Andrew Mead

Trimethoprim (TMP)‐sulfonamide combinations are widely used in veterinary medicine, yet the quantitative nature of their pharmacodynamic interaction remains incompletely characterised. This study investigated the interaction between TMP and sulfamethoxazole (SMX), sulfadiazine (SDZ) and sulfadimethoxine (SDMX) against two Staphylococcus pseudintermedius isolates using minimum inhibitory concentration (MIC) testing, time‐kill curve (TKC) experiments and semi‐mechanistic pharmacodynamic modelling incorporating a General Pharmacodynamic Interaction (GPDI) framework. TKC assays demonstrated enhanced antibacterial activity for TMP‐sulfonamide combinations compared with monotherapy, with the greatest bacterial killing observed at TMP:sulfonamide ratios of 1:4 and 1:19. The final GPDI model identified a predominantly unidirectional interaction in which sulfonamides increased TMP potency through concentration‐dependent reductions in TMP EC ₅₀ of 86%–96% at saturating sulfonamide concentrations, corresponding to approximately 7‐ to 26‐fold maximal possible increases in TMP potency. Maximal synergy differed between sulfonamides, occurring at approximately 1:20 for TMP/SMX (~75% increase in killing), 1:40 for TMP/SDZ (~181%) and 1:5 for TMP/SDMX (~80%). Pharmacokinetic‐pharmacodynamic simulations of clinically relevant canine dosing regimens predicted transient bacterial suppression but not bacterial eradication. These findings demonstrate that TMP‐sulfonamide synergy is dynamic, concentration‐dependent and bacterial species‐specific, highlighting the importance of PK/PD‐informed optimisation of potentiated sulfonamide therapy in veterinary medicine.

Trimethoprim (TMP) and sulphonamides are widely used in combination to treat many conditions, including porcine respiratory infections caused by Actinobacillus pleuropneumoniae (APP), yet the pharmacodynamic basis of their synergy remains unclear. This study investigated the interactions between TMP and three sulphonamides (sulfamethoxazole, sulfadiazine, and sulfadimethoxine) against APP. Interactions were evaluated against three APP strains using MIC determination, static time-kill assays of individual drugs across five TMP: sulphonamide ratios (1:4, 1:19, 1:99, 1:499, 1:999), and semi-mechanistic pharmacodynamic modelling. Single-drug models showed greater TMP potency than sulphonamides (median EC₅₀ 0.018 µg mL⁻¹ vs ∼3–10 µg mL⁻¹). A General Pharmacodynamic Interaction model identified a unidirectional interaction in which TMP enhanced sulphonamide potency by reducing their EC₅₀ at sub-MIC TMP concentrations (∼22-fold below the MIC), consistent with indirect antifolate action requiring folate depletion. Delayed sulphonamide effects and density-dependent growth limitation improved model performance. Maximal synergy, defined as the relative increase in bacterial killing rate, was 110–115% for all sulphonamides and occurred at a pharmacodynamic ratio of 1:250 (0.002 µg mL⁻¹ TMP with 0.5 µg mL⁻¹ sulphonamide). This represents a PD ratio and should not be confused with the classical 1:19 TMP: sulphonamide ratio reported for clinical effectiveness. Simulations using median porcine pharmacokinetics predicted rapid initial bacterial killing across intravenous and oral regimens despite pharmacokinetic ratio drift. However, sustained efficacy was regimen-dependent, with only the TMP-sulfadimethoxine combination achieving eradication, whereas others showed regrowth. These findings provide a mechanistic explanation of TMP–sulphonamide synergy against APP and highlight the value of semi-mechanistic PK/PD modelling for optimising veterinary combination therapy.

Background: Pre-clinical models are commonly used to determine human antibiotic dosage regimens using pharmacokinetic/pharmacodynamic (PKPD) indices. The murine thigh infection model (MTIM) is most commonly used for PKPD index determination, while the hollow fibre infection model (HFIM) may be a viable alternative. However, there is no standardized method for determining the PKPD index and R2 may not be the ideal metric to determine goodness of fit for nonlinear models. This study aimed to reanalyse PKPD indices published in MTIM and HFIM, using a standardized modelling approach. Methods: Systematic literature review was conducted to identify MTIM and HFIM dose fractionation studies. Searches covered databases including PubMed, MEDLINE, BIOSIS, SCOPUS and EMBASE. Data were extracted and modelled using eight variations of Emax model, with model selection based on the lowest Akaike information criterion (AIC) and parameter plausibility in terms of precision and interpretability. Results: A total of 53 studies were included: 50 MTIM (of 1138) and 3 HFIM (of 316). Among the 53 studies, reporting issues included an infrequent use of AIC for model selection as applied in only one paper, and a lack of methodological transparency in 29 papers. Remodelling revealed some disagreement in optimal PKPD indices in six studies. Conclusions: This study suggests a standard method for PKPD index model selection and provides a database on PKPD index analysis. Building the Emax model from one to four estimated parameters and assessing them with AIC is recommended to avoid over fitting. Too few HFIM dose fractionation studies were found to allow comparison of PKPD index with MTIM.

Trailing endpoints are a recognised challenge in broth microdilution MIC testing, particularly for bacteriostatic agents such as trimethoprim (TMP) and sulphonamides. In this study, we applied a pharmacodynamically guided refinement to determine the MIC of the combination against Staphylococcus pseudintermedius ; we did not aim at redefining clinical susceptibility, but at refining MIC determination to better guide pharmacodynamic study design. By providing more reliable thresholds for growth suppression, this approach supports optimisation of PD modelling and may ultimately inform translational applications, such as dose prediction and reducing misclassification in PD contexts. Visual MICs were compared to those derived from log ₁₀ changes in CFU/mL over 24 h, using pharmacodynamic thresholds of +2.3 log ₁₀ (growth from standard inoculum of 5 × 10 ⁵ to ~10 ⁸ CFU/mL, corresponding to visible growth MIC) and 0 log ₁₀ change (stationary concentration). Across 10 clinical isolates, visual MICs often underestimated the concentration required to suppress growth by 2–4 fold (more than one dilution step), particularly for sulphonamides. TMP‐sulphonamide combinations at a 1:19 ratio showed reduced trailing and closer agreement between visual and count‐based MICs, reflecting enhanced bactericidal activity. Time‐kill curve experiments anchored on the log ₁₀ count‐based MIC provided a well‐distributed range of PD responses, capturing both suppression and killing more accurately than curves centred on visual MICs. This method supports more rational selection of concentrations for PD studies and may be especially valuable for slow‐acting or ratio‐sensitive combinations, and has translational value for sulphonamides, such as sulfamethoxazole, used in both human and veterinary medicine.

Aims: This study assessed the pharmacodynamic (PD) efficacy and resistance selection risk of a novel sustained-release (SR) florfenicol formulation versus a conventional two-dose regimen for treating swine respiratory pathogens, with particular attention to potential impacts on non-target bacteria. Methods and results: Using a hollow-fibre infection model, simulated plasma pharmacokinetics for SR (30 mg kg−1, single dose) and conventional (2 × 15 mg kg−1, 48 h apart) formulations were emulated. Bactericidal efficacy was quantified against Actinobacillus pleuropneumoniae, Pasteurella multocida, and G. parasuis, while Escherichia coli was included to assess resistance emergence. Both formulations achieved rapid bacterial eradication in target pathogens with no regrowth. PD indices (fAUC/MIC, %fT > MIC) demonstrated comparable or superior exposures for the SR formulation. Median %fT within the mutant selection window (%fTMSW) was low across treatments: 2.9%–3.5% for A. pleuropneumoniae, 12.7%–15.7% for P. multocida, and 0% for E. coli. No resistant E. coli mutants emerged, one transient less-susceptible subpopulation (<0.0001%) with a 2-fold MIC increase (still below ECOFF) was transiently observed, and florfenicol concentrations remained below MIC and mutant prevention concentration thresholds. Conclusions: The SR formulation of florfenicol showed equivalent efficacy to conventional dosing against key swine respiratory pathogens and posed minimal risk for selecting resistance in non-target E. coli. This supports the SR formulation as an effective single-dose alternative in veterinary practice.

Antimicrobial resistance is a global threat to both human and animal health, and transfer of resistance between these spheres is recognised as a key concern for all species. Selection for resistance at sub-inhibitory antimicrobial concentrations has been characterised for some bacteria-antimicrobial combinations but there is little data from non-laboratory strains, and veterinary antimicrobials and bacterial species. Here, we demonstrate a minimum selective concentration of 0.06 mg/L (1/6 xMIC) for florfenicol in wild-type Pasteurella multocida, through competition experiments between a susceptible strain and a floR-resistant mutant. We also show that sub-inhibitory concentrations of florfenicol do not appear to significantly select for de novo resistance in P. multocida and present the challenges with adapting experimental protocols between bacterial species. These results have important implications for antimicrobial resistance selection at sub-inhibitory concentrations, method development for within-species differentiation in novel bacterial species, and application to policy regarding antimicrobial contamination in animal-feed.

This study examines the pharmacodynamics (PD) of florfenicol (FFN) for treating porcine respiratory diseases by comparing its effects on Glaesserella parasuis, Actinobacillus pleuropneumoniae and Pasteurella multocida. In vitro time‐kill assays and semi‐mechanistic PD modeling were used to assess bacterial growth and killing rates at varying FFN concentrations. Species‐specific PD models indicated that fAUC/MIC was the best PK/PD index across all species. A. pleuropneumoniae and P. multocida had target values of 1.05 and 1.66 × MIC, respectively for bacteriostasis and 1.12 and 1.87 × MIC for 99.9% kill. Two phenotypes of G. parasuis emerged “fast‐kill” and “slow‐kill” which displayed distinct bacterial eradication rates despite similar MICs. For “slow‐kill” isolates, an average free drug concentration (fAUC/MIC) of 1.46 and 1.63 × MIC (median, range: 1.53–1.69) was required for bacteriostasis and 99.9% kill. “Fast‐kill” isolates needed an average free drug concentration of 1.38 × MIC for bacteriostasis and 1.51 × MIC for a 99.9% reduction. Indicating that the rate of kill influences the respective average free concentration required to achieve an equivalent antibacterial effect. Simulations of clinical dosing of FFN predicted bacterial eradication for all species, highlighting the value of phenotype‐specific PD modeling in guiding treatment strategies for porcine respiratory infections.

The hollow-fibre infection model (HFIM) is a valuable in vitro platform for emulating antimicrobial drug pharmacokinetic profiles. Despite its potential, standardized protocols for HFIM operation, especially concerning fastidious organisms, are lacking. This study addresses this gap by examining challenges in culturing Pasteurella multocida and Actinobacillus pleuropneumoniae, two fastidious organisms, in the HFIM. Our findings reveal effective strategies to prevent system clogging, involving multiple freeze–thaw cycles of horse blood, centrifugation and cell straining to enhance the clarity of the Mueller-Hinton fastidious medium defined by the European Committee on Antimicrobial Susceptibility Testing and Clinical and Laboratory Standards Institute. Additionally, we propose that the provision of a CO₂ atmosphere, along with the utilization of gas-permeable tubing and gas vent filters, significantly facilitates the growth of fastidious organisms. Remarkably, both P. multocida and A. pleuropneumoniae were sustained for a period of up to 10 days under these optimized conditions. This study provides crucial insights into the modifications necessary to successfully culture fastidious organisms in the HFIM, paving the way for more accurate and representative in vitro models for antimicrobial drug testing. These advancements hold promise for advancing research in the field of antimicrobial pharmacokinetics and efficacy against challenging pathogens.

The Hollow-fibre Infection Model (HFIM) is a valuable in vitro platform for emulating antimicrobial drug (AMD) pharmacokinetic (PK) profiles. Despite its potential, standardized protocols for HFIM operation, especially concerning fastidious organisms, are lacking. This study addresses this gap by examining challenges in culturing Pasteurella multocida and Actinobacillus pleuropneumoniae, two fastidious organisms, in the HFIM. Our findings reveal effective strategies to prevent system clogging, involving multiple freeze-thaw cycles of horse blood, centrifugation, and cell straining to enhance the clarity of the Mueller-Hinton fastidious (MH-F) medium defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and Clinical and Laboratory Standards Institute (CLSI). Additionally, we propose that the provision of a CO2 atmosphere, along with the utilization of gas-permeable tubing and gas vent filters, significantly facilitates the growth of fastidious organisms. Remarkably, both P. multocida and A. pleuropneumoniae were sustained for a period of up to 10 days under these optimized conditions. This study provides crucial insights into the modifications necessary to successfully culture fastidious organisms in the HFIM, paving the way for more accurate and representative in vitro models for antimicrobial drug testing. These advancements hold promise for advancing research in the field of antimicrobial pharmacokinetics and efficacy against challenging pathogens.

The Hollow-fibre Infection Model (HFIM) is a valuable in vitro platform for emulating antimicrobial drug (AMD) pharmacokinetic (PK) profiles. Despite its potential, standardized protocols for HFIM operation, especially concerning fastidious organisms, are lacking. This study addresses this gap by examining challenges in culturing Pasteurella multocida and Actinobacillus pleuropneumoniae, two fastidious organisms, in the HFIM. Our findings reveal effective strategies to prevent system clogging, involving multiple freeze-thaw cycles of horse blood, centrifugation, and cell straining to enhance the clarity of the Mueller-Hinton fastidious (MH-F) medium defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and Clinical and Laboratory Standards Institute (CLSI). Additionally, we demonstrate that the provision of a CO2 atmosphere, along with the utilization of gas-permeable tubing and gas vent filters, significantly facilitates the growth of fastidious organisms. Remarkably, both P. multocida and A. pleuropneumoniae were sustained for a period of up to 10 days under these optimized conditions. This study provides crucial insights into the modifications necessary to successfully culture fastidious organisms in the HFIM, paving the way for more accurate and representative in vitro models for antimicrobial drug testing. These advancements hold promise for advancing research in the field of antimicrobial pharmacokinetics and efficacy against challenging pathogens.