Superoxide (02-), hydrogen peroxide (H202), and lipid peroxides are generated in luteal tissue during natural and prostaglandin-induced regression in the rat, and this response is associated with reversible depletion of ascorbic acid. Reactive oxygen species immediately uncouple the luteinizing hormone receptor from adenylate cyclase and inhibit steroidogenesis by interrupting transmitochondrial cholesterol transport.7The cellular origin ofoxygen radicals in regressing corpora lutea is predominatelyfrom resident and infiltrated leukocytes, notably neutrophils. Reactive oxygen species are also produced within the follicle at ovulation and, like the corpus luteum, leukocytes are the major source of these products. Antioxidants block the resumption of meiosis, whereas the generation of reactive oxygen induces oocyte maturation in thefollicle.Although oxygen radicals may serve important physiologic roles within the ovary, the cyclic production of these damaging agents over years may lead to an increased cumulative risk of ovarian pathology that would probably be exacerbated under conditions of reduced antioxidant status.

Our objective was to prospectively determine the factors influencing the probability of a good microbiological or clinical outcome in patients with nosocomial pneumonia treated with a fluoroquinolone. Levofloxacin was administered as an infusion of 500 mg/h for 1.5 h (total dose, 750 mg). For patients with Pseudomonas aeruginosa or methicillin-resistant Staphylococcus aureus, a second drug was added (ceftazidime or piperacillin/tazobactam for P. aeruginosa and vancomycin for methicillin-resistant S. aureus). Population pharmacokinetic studies of 58 patients demonstrated that this population handled the drug differently from populations of volunteers. Multivariate logistic regression analysis (n=47 patients) demonstrated that only the age of the patient and the achievement of an area under the curve: minimum inhibitory concentration ratio of > or =87 had a significant effect on eradication of the pathogen (P<.001). Achieving the breakpoint made the patient 4 times more likely to achieve eradication. The effect was greatest in patients > or =67 years old.

One of the most challenging issues in the design of phase II/III clinical trials of antimicrobial agents is dose selection. The choice is often based on preclinical data from pharmacokinetic (PK) studies with animals and healthy volunteers but is rarely linked directly to the target organisms except by the MIC, an in vitro measure of antimicrobial activity with many limitations. It is the thesis of this paper that rational dose-selection decisions can be made on the basis of the pharmacodynamics (PDs) of the test agent predicted by a mathematical model which uses four data sets: (i) the distribution of MICs for clinical isolates, (ii) the distribution of the values of the PK parameters for the test drug in the population, (iii) the PD target(s) developed from animal models of infection, and (iv) the protein binding characteristics of the test drug. In performing this study with the new anti-infective agent evernimicin, we collected a large number (n ‫؍‬ 4,543) of recent clinical isolates of gram-positive pathogens (Streptococcus pneumoniae, Enterococcus faecalis and Enterococcus faecium, and Staphylococcus aureus) and determined the MICs using E-test methods (AB Biodisk, Stockholm, Sweden) for susceptibility to evernimicin. Population PK data were collected from healthy volunteers (n ‫؍‬ 40) and patients with hypoalbuminemia (n ‫؍‬ 12), and the data were analyzed by using NPEM III. PD targets were developed with a neutropenic murine thigh infection model with three target pathogens: S. pneumoniae (n ‫؍‬ 5), E. faecalis (n ‫؍‬ 2), and S. aureus (n ‫؍‬ 4). Drug exposure or the ratio of the area under the concentration-time curve/MIC (AUC/MIC) was found to be the best predictor of microbiological efficacy. There were three possible microbiological results: stasis of the initial inoculum at 24 h (10 7 CFU), log killing (pathogen dependent, ranging from 1 to 3 log 10 ), or 90% maximal killing effect (90% E max ). The levels of protein binding in humans and mice were similar. The PK and PD of 6 and 9 mg of evernimicin per kg of body weight were compared; the population values for the model parameters and population covariance matrix were used to generate five Monte Carlo simulations with 200 subjects each. The fractional probability of attaining the three PD targets was calculated for each dose and for each of the three pathogens. All differences in the fractional probability of attaining the target AUC/MIC in this PD model were significant. For S. pneumoniae, the probability of attaining all three PD targets was high for both doses. For S. aureus and enterococci, there were increasing differences between the 6-and 9-mg/kg evernimicin doses for reaching the 2 log killing (S. aureus), 1 log killing (enterococci), or 90% E max AUC/MIC targets. This same approach may also be used to set preliminary in vitro MIC breakpoints.The drug development process traditionally follows the initial "first-in-human" pharmacokinetic (PK) studies with phase II dose-finding studies. Such studies are often relatively small and provide litt...

Population pharmacokinetic modeling is a useful approach to obtaining estimates of both population and individual pharmacokinetic parameter values. The potential for relating pharmacokinetic parameters to pharmacodynamic outcome variables, such as efficacy and toxicity, exists. A logistic regression relationship between the probability of a successful clinical and microbiological outcome and the peak concentration-to-MIC ratio (and also the area under the plasma concentration-time curve [AUC]/MIC ratio) has previously been developed for levofloxacin; however, levofloxacin assays for determination of the concentration in plasma are not readily available. We attempted to derive and validate demographic variable models to allow prediction of the peak concentration in plasma and clearance (CL) from plasma for levofloxacin. Two hundred seventy-two patients received levofloxacin intravenously for the treatment of community-acquired infection of the respiratory tract, skin or soft tissue, or urinary tract, and concentrations in plasma, guided by optimal sampling theory, were obtained. Patient data were analyzed by the Non-Parametric Expectation Maximization approach. Maximum a posteriori probability Bayesian estimation was used to generate individual parameter values, including CL. Peak concentrations were simulated from these estimates. The first 172 patients were used to produce demographic models for the prediction of CL and the peak concentration. The remaining 100 patients served as the validation group for the model. A median bias and median precision were calculated. A two-compartment model was used for the population pharmacokinetic analysis. The mean CL and the mean volume of distribution of the central compartment (V 1) were 9.27 liters/h and 0.836 liter/kg, respectively. The mean values for the intercompartmental rate constants, the rate constant from the central compartment to the peripheral compartment (K cp) and the rate constant from the peripheral compartment to the central compartment (K pc), were 0.487 and 0.647 h−1, respectively. The mean peak concentration and the mean AUC values normalized to a dosage of 500 mg every 24 h were 8.67 μg/ml and 72.53 μg · h/ml, respectively. The variables included in the final model for the prediction of CL were creatinine clearance (CLCR), race, and age. The median bias and median precision were 0.5 and 18.3%, respectively. Peak concentrations were predicted by using the demographic model-predicted parameters of CL,V 1, K cp, andK pc, in the simulation. The median bias and the median precision were 3.3 and 21.8%, respectively. A population model of the disposition of levofloxacin has been developed. Population demographic models for the prediction of peak concentration and CL from plasma have also been successfully developed. However, the performance of the model for the prediction of peak concentration was likely insufficient to be of adequate clinical utility. The model for the prediction of CL was relatively robust, with acceptable bias and precision, and explained a reasonable amount of the variance in the CL of levofloxacin from plasma in the population (r 2 = 0.396). Estimated CLCR, age, and race were the final model covariates, with CLCRexplaining most of the population variance in the CL of levofloxacin from plasma. This model can potentially optimize the benefit derived from the pharmacodynamic relationships previously developed for levofloxacin.