Antimicrobial breakpoint estimation accounting for variability in pharmacokinetics

Abstract

Background: Pharmacokinetic and pharmacodynamic (PK/PD) indices are increasingly being used in the microbiological field to assess the efficacy of a dosing regimen. In contrast to methods using MIC, PK/PD-based methods reflect in vivo conditions and are more predictive of efficacy. Unfortunately, they entail the use of one PK-derived value such as AUC or Cmax and may thus lead to biased efficiency information when the variability is large. The aim of the present work was to evaluate the efficacy of a treatment by adjusting classical breakpoint estimation methods to the situation of variable PK profiles.

Methods and results: We propose a logical generalisation of the usual AUC methods by introducing the concept of "efficiency" for a PK profile, which involves the efficacy function as a weight. We formulated these methods for both classes of concentration- and time-dependent antibiotics. Using drug models and in silico approaches, we provide a theoretical basis for characterizing the efficiency of a PK profile under in vivo conditions. We also used the particular case of variable drug intake to assess the effect of the variable PK profiles generated and to analyse the implications for breakpoint estimation.

Conclusion: Compared to traditional methods, our weighted AUC approach gives a more powerful PK/PD link and reveals, through examples, interesting issues about the uniqueness of therapeutic outcome indices and antibiotic resistance problems.

Figure 1

The left panel depicts two PK profiles with the same AUC (23.6 mg × h/L). The solid curve illustrates rapid absorption while the dashed curve corresponds to slower absorption. The right panel depicts the corresponding efficacy vs time curves, which still show the difference in the PK profiles of the left panel; this difference is translated into the values of the corresponding efficiency AUC_W (17.45 vs 14.40 mg × h/L). The efficacy of the high absorption regime lasts almost throughout the therapeutic period (24 h) beyond the target efficacy of 0.8 mg.h/L, while the lower absorption regime barely reaches this target.

Figure 2

Illustration of efficacy vs. concentration of the two groups of antimicrobial agents. The time-dependent microbial agent in the left panel has an efficiency of all or none, i.e. there is a threshold concentration above which the drug is considered to be fully effective, and below which it is non-effective. The performance of the concentration-dependent antimicrobial agent in the right panel is known to be proportional to concentration.

Figure 3

A typical plasma drug concentration under conditions of irregular drug intake, with DOSE = 500 ppm CTC mixed in the animal feed.

Figure 4

The left panel shows the in vitro equivalent concentrations versus DOSE; the solid, dotted and dash-dot lines are , , respectively. The right panel shows the average concentrations versus DOSE; the solid, dotted and dash-dot lines are , , respectively.

Figure 5

In vivo mean concentrations versus in vitro equivalent concentrations.

Figure 6

In vitro equivalent concentrations versus in vivo average concentrations.

Figure 7

Therapeutic success probability across DOSEs. MIC = 0.5 mg/L.

Figure 8

Robustness of weighted AUC method. Left panel represents the three most widely used efficacy functions E: solid line for the linear function, broken line for the Emax function and dotted line for the logistic function. The corresponding AUC_W are plotted in the right panel with respect to concentration, along with AUC (solid thick line). The difference in AUC_W value estimated for these three efficacy functions is negligible compared to the differences from AUC.