Michael N. Dudley

Application of a mathematical model to prevent in vivo amplification of antibiotic-resistant bacterial populations during therapy

The worldwide increase in the prevalence of multi-antibiotic-resistant bacteria has threatened the physicians ability to provide appropriate therapy for infections. The relationship between antimicrobial drug concentration and infecting pathogen population reduction is of primary interest. Using data derived from mice infected with the bacterium Pseudomonas aeruginosa and treated with a fluoroquinolone antibiotic, a mathematical model was developed that described relationships between antimicrobial drug exposures and changes in drug-susceptible and -resistant bacterial subpopulations at an infection site. Dosing regimens and consequent drug exposures that amplify or suppress the emergence of resistant bacterial subpopulations were identified and prospectively validated. Resistant clones selected in vivo by suboptimal regimens were characterized. No mutations were identified in the quinolone resistance-determining regions of gyrA/B or parC/E. However, all resistant clones demonstrated efflux pump overexpression. At base line, MexAB-OprM, MexCD-OprJ, and MexEF-OprN were represented in the drug-resistant population. After 28 hours of therapy, MexCD-OprJ became the predominant pump expressed in the resistant clones. The likelihood of achieving resistance-suppression exposure in humans with a clinically prescribed antibiotic dose was determined. The methods developed in this study provide insight regarding how mathematical models can be used to identify rational dosing regimens that suppress the amplification of the resistant mutant population.

Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs

Over the last decades, the interest in the relationships between the pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobial agents has increased and, therefore, the use of PK/PD indices and expressions has spread widely. The appropriate definition and use of these parameters is a matter of controversy. This paper contains a proposal to use PK/PD expressions for antimicrobial agents and their units in a uniform manner.

Predicting efficacy of antiinfectives with pharmacodynamics and Monte Carlo simulation.

1. To describe how antibiotic absorption and elimination can vary depending on the route of administration, the age of the child and function of the organs involved in antibiotic metabolism. 2. To be able to discuss the fact that the antibiotic exposure to the pathogen, over time, varies from tissue to tissue but can be measured at many target sites where the infections actually occur, such as the bloodstream, cerebrospinal fluid or middle ear fluid. 3. To describe the variables providing data to the Monte Carlo simulation. 4. To recall that data used to describe the variables in a published Monte Carlo simulation in a journal may not necessarily reflect the data that would be used to describe those variables for a particular physician’s own patient.

Absence of TetB Identifies Minocycline-Susceptible Isolates of Acinetobacter baumannii

Minocycline is one of the few options available to treat infections caused by Acinetobacter baumannii. Acquired resistance to minocycline in A. baumannii is associated with presence of the TetB efflux pump. Previous studies suggested that the absence of tetB may predict minocycline minimum inhibitory concentrations (MICs) of ≤4 µg/mL. In this study, a collection of 258 A. baumannii isolates was used to generate MIC frequency distributions for the tetB-positive and -negative sets of isolates. Of the 93 tetB-negative strains, all had minocycline MICs ≤ 4 µg/mL, resulting in a negative predictive value of 100%. Of the 165 tetB-positive strains, 154 had minocycline MICs > 4 µg/mL, resulting in a positive predictive value of 93.3%. In conclusion, this study shows that tetB is highly associated with MICs above the current US Food and Drug Administration (FDA) and Clinical and Laboratory Standards Institute (CLSI) susceptible breakpoint of 4 µg/mL.