title: Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs.
abstract: OBJECTIVE
  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.
authors.affiliation: Department of Pharmaceutical Biosciences, Uppsala Universitet, Box 591, Uppsala, SE-751 24, Sweden. anders.kristoffersson@farmbio.uu.se.
authors.forename: Anders N
authors.identifier: http://orcid.org/0000-0003-3166-9981
authors.initials: AN
authors.lastname: Kristoffersson
authors.affiliation: F. Hoffmann-La Roche Ltd., Innovation Center Basel, Pharmaceuticals Sciences, Basel, Switzerland.
authors.forename: Pascale
authors.initials: P
authors.lastname: David-Pierson
authors.affiliation: F. Hoffmann-La Roche Ltd., Innovation Center Basel, Pharmaceuticals Sciences, Basel, Switzerland.
authors.forename: Neil J
authors.initials: NJ
authors.lastname: Parrott
authors.affiliation: F. Hoffmann-La Roche Ltd., Innovation Center Basel, Pharmaceuticals Sciences, Basel, Switzerland.
authors.forename: Olaf
authors.initials: O
authors.lastname: Kuhlmann
authors.affiliation: F. Hoffmann-La Roche Ltd., Innovation Center Basel, Pharmaceuticals Sciences, Basel, Switzerland.
authors.forename: Thierry
authors.initials: T
authors.lastname: Lave
authors.affiliation: Department of Pharmaceutical Biosciences, Uppsala Universitet, Box 591, Uppsala, SE-751 24, Sweden.
authors.forename: Lena E
authors.initials: LE
authors.lastname: Friberg
authors.affiliation: Department of Pharmaceutical Biosciences, Uppsala Universitet, Box 591, Uppsala, SE-751 24, Sweden.
authors.forename: Elisabet I
authors.initials: EI
authors.lastname: Nielsen
mesh_terms: D000818:Animals; D000900:Anti-Bacterial Agents / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000627:therapeutic use; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D005260:Female; D006801:Humans; D008297:Male; D000077731:Meropenem; D051379:Mice; D008826:Microbial Sensitivity Tests; D008954:Models, Biological; D011552:Pseudomonas Infections / Q000188:drug therapy*; D011550:Pseudomonas aeruginosa / Q000187:drug effects* / Q000254:growth & development; D013845:Thienamycins / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000627:therapeutic use
chemical_list: D000900:Anti-Bacterial Agents; D013845:Thienamycins; D000077731:Meropenem
keywords: antibiotic; dose selection; meropenem; pharmacometric; pseudomonas aeruginosa