The effects of several antimicrobial agents are predicted by the ratio of the area under the concentration-time curve (AUC) to the MIC (AUC/MIC). Peak (C-p) and trough (C-t) concentrations are often measured clinically as surrogates of AUC because actual computation of AUC from 1 or 2 samples requires sophisticated mathematical methods. Given that the effects of daptomycin are predicted by AUC/MIC, our objective was to compare simple equation calculated AUC based on C-p and C-t to model integrated AUC. A standard population pharmacokinetic model was used to simulate 5,000 daptomycin concentration-time profiles after 5 doses of 6 mg/kg of body weight/day (0.5-h infusions). The AUC for the 24-h period was computed by integration and by equations with 110 C-p-C-t combination pairs. The C-p time points were in 15-min increments between 0.5 h and 3 h and C-t in 15-min increments within an hour of the end of the dosing interval for each dose. The precision and bias of the calculated AUC relative to the integrated AUC were determined to identify C-p-C-t pairs associated with the lowest bias and highest precision. The equations were further validated using two daptomycin concentration-time data sets from healthy volunteers and critically ill patients. The precision and bias of calculated AUC were based primarily on C-p, and use of a daptomycin C-p 1.5 h to 3 h from the start of infusion was associated with a bias of <10% and an R2 of >0.95. Data from the healthy volunteers and critically ill patients also demonstrated declining bias with use of C-p >= 1.5 h from the start of infusion with relatively good precision. Simplified equations using a daptomycin C-p approximately 2 h from the start of infusion and a C-t within an hour of the end of the dosing interval should yield precise and unbiased estimates of daptomycin AUC.

Simplified Equations Using Two Concentrations To Calculate Area under the Curve for Antimicrobials with Concentration-Dependent Pharmacodynamics: Daptomycin as a Motivating Example

Marco Falcone
2014-01-01

Abstract

The effects of several antimicrobial agents are predicted by the ratio of the area under the concentration-time curve (AUC) to the MIC (AUC/MIC). Peak (C-p) and trough (C-t) concentrations are often measured clinically as surrogates of AUC because actual computation of AUC from 1 or 2 samples requires sophisticated mathematical methods. Given that the effects of daptomycin are predicted by AUC/MIC, our objective was to compare simple equation calculated AUC based on C-p and C-t to model integrated AUC. A standard population pharmacokinetic model was used to simulate 5,000 daptomycin concentration-time profiles after 5 doses of 6 mg/kg of body weight/day (0.5-h infusions). The AUC for the 24-h period was computed by integration and by equations with 110 C-p-C-t combination pairs. The C-p time points were in 15-min increments between 0.5 h and 3 h and C-t in 15-min increments within an hour of the end of the dosing interval for each dose. The precision and bias of the calculated AUC relative to the integrated AUC were determined to identify C-p-C-t pairs associated with the lowest bias and highest precision. The equations were further validated using two daptomycin concentration-time data sets from healthy volunteers and critically ill patients. The precision and bias of calculated AUC were based primarily on C-p, and use of a daptomycin C-p 1.5 h to 3 h from the start of infusion was associated with a bias of <10% and an R2 of >0.95. Data from the healthy volunteers and critically ill patients also demonstrated declining bias with use of C-p >= 1.5 h from the start of infusion with relatively good precision. Simplified equations using a daptomycin C-p approximately 2 h from the start of infusion and a C-t within an hour of the end of the dosing interval should yield precise and unbiased estimates of daptomycin AUC.
2014
Pai, M. p.; Russo, A.; Novelli, A.; Venditti, Mario; Falcone, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/928029
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