PHARMACODYNAMIC RELATIONSHIPS AND EMERGENCE OF RESISTANCE

4. PHARMACODYNAMIC RELATIONSHIPS AND EMERGENCE OF RESISTANCE

In the sections above, it was shown that there is a relationship between PK/PD index and efficacy and that this relationship can be used to optimize dosing regimens. The question that can be asked subsequently is, whether there is a relationship between PK/PD indices and emergence of resistance as well. To answer that question, two items need to be addressed. The first is whether the PK/PD index itself is the proper measure to use, more in particu- lar whether the MIC part of the ratio should be applied to calculate the index or whether another pharmacodynamic measure of antibacterial activity is more appropriate. The second item that needs to be addressed is a measure of emergence of resistance. Both these items are discussed below.

4.1. Pharmacodynamic measures: PK/PD index, mutation prevention concentration and mutation selection window

The mutation prevention concentration (MPC) has been used recently as

a measure for emergence of resistance. Although various definitions and

402 Johan W. Mouton method descriptions exist, the one used most often lately is comparable to an

agar dilution MIC with a high inoculum. Agar plates are prepared with anti- microbial concentrations in twofold dilutions. The plates are inoculated with a

high inoculum, typically 10 9 or more colony forming units (cfu). The MPC is the lowest concentration where no growth is observed. The major shortcoming of the MPC is comparable to the use of the MIC as discussed above. The MPC, similar to the MIC, is determined at static concen- trations and read after a certain period of time, while in vivo concentrations decline over time. In attempting to overcome this problem, to correlate the MPC to emergence of resistance, the mutant selection window is defined and it is hypothesized that when concentrations of an antimicrobial fall into this window there is a marked increase in risk of emergence of resistance. Concentrations should be above the MPC for the whole dosing interval or, at least, the duration of exposure at concentrations within this window should be as short as possible (Zhao and Drlica, 2002; Drlica, 2003) (Figure 9). Several authors have attempted to demonstrate the validity of the concept, mainly with the fluoroquinolones (Firsov et al., 2003). Although some of these studies seem to favour the concept, it is difficult to prove and there are a number of theoretical and practical arguments against it. The two most important ones are again that both the MIC and the MPC are determined at static concentrations after a certain period of time and the window itself does not take into account the momentary effects of the concentrations, nor the effect of the concentrations

Concentration (mg/L)

Time

Figure 9. Diagram showing the mutation prevention window (shaded area).

Impact of Pharmacodynamics on Dosing Schedules 403 over time. Another important argument is that the window is determined by

concentrations determined in serum, while the concentration profile at the site of infection may be markedly different.

Another approach that has been taken is to correlate emergence of resis- tance to PK/PD indices, the effect parameter being the frequency of resistant clones after exposure. In this manner the total concentration–time profile is correlated to outcome in terms of emergence of resistance in a similar way to the efficacy of the drug. In a recent study by Firsov et al. (2003), it was demonstrated that there is a clear relationship between AUC/MIC ratio and frequency of emergence of resistance that followed a Bell-shaped curve when exposing four S. aureus strains to various dosing regimens of quinolones in an in vitro pharmacokinetic model (Figure 10). Indeed, the model fit to the data shown in the figure is analogous to the normal equation. At low AUC/MIC ratios the frequency of emergence of resistant clones is very low, as it is also low at relatively high values. There is a value of the AUC/MIC ratio that corresponds to the highest frequency of resistant clones after exposure, in this instance 43 hr. Similar relationships could be made for results obtained in other studies (Aeschlimann et al., 1999; Firsov et al., 2003; Peterson et al., 1999). The question that arises is, how does the value

Figure 10. Bell-shaped relationship between AUC/MIC and frequency of resistance for quinolones. Reproduced from Firsov et al., 2003.

404 Johan W. Mouton of 43 hr compare to the PK/PD index value necessary for a maximum effect?

In the paper mentioned this was not the subject of study, but other studies involving quinolones and Gram-positive microorganisms have found values between 30 and 50 hr. Thus, it may very well be that the PK/PD index value necessary to minimize emergence of resistance is higher than the value needed to obtain maximum efficacy. Experiments have also been performed in vivo. In an established abscess mixed model of infection Stearne et al. determined the frequency of emergence of resistant clones following expo- sure to ceftizoxime (Stearne et al., 2002). The data presented allowed the determination of PK/PD index values for the various dosing regimens. Figure 11 shows the relationship between T ⬎MIC and frequency of emergence of resistant clones. Again, a Bell-shaped curve is observed. Apparent from the figure is that the highest frequency of resistance is observed at values of 60–70% while the frequency is very low at T ⬎MIC values above 87%. These values are higher than those where a maximum effect is reached. One study in humans has shown that the probability of emergence of resistance was far greater when AUC/MIC ratios were lower than 100 hr as compared to values above 100 hr (Figure 12) (Thomas et al., 1998).

Taken together, these studies, although still few in number, show that there is a clear relationship between PK/PD index values and emergence of resis- tance and that suboptimal dosing leads to a higher probability of emergence of resistance. It is therefore important that dosing schedules of antimicrobials are derived which do take these relationships into account. This probably also applies to breakpoints, but this has, as yet, to be taken into consideration.

Mutation frequency 0.2

T > MIC (% dosing interval) Figure 11. Bell-shaped relationship between T ⬎MIC and frequency of resistance for cefti-

zoxime. Based on data from Stearne et al., 2002.

Impact of Pharmacodynamics on Dosing Schedules 405

Figure 12. Relationship between AUC/MIC and probability of emergence of resistance (Thomas et al., 1998).