In Vitro Models

In vitro infection models are dynamic systems designed to assess the effect of anti-infective drugs by mimicking human pharmacokinetics. This is accomplished through the controlled dilution of the drug- and organism-containing growth media. Many infection models have been developed over the years, including the following: bladder-infection, biofilm-catheter, infected fibrin clot, intracellular infection, and one-compartment models. Today, the most commonly employed system is the hollow-fiber infection model, which is also known as a two-compartment system (see figure below).

Data from these models can help answer basic pharmacology questions. Through dose fractionation studies, one can identify which pharmacokinetic-pharmacodynamic measure is most closely associated with drug effect and the magnitude of this measure necessary for acceptable drug effect. These models can also be utilized to evaluate resistance. For instance, studies can be designed to determine if drug-susceptible strains behave differently than drug-resistant strains or to determine the drug exposure needed to counter-select resistance. A major advantage of these systems is that it is possible to conduct studies that would not be possible in rodents. For example, these systems can be used to study organisms (e.g., Haemophilus influenzae) for which animal models have not been well-established or for diseases (e.g., HIV, tuberculosis models) which require longer treatment durations.

One Recent Application

Salmonella enterica serotype Typhi and nontyphoidal Salmonella remain major causes of morbidity and mortality worldwide. Ampicillin, trimethoprim-sulfamethoxazole, and chloramphenicol no longer provide reliable coverage of Salmonella, and fluoroquinolones have emerged as first-line treatment options. Due to mounting evidence of decreased in vitro susceptibility and diminished clinical response to fluoroquinolone therapy, it has been suggested that the CLSI (formally known as he NCCLS) breakpoints for the salmonellae be re-evaluated.

We utilized an in vitro infection model to determine which of three pharmacokinetic-pharmacodynamic (PK-PD) measures (free-drug ( f ) AUC0-24:MIC, f Cmax:MIC or the percentage time (T) during the dosing interval that free-drug concentrations remained above the MIC (T>MIC)) was most closely linked to fluoroquinolone activity against salmonellae, and the magnitude that corresponded to maximal activity. Monte Carlo simulation was utilized to determine the probability of attaining potential susceptibility breakpoints for three fluoroquinolones.

The f AUC0-24:MIC ratio was the PK-PD measure most predictive of efficacy, and a ratio of 105 corresponded to 90% of maximal activity (see figure below). Simulation results suggested susceptible breakpoints of 0.12 mg/L for ciprofloxacin and gatifloxacin and 0.25 mg/L for levofloxacin. These proposed breakpoints correspond to the MIC separating the wild-type susceptible organism population from those strains possessing single-step mutations in the quinolone resistance-determining region. These results that integrate PK-PD measures and fluoroquinolone MIC distributions in the genetic context of examined Salmonella isolates clearly demonstrate that the prudent use of a lower susceptibility breakpoint minimizes the probability of clinical failure or delayed response in fluoroquinolone-treated patients.