Physiologically based pharmacokinetic‐pharmacodynamic evaluation of meropenem plus fosfomycin in paediatrics

Abstract

Aims The objective of the current study was to evaluate paediatric dosing regimens for meropenem plus fosfomycin that generate sufficient coverage against multidrug‐resistant bacteria. Methods The physiologically based pharmacokinetic (PBPK) models of meropenem and fosfomycin were developed from previously published pharmacokinetic studies in five populations: healthy subjects of Japanese origin, and healthy adults, geriatric, paediatric and renally impaired of primarily Caucasian origins. Pharmacodynamic (PD) analyses were carried out by evaluating dosing regimens that achieved a ≥90% joint probability of target attainment (PTA), which was defined as the minimum of the marginal probabilities to achieve the target PD index of each antibiotic. For meropenem, the percentage of time over a 24‐hour period wherein the free drug concentration was above the minimum inhibitory concentration (fT > MIC) of at least 40% was its PD target. The fosfomycin PD index was described by fAUC/MIC of at least 40.8. Results For coadministration consisting of 20 mg/kg meropenem q8h as a 3‐hour infusion and 35 mg/kg fosfomycin q8h also as a 3‐hour infusion in a virtual paediatric population between 1 month and 12 years of age with normal renal function and a corresponding body weight between 3 and 50 kg, a joint PTA ≥ 90% is achieved at MICs of 16 and 64 mg/L for meropenem and fosfomycin coadministration, respectively, against Klebsiella pneumoniae and Pseudomonas aeruginosa. Conclusion The current study identified potentially effective paediatric dosing regimens for meropenem plus fosfomycin coadministration against multidrug‐resistant bacteria.

Metabolomic profiling of polymyxin-B in combination with meropenem and sulbactam against multi-drug resistant Acinetobacter baumannii

“…4 mg/l sulbactam further reduces MIC to ≤2/2/4 mg/l for meropenem/polymyxin-B/sulbactam, resulting in susceptible for meropenem and intermediate for polymyxin-B (CLSI, 2020). The reduction in MIC provides sufficient drug exposure for clinical regimens of meropenem, polymyxin-B and sulbactam to achieve ≥90% PTA for their respective pharmacodynamic indices (Martins et al, 2020;Zhu et al, 2022). The metabolomic profiling results revealed that the combination therapy (P + M + S) initially perturbed lipids, LPS and peptidoglycan metabolism therefore impacted the stability of cell membrane and cell wall.…”

Evaluation of the drug‐drug interaction potential of treosulfan using a physiologically‐based pharmacokinetic modelling approach

“…The qualification of the developed PBPK model of treosulfan consisted of a population simulation of 200 subjects using ranges for age, gender, body weight and dosing information representative of the second half (qualification data set) of the study population. To evaluate the predictive performance of the PBPK model, the overall accuracy of the predicted PK parameters was assessed using the mean fold‐error (MFE; the difference between predicted in silico and observed in vivo values from the qualification data set): The model was accepted when all predicted PK parameters were within 2‐fold of the corresponding observed values (eg, MFE 0.5‐2.0) 23 …”

“…To evaluate the predictive performance of the PBPK model, the overall accuracy of the predicted PK parameters was assessed using the mean fold‐error (MFE; the difference between predicted in silico and observed in vivo values from the qualification data set): The model was accepted when all predicted PK parameters were within 2‐fold of the corresponding observed values (eg, MFE 0.5‐2.0). 23 …”

“…The model was accepted when all predicted PK parameters were within 2-fold of the corresponding observed values (eg, MFE 0.5-2.0). 23…”

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

“…The PBPK model has been widely applied as a tool for decision making, study optimization, and data analysis by academia, the pharmaceutical industry, and the regulatory agencies of pediatric drug development and therapy (11)(12)(13). The PBPK model has a variety of applications, such as guiding first dosing (14)(15)(16), predicting tissue drug concentration (17), estimating potential drug-drug interactions (DDIs) in pediatric patients, and describing the effects of organ impairment on pediatric pharmacokinetics (18).…”