as population (Pop) pharmacokinetic (PK) models, were developed to explain the variability in PK parameters of anti-infective drugs including cefiderocol cefepime, rifampicin, and remdesivir, and to identify sources of these variabilities using subject characteristics for dose individualization.<br /> Cefiderocol is a novel siderophore cephalosporin antibiotic. A PopPK model with three compartments best described the PK of cefiderocol with kidney function as a predictor of clearance. The clinical studies showed that cefiderocol is non-inferior to imipenem/cilastatin and meropenem and showed similar safety and efficacy to the best available therapy in treating nosocomial pneumonia, sepsis/bloodstream, and urinary tract infections caused by carbapenem-resistant Gram-negative bacteria, making it an alternative antibiotic in treating drug-resistant bacterial infections.<br /> Cefepime is a broad-spectrum cephalosporin antibiotic and has been reported to cause neurotoxicity in patients with renal dysfunction. Pathophysiological changes cause high variability in the PK of the drug in critically ill patients. A two-compartment model best described the data obtained from 14 critically ill patients and identified estimated creatinine clearance as a predictor of cefepime clearance. Monte Carlo simulations (MCS) for patients with varying degrees of renal dysfunction showed that continuous infusion achieved a higher level of efficacy and lower risk of neurotoxicity compared to a dosing regimen based on q8h, q12h, and q24h with the same daily dose.<br /> Rifampicin is an anti-tuberculosis (TB) drug dosed based on body weight (BW). A one-compartment model with nonlinear (Michaelis–Menten) elimination and zero-order absorption kinetics with a lag time best described the data obtained from a bioequivalence study conducted on 24 healthy Caucasian volunteers. Various body size descriptors were tested to assess the PK variability of rifampicin. Estimated Fat-Free Mass (FFM) best explained the variability followed by BW and sex combined covariate model. MCS based on the FFM covariate model showed lower exposure to rifampicin with an increase in FFM and higher exposure in females compared to males. The results indicate that sex could also be relevant for optimizing the dosing of rifampicin, either directly with BW or indirectly via FFM.<br /> Remdesivir is a broad-spectrum antiviral drug with limited known PK information. It was the first drug approved during the COVID-19 pandemic for treating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) disease. Mean concentration data was obtained from a published phase I clinical trial. A two-compartment PopPK model best described the PK of remdesivir and its two metabolites with sequential metabolism between moieties. Inter-dose cohort variability was estimated due to the absence of individual data. Simulations based on clinically approved doses of remdesivir showed that the concentrations of GS-441524 metabolite exceeded the reported EC50 values for human airway epithelial cells infected with SARS-CoV-2, showing that the recommended doses would effectively inhibit the replication of the SARS-CoV-2 virus. The model could serve as a good starting point for further evaluations to explore PK variability in individual patients, including those with renal impairment.<br /> In summary, this work demonstrates the potential of pharmacometrics in improving the understanding of the PK of anti-infective drugs by developing PopPK models and identifying covariates for dose individualization.