The MICs used for pharmacokinetic/pharmacodynamic indices should be functions of the anticipated densities of the infecting population.

The successful treatment of bacterial infections is the product of a collaboration between antibiotics and the host's immune defenses. Nevertheless, in the design of antibiotic treatment regimens, few studies have explored the combined action of antibiotics and the immune response to clearing infections. Here, we use mathematical models to examine the collective contribution of antibiotics and the immune response to the treatment of acute, self-limiting bacterial infections. Our models incorporate the pharmacokinetics and pharmacodynamics of the antibiotics, the innate and adaptive immune responses, and the population and evolutionary dynamics of the target bacteria. We consider two extremes for the antibiotic-immune relationship: one in which the efficacy of the immune response in clearing infections is directly proportional to the density of the pathogen; the other in which its action is largely independent of this density. We explore the effect of antibiotic dose, dosing frequency, and term of treatment on the time before clearance of the infection and the likelihood of antibiotic-resistant bacteria emerging and ascending. Our results suggest that, under most conditions, high dose, full-term therapy is more effective than more moderate dosing in promoting the clearance of the infection and decreasing the likelihood of emergence of antibiotic resistance. Our results also indicate that the clinical and evolutionary benefits of increasing antibiotic dose are not indefinite. We discuss the current status of data in support of and in opposition to the predictions of this study, consider those elements that require additional testing, and suggest how they can be tested.population dynamics | immunology T he goals of antibiotic treatment of bacterial infections are straightforward and interrelated: to maximize the likelihood and rate of cure, to minimize the toxic and other deleterious side effects of treatment, and to minimize the likelihood of resistance emerging during the course of therapy. How does one choose the most effective antibiotic(s) for a given infection and determine its optimum dose, frequency, and term of administration to achieve these goals?One answer has been to combine in vitro studies of the pharmacodynamics (PD) of the antibiotics and bacteria and the in vivo pharmacokinetics (PK) of the antibiotics in treated patients or model organisms (1, 2). Central to this "rational" (as opposed to purely empirical) approach to antibiotic treatment are PK/PD indices. Although there have been efforts to develop more comprehensive measures of the relationship between the concentration of antibiotics and rate of bacterial growth (e.g., see refs. 3-5), in practice the lowest antibiotic concentration required to prevent the in vitro growth of the bacteria [the minimum inhibitory concentration (MIC)] is the sole pharmacodynamic parameter used for these indices (6). Depending on the drug, one of three PK parameters that quantify drug availability is combined with the MIC to generate these PK/PD indices: (i) the r...

The evolution of resistance to antimicrobial chemotherapy is a major and growing cause of human mortality and morbidity. Comparatively little attention has been paid to how different patient treatment strategies shape the evolution of resistance. In particular, it is not clear whether treating individual patients aggressively with high drug dosages and long treatment durations, or moderately with low dosages and short durations can better prevent the evolution and spread of drug resistance. Here, we summarize the very limited available empirical evidence across different pathogens and provide a conceptual framework describing the information required to effectively manage drug pressure to minimize resistance evolution.

The vibrational Stark effect (VSE) has proven to be an effective method for the study of electric fields in proteins via the use of infrared probes. In order to explore the use of VSE in nucleic acids, the Stark spectroscopy of nine structurally diverse nucleosides was investigated. These nucleosides contained nitrile or azide probes in positions that correspond to both the major and minor grooves of DNA. The nitrile probes showed better characteristics and exhibited absorption frequencies over a broad range; i.e., from 2253 cm −1 for 2′-O-cyanoethyl ribonucleosides 8 and 9 to 2102 cm −1 for a 13 C-labeled 5-thiocyanatomethyl-2'-deoxyuridine 3c. The largest Stark tuning rate observed was |Δµ| = 1.1 cm −1 /(MV/cm) for both 5-cyano-2′-deoxyuridine 1 and N2-nitrile-2′-deoxyguanosine 7. The latter is a particularly attractive probe because of its high extinction coefficient (ε = 412 M −1 cm −1 ) and ease of incorporation into oligomers.