Pharmaceutical Research

, Volume 33, Issue 5, pp 1115–1125 | Cite as

Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs

  • Anders N. Kristoffersson
  • Pascale David-Pierson
  • Neil J. Parrott
  • Olaf Kuhlmann
  • Thierry Lave
  • Lena E. Friberg
  • Elisabet I. Nielsen
Research Paper

ABSTRACT

Purpose

Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa.

Methods

A published murine dose fractionation study was replicated in silico. The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated.

Results

The previous murine study data were well replicated with fT > MIC selected as the best predictor. However, for increased dosing frequencies fAUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK fT > MIC and fAUC/MIC had similar predictive capacities with preference for fT > MIC when short t1/2 and fAUC/MIC when long t1/2.

Conclusions

A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.

KEY WORDS

antibiotic dose selection meropenem pharmacometric pseudomonas aeruginosa 

ABBREVIATIONS

AUC

Area under the curve

c.i.

Continuous infusion

CL

Clearance

CLCR

Creatinine CL

Cmax

Maximum concentration

fAUC/MIC

Unbound AUC divided by the MIC

fCmax/MIC

Unbound Cmax divided by the MIC

fT > MIC

Unbound time above the MIC

fu

Fraction unbound

h

Hour

i.v.

Intra venous

k

Rate constant

ka

Absorption rate

MIC

Minimum inhibitory concentration

PD

Pharmacodynamic

PK

Pharmacokinetic

q

Dose interval

Q

Inter compartmental CL

R2

Coefficient of determination

s.c.

Sub cutaneous

SCr

Serum creatinine

T

Time

t1/2

Half-life (elimination)

t1/2β

Half-life of the β-phase

TDM

Therapeutic drug monitoring

V

Volume

Vc

Central Volume (of distribution)

Vp

Peripheral volume (of distribution)

w

Week

WT

Weight

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Pharmaceutical BiosciencesUppsala UniversitetUppsalaSweden
  2. 2.F. Hoffmann-La Roche Ltd.Innovation Center Basel, Pharmaceuticals SciencesBaselSwitzerland

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