The objective of this study was to better characterize the activity of enrofloxacin against Pasteurella multocida thanks to available PK data (in pigs) and PD data by developing a semi-mechanistic PKPD modeling approach. Data from in vitro Time-kill (TK) experiments carried-out with 9 strains of Pasteurella multocida susceptible to enrofloxacin (MIC<0.06μg/mL) were used. Data from ex-vivo TK assays were also available for one of the 9 strains, using serum collected from pigs treated with enrofloxacin. Individual PK data were collected from another study involving healthy pigs treated with enrofloxacin at the usual doses. The semi-mechanistic PD model includes 2 bacterial sub-population (sensitive and resting one). Enrofloxacin action was modelled with a sigmoid Emax model, including a latency on the bactericidal effect and a saturation at high concentrations. Parameter values were shared by the 9 strains except for growth rate, EC50 and latency. An inoculum effect was included for experiments using different starting inocula. An external validation was done to assess the predictive performance of the PD model thanks to independent in vitro TK data already published for P. multocida. For the ex-vivo data, the same model was used taking into account the unbound fraction of enrofloxacin in pig plasma. Other refinements were made such as removing the latency on the bactericidal effect, and correcting the EC50 value. The ex-vivo PD model is still being improved. A population PK model of enrofloxacin in pigs was developed and will be linked to this PD model to assess the relevance of current dosing regimens of enrofloxacin in pigs with Monte Carlo simulations. Overall this works highlights the importance of strain-specific characteristics to get reliable PKPD predictions and optimize dosing regimens of antimicrobial in veterinary medicine.