title: The pharmaco -, population and evolutionary dynamics of multi-drug therapy: experiments with S. aureus and E. coli and computer simulations.
abstract: There are both pharmacodynamic and evolutionary reasons to use multiple rather than single antibiotics to treat bacterial infections; in combination antibiotics can be more effective in killing target bacteria as well as in preventing the emergence of resistance. Nevertheless, with few exceptions like tuberculosis, combination therapy is rarely used for bacterial infections. One reason for this is a relative dearth of the pharmaco-, population- and evolutionary dynamic information needed for the rational design of multi-drug treatment protocols. Here, we use in vitro pharmacodynamic experiments, mathematical models and computer simulations to explore the relative efficacies of different two-drug regimens in clearing bacterial infections and the conditions under which multi-drug therapy will prevent the ascent of resistance. We estimate the parameters and explore the fit of Hill functions to compare the pharmacodynamics of antibiotics of four different classes individually and in pairs during cidal experiments with pathogenic strains of Staphylococcus aureus and Escherichia coli. We also consider the relative efficacy of these antibiotics and antibiotic pairs in reducing the level of phenotypically resistant but genetically susceptible, persister, subpopulations. Our results provide compelling support for the proposition that the nature and form of the interactions between drugs of different classes, synergy, antagonism, suppression and additivity, has to be determined empirically and cannot be inferred from what is known about the pharmacodynamics or mode of action of these drugs individually. Monte Carlo simulations of within-host treatment incorporating these pharmacodynamic results and clinically relevant refuge subpopulations of bacteria indicate that: (i) the form of drug-drug interactions can profoundly affect the rate at which infections are cleared, (ii) two-drug therapy can prevent treatment failure even when bacteria resistant to single drugs are present at the onset of therapy, and (iii) this evolutionary virtue of two-drug therapy is manifest even when the antibiotics suppress each other's activity.
authors.affiliation: Molecules to Mankind Program and Graduate Program in Population Biology, Ecology and Evolution, Laney Graduate School, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Peter
authors.initials: P
authors.lastname: Ankomah
authors.forename: Paul J T
authors.initials: PJ
authors.lastname: Johnson
authors.forename: Bruce R
authors.initials: BR
authors.lastname: Levin
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology* / Q000627:therapeutic use; D003198:Computer Simulation; D004338:Drug Combinations; D004347:Drug Interactions; D024881:Drug Resistance, Bacterial; D004359:Drug Therapy, Combination; D004926:Escherichia coli / Q000187:drug effects*; D004927:Escherichia coli Infections / Q000188:drug therapy* / Q000382:microbiology; D008826:Microbial Sensitivity Tests; D009010:Monte Carlo Method; D013203:Staphylococcal Infections / Q000188:drug therapy* / Q000382:microbiology; D013211:Staphylococcus aureus / Q000187:drug effects*
chemical_list: D000900:Anti-Bacterial Agents; D004338:Drug Combinations