Fig 1.
Formula for calculation of daily dose.
Calculation at steady state based on pharmacokinetic and pharmacodynamic variables.
Fig 2.
Used to model time-kill data by non-linear regression [13].
Fig 3.
Example plot of AUC24h/MIC versus change in bacterial count from initial count (log10 CFU/mL).
Obtained from in vitro time-kill data for florfenicol. Each point represents an experimental value. The curve is the line of best fit based on the sigmoidal Emax equation.
Fig 4.
MIC distribution of P. multocida (n = 230) and A. pleuropneumoniae (n = 219).
Fig 5.
Formulae for calculation of the loading dose for 48h duration of action.
Table 1.
Pharmacokinetic variables (mean, standard deviation, n = 34) for florfenicol.
Table 2.
Integration of pharmacokinetic (in vivo plasma concentration) and pharmacodynamic (MIC determined in broth and serum) variables for florfenicol (mean and standard deviation).
Table 3.
Integration of pharmacokinetic (in vivo plasma concentration) and pharmacodynamic (MPC determined in broth and serum) variables for florfenicol (mean and standard deviation).
Table 4.
PK/PD modelling for P. multocida from time-kill curves (means and standard deviation, n = 6).
Table 5.
PK/PD modelling for A. pleuropneumoniae from time-kill curves (mean, and standard deviation, n = 6).
Table 6.
Predicted daily doses calculated by deterministic approach.
Table 7.
Predicted daily doses at steady state.
Table 8.
Single doses for 24, 48 and 72 h durations of activity.