JOURNAL TRANSCRIPT

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Estimation of In Vitro Susceptibility Breakpoints for Tigecycline Against Staphylococcus aureus Alison K Meagher, PharmD Cognigen Corporation 45th ICAAC December 17, 2005

Co-Authors Julie Passarell, M.A.

Cognigen Corporation

Scott Van Wart, M.S. Cognigen Corporation

Brenda Cirincione, M.A. Cognigen Corporation

Paul G. Ambrose, PharmD, FIDSA Institute for Clinical Pharmacodynamics Ordway Research Institute

This research was supported by a grant from Wyeth

Introduction • Susceptibility breakpoints are critical from the patient perspective as well as for society – Patient perspective: risk of clinical failure – Society perspective : risk of resistance

• Clinical trials collect PK data in target patient populations and provide the opportunity to integrate – Patient population PK – Exposure-response relationships – Distribution of MIC values for clinical isolates

Objective • Identify MIC susceptibility breakpoints for tigecycline against Staphylococci

Methods • Tigecycline exposure measures were generated from a population PK model.1 • A defined range of PK/PD targets (AUC/MIC) identified in previously presented exposureresponse analyses2 was used. • MIC susceptibility breakpoints were estimated through integration of these results and the distribution of S. aureus from clinical trials. 1Van

Wart, et al. Population pharmacokinetics of tigecycline in Phase 1 subjects (ICAAC 2004) et al. Exposure-response analysis of the efficacy of tigecycline in patients with complicated skin and skin-structure infections (ECCMID 2005) 2Meagher,

Methods

Study Design • One Phase 2 and two Phase 3 trials of patients with complicated skin and skin-structure infections (cSSSI) • 61 patients (91 pathogens) with cSSSI • Patients received either tigecycline 50-mg loading dose/25 mg q12h or 100-mg loading/50 mg q12h

Methods

Outcome Evaluation • Patients with S. aureus and/or streptococci isolated from skin lesions • Outcome evaluation considered in this analysis was microbiological response – Eradication/presumed eradication were considered “successful” – Persistence/presumed persistence were considered “failures”

Methods

Pharmacokinetics

Phase 2 patients

50 mg + 25 mg q12h 100 mg + 50 mg q12h

Observed AUC0-12 (mg*h/L)

1Van

Individual Predicted AUC0-12 (mg*h/L)

Individual Predicted AUC0-12 (mg*h/L)

• Previously presented population PK model1 • Two-compartment model with zero-order input and first-order elimination Phase 3 cSSSI patients

100 mg + 50 mg q12h

Observed AUC0-12 (mg*h/L)

Wart, et al. Population pharmacokinetics of tigecycline in Phase 1 subjects. ICAAC 2004.

Methods

PK/PD Analyses • CART analysis identified AUC/MIC breakpoints at 12.5 (p = 0.0309) and 16.4 (p = 0.0118) Patient Level

Probability of Bacteriologic Cure

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0

10

20

30

40 50 60 70 AUCss(0-24)/MIC Ratio 25 mg

80

50 mg

The line represents the model-based predicted probability of the patient level bacteriologic cure. The bars represent the 25th to 75th percentiles of ratio for each dose group.

90

100

Methods

Bootstrap Confidence Interval • 1000 randomly simulated datasets with replacement (40 patients each) were generated • CART analysis was performed to determine breakpoints in the AUC/MIC distribution, based upon microbiological outcomes

Methods

PK/PD Target Attainment • Within each simulated dataset, AUC values were paired with selected MIC values. • AUC/MIC ratios were evaluated with the previously identified PK/PD target values of 12.5 and 16.4 and the median bootstrap breakpoint estimate.

Results

Pharmacokinetics

Number of Patients

300

214 207

200 168

106

100

122

85

39 20

0

1

15 17

2

1

1

0

1

1

AUCss(0-24) (mcg*hr/mL)

Mean (SD) observed AUC was 6.02 (2.2) µg•hr/mL (2.6 to 22.58 µg•hr/mL) Mean (SD) simulated AUC was 6.02 (1.99) µg•hr/mL (1.5 to 26 µg•hr/mL)

Results

Boot Strap Confidence Interval 392

Number of Datasets

400

291

300

201

200

100

75

32

0

1

0

0

0

2

0

0

0

6

9.0 10.2 11.4 12.6 13.8 15.0 16.2 17.4 18.6 19.8 21.0 22.2 23.4 24.6

CART AUCss(0-24)/MIC Breakpoint

Median of 17.9 served as bootstrap estimate for the 95% CI of 13.9 to 19.5

Results

PK/PD Target Attainment AUC/MIC Breakpoint

MIC (µg/mL)

12.5

16.4

17.9

0.06

100

100

100

0.12

99.99

99.91

99.76

0.25

94.13

74.51

64.25

0.5

22.58

4.82

2.52

1

0.17

0.11

0.10

2

0

0

0

Results PK/PD Target Attainment 1

PK/PD Target 17.9

0.9

PK/PD Target 16.4

MIC Probability

0.8

PK/PD Target 12.5

0.7

0.9 0.8 0.7

0.6

0.6

0.5

0.5

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

0 0.06

0.12

0.25

0.5 1 2 MIC (mg/L)

4

8

16

Probability of Target Attainment

1

Conclusions • Integration of population PK, exposureresponse analyses, and MIC distributions is a useful approach for evaluating susceptibility breakpoints. • This analysis provided an estimation of susceptibility breakpoints for tigecycline against Staphylococci. • In addition to clinical response, these analyses may be a useful component in assessing breakpoints for these organisms.