Neural correlates of adherence to extended-release naltrexone pharmacotherapy in heroin dependence.

Injectable extended-release naltrexone (XRNTX) presents an effective therapeutic strategy for opioid addiction, however its utility could be hampered by poor adherence. To gain a better insight into this phenomenon, we utilized blood oxygenation level-dependent functional magnetic resonance imaging (fMRI) in conjunction with a validated cue-induced craving procedure to examine neural correlates of XRNTX adherence. We operationalized treatment adherence as the number of monthly XRNTX injections (range: 0-3) administered to a group of fully detoxified heroin-dependent subjects (n=32). Additional outcomes included urine toxicology screening and self-reported tobacco use. The presented heroin-related visual cues reliably elicited heroin craving in all tested subjects. Nine, five, three and 15 of the participants, respectively, received zero, one, two and three XRNTX injections, predicted by the individual baseline fMRI signal change in response to the cues in the medial prefrontal cortex, a brain region involved in inhibitory self-control and emotional appraisal. The incidence of opioid-positive urines during the XRNTX therapy was low and remained about half the pre-treatment rate after the XRNTX ended. During the treatment, cigarette smoking behaviors followed patterns of opioid use, while cocaine consumption was increased with reductions in opioid use. The present data support the hypothesis that medial prefrontal cortex functions are involved in adherence to opioid antagonist therapy. A potential role of concurrent non-opioid addictive substances consumption during the XRNTX pharmacotherapy warrants further investigation. Our findings set the stage for further bio-behavioral investigations of the mechanisms of relapse prevention in opioid dependence.

Pharmacokinetic/pharmacodynamic predictors of time to clinical resolution in patients with acute bacterial exacerbations of chronic bronchitis treated with a fluoroquinolone.

Forty nine subjects with acute bacterial exacerbations of chronic bronchitis (ABECB) treated with grepafloxacin were evaluated for parameters predictive of clinical outcome. Signs and symptoms associated with ABECB were serially collected and evaluated for changes. Coughs per day, sputum volume and the percentage of sputum neutrophils were associated with clinical outcome. A by groups analysis, based on clinical success was performed using Cox regression analysis to determine factors associated with time to clinical success and time to reduction in sputum volume, coughs per day and sputum neutrophil percent. Factors evaluated included AUIC (AUC/MIC), isolate species, years and type of underlying lung disease, alcohol use, smoking history and number of ABECB within the previous 12 months. AUIC<276 (mg h/l)/mg/l (P<0.03) and or the presence of mild bronchiectasis (P<0.01) were associated with longer time to clinical success. In addition a relationship was found between AUIC>212 (mg h/l)/mg/l (P<0.01) and AUIC>576 (mg h/l)/mg/l (P<0.02) and decreasing days to sputum volume reduction and coughs per day, respectively. A diagnosis of mild bronchiectasis prolonged the time to reduce coughs per day (P<0.03) and neutrophil percentage (P<0.01). Patients with mild bronchiectasis were found to have an increase in the time to clinical success, coughs per day improvement and sputum neutrophil percent improvement. AUIC is an important PK/PD parameter predictive of successful outcome in ABECB, even in subjects with mild bronchiectasis. Grepafloxicin has been withdrawn from sale since these studies were carried out. This work is published to illustrate the relationship between pharmacodynamics and clinical efficacy and the use of AUIC as a valuable predictive parameter for fluoroquinolones.

Comparison of the abilities of grepafloxacin and clarithromycin to eradicate potential bacterial pathogens from the sputa of patients with chronic bronchitis: influence of pharmacokinetic and pharmacodynamic variables.

A randomized open-label study was conducted to compare the pharmacokinetics and pharmacodynamics of grepafloxacin with those of clarithromycin in patients with chronic bronchitis whose sputa were colonized with potential bacterial pathogens. Patients received oral grepafloxacin 400 mg od for 10 days (n = 15) or oral clarithromycin 500 mg bd for 10 days (n = 10). Sputum samples were collected before the first dose, 1, 4 and 8 h after a dose on day 1 and then before a dose on days 2, 3, 5, 7 and 10 to determine the time to eradication (T(erad)) of the potential bacterial pathogens. Blood samples for measurement of grepafloxacin or clarithromycin and 14-hydroxyclarithromycin concentrations were obtained before a dose and 1, 2, 4, 8 and 12 h after doses on days 1 and 5. The area under the inhibitory serum concentration-time curve over 24 h (AUIC(24)), peak serum concentration:MIC ratio (C(max):MIC) and the percentage of the dosing interval during which the serum concentration exceeded the MIC (%tau >MIC) were calculated and serum inhibitory titres (SITs) were determined. Haemophilus spp. were the predominant potential bacterial pathogens and were recovered from the sputa of 24 patients. Strains of Streptococcus pneumoniae were isolated from two patients in the grepafloxacin group and a strain of Moraxella catarrhalis was isolated from one patient in the clarithromycin group. Haemophilus spp. isolates were eradicated from the sputa of 13 of 14 (93%) patients given grepafloxacin, but from only two of 10 (20%) patients given clarithromycin (P < 0.05). In the other eight (80%) patients who received clarithromycin, the sputum cultures remained positive throughout the 10 day course. Grepafloxacin eliminated potential bacterial pathogens more quickly than clarithromycin (median T(erad) 4 h versus 76 h). The S. pneumoniae strains were eradicated by grepafloxacin within 4 h and the single M. catarrhalis strain was eradicated by clarithromycin within 1 h. The greater efficacy of grepafloxacin, compared with that of clarithromycin, in terms of the incidence and speed of eradication of the Haemophilus spp. isolates, was associated with higher median values of AUIC(24) (169 SIT(-1)*h versus 8.1 SIT(-1)*h), C(max):MIC ratio (23.6 versus 0.7) and %tau >MIC (100% versus 0%). A Hill-type model adequately described the relationship between the percentage probability of eradicating potential bacterial pathogens from sputa and the plasma grepafloxacin concentration.

Pharmacodynamic modeling of risk factors for ciprofloxacin resistance in Pseudomonas aeruginosa.

OBJECTIVE: To determine risk factors for ciprofloxacin resistance in Pseudomonas aeruginosa. METHODS: Patients with cultures (any site) positive for P aeruginosa, susceptible to ciprofloxacin, between January 1993 and December 1996 were identified using a computerized database. Factors predictive of emergence of ciprofloxacin resistance in P aeruginosa strains isolated from the same cultured site, within 21 days of the initial culture, were determined. Factors considered included length of stay prior to initial P aeruginosa culture, isolation site, initial minimum inhibitory concentration (MIC), antibiotic area under the 24-hour concentration curve (AUC24), total area under the 24-hour inhibitory concentration curve ([AUIC24] AUC24/MIC summed for all active drugs), antibiotic(s) used as dichotomous variables (yes/no), and use of monotherapy or combination therapy. RESULTS: Of 635 patients, 43 (7%) subsequently had ciprofloxacin-resistant P aeruginosa isolated. Four significantly differing patient groups were identified: group 1, P aeruginosa isolates from all sites other than the respiratory tract, treated with any drugs; group 2, respiratory tract isolates treated with drugs other than ciprofloxacin; group 3, respiratory tract isolates treated with ciprofloxacin at AUIC24 >110 (microg x h/mL)/microg/mL; and group 4, respiratory tract isolates treated with ciprofloxacin at AUIC24 < or =110 (microg x h/mL)/microg/mL. The observed percentage resistant was a continuous function of prior length of stay in all four groups. Respiratory tract isolates had higher rates of ciprofloxacin resistance (12%) than isolates from other infection sites (4%). Respiratory tract isolates exposed to ciprofloxacin at AUIC24 < or =110 (microg x h/mL)/microg/mL had the highest resistance (17%). At AUIC24 >110 (microg x h/mL)/microg/mL, resistance was decreased to 11%, a rate similar to that seen in respiratory isolates not exposed to ciprofloxacin (7%). CONCLUSIONS: Application of pharmacokinetic and pharmacodynamic principles to dosing of ciprofloxacin may reduce the risk of ciprofloxacin resistance to the level seen in isolates exposed to other agents.

Potential role of pharmacokinetics, pharmacodynamics, and computerized databases in controlling bacterial resistance.

Bacterial resistance to antibiotics continues to be a problem, in spite of increased knowledge of resistance mechanisms. Due to the multifactorial nature of bacterial resistance, studies that evaluate the association between antimicrobial exposure and emergence of resistance may fail to find a relationship unless other factors, in particular the association between patient-pathogen pharmacokinetics (PK) and pharmacodynamics (PD) and the emergence of bacterial resistance, are evaluated as well. It has been hypothesized that, in conjunction with good infection control practices, cycling of antimicrobial agents may prove to be effective in reducing resistance emergence. There is some indication that there may be a relationship between the level of antibiotic exposure and the probability of emergence of bacterial resistance. As shown in our companion article in this supplement, factors associated with ciprofloxacin resistance in Pseudomonas aeruginosa included increased length of stay prior to isolation, exposure to ciprofloxacin, and respiratory tract site of bacterial isolation. However, in patients who received ciprofloxacin therapy, when exposure was at an area under the 24-hour inhibitory concentration curve (AUIC24)>110 (microg x h/mL)/microg/mL, resistance was decreased to 11%, a rate similar to that seen in respiratory isolates not exposed to ciprofloxacin (7%). While the length of time the patient spends in the hospital and the site of infection cannot be controlled, by using PK and PD principles for dosing of ciprofloxacin, the emergence of ciprofloxacin resistance in P aeruginosa may be reduced. Prospective antibiotic-cycling studies may help to determine not only the impact of antibiotic cycling on the institution's antibiogram but also, through the use of PK and PD principles, may help to determine appropriate dosing schedules for antibiotics in order to reduce the probability of emergence of bacterial resistance.

Genesis of methicillin-resistant Staphylococcus aureus (MRSA), how treatment of MRSA infections has selected for vancomycin-resistant Enterococcus faecium, and the importance of antibiotic management and infection control.

We extensively studied the epidemiology and time course of endemic methicillin-resistant Staphylococcus aureus (MRSA) in the Millard Fillmore Hospital, a 600-bed teaching hospital in Buffalo. The changeover from methicillin-susceptible S. aureus to MRSA begins on the first hospital day, when patients are given cefazolin as presurgical prophylaxis. Under selective antibiotic pressure, colonizing flora change within 24 to 48 hours. For patients remaining hospitalized, subsequent courses of third-generation cephalosporins further select and amplify the colonizing MRSA population. Therefore, managing antibiotic selective pressure might be essential. Other strategies include attention to dosing, so that serum concentrations of drug exceed the minimum inhibitory concentration, and antibiotic cycling. Although there are some promising new antibiotics on the horizon, it is necessary to deal with many resistance patterns by using the combined strategies of infection control and antibiotic management.

Pharmacodynamic evaluation of factors associated with the development of bacterial resistance in acutely ill patients during therapy.

The selection of bacterial resistance was examined in relationship to antibiotic pharmacokinetics (PK) and organism MICs in the patients from four nosocomial lower respiratory tract infection clinical trials. The evaluable database included 107 acutely ill patients, 128 pathogens, and five antimicrobial regimens. Antimicrobial pharmacokinetics were characterized by using serum concentrations, and culture and sensitivity tests were performed daily on tracheal aspirates to examine resistance. Pharmacodynamic (PD) models were developed to identify factors associated with the probability of developing bacterial resistance. Overall, in 32 of 128 (25%) initially susceptible cases resistance developed during therapy. An initial univariate screen and a classification and regression tree analysis identified the ratio of the area under the concentration-time curve from 0 to 24 h to the MIC (AUC[0-24]/MIC) as a significant predictor of the development of resistance (P < 0.001). The final PK/PD model, a variant of the Hill equation, demonstrated that the probability of developing resistance during therapy increased significantly when antimicrobial exposure was at an AUC[0-24]/MIC ratio of less than 100. This relationship was observed across all treatments and within all organism groupings, with the exception of beta-lactamase-producing gram-negative organisms (consistent with type I beta-lactamase producers) treated with beta-lactam monotherapy. Combination therapy resulted in much lower rates of resistance than monotherapy, probably because all of the combination regimens examined had an AUC[0-24]/MIC ratio in excess of 100. In summary, the selection of antimicrobial resistance appears to be strongly associated with suboptimal antimicrobial exposure, defined as an AUC[0-24]MIC ratio of less than 100.

Modeling the response of pneumonia to antimicrobial therapy.

The response to antimicrobial therapy in patients with pneumonia was assessed by using a previously developed pneumonia scoring system. Patients from two different clinical trials were evaluated. The first group (n = 22) was treated with cefmenoxime. For these patients, doses were adjusted to achieve an area under the plasma concentration-versus-time curve (AUC) above the MIC of 140 microg x h/ml and pneumonia response scores were evaluated retrospectively. The second group (n = 21) were treated with either ciprofloxacin (CIP) or ceftazidime (TAZ) in a randomized clinical trial. Here, doses were adjusted to achieve AUC from 0 to 24 h/MIC values that were > 250 SIT(-1) x h (estimate of the area under the curve of inverse serum inhibitory titer versus time) and pneumonia response scoring was concurrent. In both studies eradication of the pathogen was determined by serial endotracheal cultures and clinical parameters were scored daily. A decrease in total score was indicative of an improving clinical condition. The percent change in clinical daily score was determined for each day of treatment. The rate of clinical response was determined by linear regression of the percent change in daily clinical score versus time during the course of antimicrobial therapy. Factors predictive of time to eradication were explored by interval analysis. Logistic regression was used to determine the earliest time point in therapy at which treatment scores predicted outcome. Kruskal-Wallis analysis of variance was used for statistical analysis, and significance was accepted at P < 0.05. There were no differences in baseline scores at day one for the patients treated with different antibiotics (P = 0.58). For patients with pathogen eradication, a significant difference between the two studies in time to eradication was found: 4.8 days for cefmenoxime-treated patients and 1.4 days for CIP- or TAZ-treated patients (P < 0.001). For patients experiencing bacterial eradication, the rates of clinical change for cefmenoxime and CIP or TAZ treatment were similar (P = 0.77). For patients with organisms that were not eradicated, the rates of change were similar (P = 0.14). There was a significant difference in the rate of change for patients experiencing eradication compared with that for patients in which the organism persisted (P << 0.01). Both treatment group and rate were found to be predictive of days to eradication. There was a significant difference in the percent change in clinical score on day 3 of therapy for patients with bacteria that were eradicated versus those with persistent organisms (P < 0.01). The percent change was more predictive of outcome with each subsequent day. Patients who demonstrated a > or = 10% reduction in clinical score after 72 h of treatment had an 88% probability of bacterial eradication. The clinical scoring system is a useful tool for modeling the response of pneumonia to antimicrobial therapy. The ability to predict outcome relatively early in therapy, by using a scoring system of clinical parameters which can be routinely monitored, will aid in assessing the response to antimicrobial therapy in clinical as well as in research settings.

Comparative pharmacokinetics of oral ceftibuten, cefixime, cefaclor, and cefuroxime axetil in healthy volunteers.

STUDY OBJECTIVE: To compare the pharmacokinetics of ceftibuten, cefixime, ceturoxime axetil, and cefaclor after oral administration. DESIGN: Randomized, four-period, crossover study. SETTING: Hospital-based clinical research center. SUBJECTS: Healthy adult men and women volunteers. INTERVENTIONS: Single 400-mg doses of cefixime and ceftibuten, and 500-mg doses of cefuroxime axetil and cefaclor. MEASUREMENTS AND MAIN RESULTS: Serum concentrations were determined by high-performance liquid chromatography methods. The mean oral clearances of cefixime, cefuroxime axetil, and cefaclor were similar, ranging from 20.4-27.0 L/hour; clearance of ceftibuten was approximately 4-fold less, 5.45 L/hour. The serum half-lives of ceftibuten (2.35 hrs) and cefixime (2.38 hrs) were prolonged compared with those of cefuroxime axetil (1.30 hrs) and cefaclor (0.693 hr). These agents also differed in terms of time to maximum concentration, time to peak plasma level, area under the curve, and apparent volume of distribution, the last reflecting differences in biovailability. CONCLUSION: Ceftibuten had a relatively high time to maximum concentration and long half-life, resulting in a 3.5-fold higher area under the curve than cefixime, cefuroxime axetil, and cefaclor. These pharmacokinetic data can be used as a basis to compare the four oral cephalosporins; however, comparative susceptibility data must also be considered.

In nosocomial pneumonia, optimizing antibiotics other than aminoglycosides is a more important determinant of successful clinical outcome, and a better means of avoiding resistance.

In in vitro and animal models, antibiotics show good relationships between concentration and response, when response is quantified as the rate of bacterial eradication. The strength of these in vitro relationships promises their utility for dosage regimen design and predictable cure of infections such as nosocomial pneumonia. In spite of their intuitive logic, close relationships between dosage and bacterial eradication have not been easy to show in clinical studies of nosocomial pneumonia. Presumably, a variety of patient, disease, bacterial, and pharmacokinetic variables cloud these relationships in patients, and delay their elucidation in patient trials. Patients with serious infections like nosocomial pneumonia require bactericidal antimicrobial activity. Studies in our laboratory show that the minimum effective antimicrobial action is an area under the inhibitory titer (AUIC) of 125, in which AUIC is calculated as the 24 hour serum area under the curve (AUC) divided by the minimum inhibitory concentration (MIC) of the pathogen. This target AUIC may be achieved with either a single antibiotic or it can be the sum of AUIC values of two or more antibiotics. There is considerable variability in the actual AUIC value for patients when antibiotics are administered in their usual recommended dosages. Examples of this variance will be provided using aminoglycosides, fluoroquinolones, and beta-lactams. The achievement of minimally effective antibiotic action, consisting of an AUIC of at least 125, is associated with bacterial eradication in about 7 days for beta-lactams and quinolones. Adding an aminoglycoside to beta-lactams may produce a slight increase in their rate of bacterial killing in vivo, but because of their narrow therapeutic window, and the associated low doses in relation to MIC, there are situations in which the aminoglycosides may be unable to add sufficient additional AUIC. Antibiotic activity indices allow clinicians to evaluate individualized patient regimens. Furthermore, antibiotic activity is a predictable clinical endpoint with predictable clinical outcome. This value also is highly predictive of the development of bacterial resistance. Antimicrobial regimens that do not achieve an AUIC of at least 125 cannot prevent the selective pressure that leads to overgrowth of resistant bacterial subpopulations. The methods based on the determination of AUIC have clinical applicability in routine practice, through software developed for this purpose. These indices can assist with patient management strategies in a prospective manner because they can identify patients at high risk of therapeutic failure or acquired resistance early in therapy before therapy fails. Our studies show that calculations of AUIC can be used to prospectively target regimens to improve the chances of cure with nosocomial pneumonia and other serious infections. A clinical intervention team has been organized to optimize antimicrobial regimens as early in therapy as possible, to lower the high cost events such as failure and acquired bacterial resistance.

In vitro pharmacodynamics of piperacillin, piperacillin-tazobactam, and ciprofloxacin alone and in combination against Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter cloacae, and Pseudomonas aeruginosa.

The time-kill curve methodology was used to determine the pharmacodynamics of piperacillin, ciprofloxacin, piperacillin-tazobactam and the combinations piperacillin-ciprofloxacin and ciprofloxacin-piperacillin-tazobactam. Kill curve studies were performed for piperacillin, ciprofloxacin, and piperacillin-tazobactam at concentrations of 0.25 to 50 times the MICs for 13 strains of bacteria: four Pseudomonas aeruginosa, three Enterobacter cloacae, three Klebsiella pneumoniae, and three Staphylococcus aureus isolates (tazobactam concentrations of 0.5, 4, and 12 micrograms/ml). By using a sigmoid Emax model and nonlinear least squares regression, the 50% lethal concentrations and the maximum lethal rates of each agent were determined for each bacterial strain. For piperacillin-ciprofloxacin and ciprofloxacin-piperacillin-tazobactam, kill curve studies were performed with concentrations obtained by the fractional maximal effect method (R. C. Li, J. J. Schentag, and D. E. Nix, Antimicrob. Agents Chemother. 37:523-531, 1993) and from individual 50% lethal concentrations and maximum lethal rates. Ciprofloxacin-piperacillin-tazobactam was evaluated only against the four P. aeruginosa strains. Interactions between piperacillin and ciprofloxacin were generally additive. At physiologically relevant concentrations of piperacillin and ciprofloxacin, ciprofloxacin had the highest rates of killing against K. pneumoniae. Piperacillin-tazobactam (12 micrograms/ml) had the highest rate of killing against E. cloacae. Piperacillin-ciprofloxacin with relatively higher ciprofloxacin concentrations had the greatest killing rates against S. aureus. This combination had significantly higher killing rates than piperacillin (P < 0.002). For all the bacterial strains tested, killing rates by ciprofloxacin were significantly higher than those by piperacillin-tazobactam (4 and 12 micrograms/ml had significantly higher killing rates than piperacillin alone (P < 0.02 and P < 0.004, respectively). The effect of the combination of piperacillin-ciprofloxacin, in which piperacillin concentrations were relatively higher, was not statistically different from that of piperacillin alone (p > or = 0.71). The combination of ciprofloxacin-piperacillin-tazobactam achieved greater killing than other combinations or monotherapies against P. aeruginosa. The reduction in the initial inoculum was 1 to 4 logs greater with ciprofloxacin-piperacillin-tazobactam at 4 and 12 micrograms/ml than with any other agent or combination of agents. On the basis of the additive effects prevalently demonstrated in the in vitro study, the combinations of piperacillin-ciprofloxacin and piperacillin-tazobactam are rational therapeutic options. Greater killing of P. aeruginosa was demonstrated with ciprofloxacin-piperacillin--tazobactam. Since treatment failure of P. aeruginosa pneumonia is a significant problem, clinical studies are warranted.

The importance of pharmacokinetic/pharmacodynamic surrogate markers to outcome. Focus on antibacterial agents.

Pharmacokinetic/pharmacodynamic surrogate relationships have been used to describe the antibacterial activity of various classes of antimicrobial agents. Studies that have evaluated these relationships were reviewed to determine which of these surrogate markers were further dependent on antimicrobial class. The fluoroquinolone and aminoglycoside agents exhibit concentration-dependent killing. Studies have demonstrated that peak serum concentration: minimum inhibitory concentration (MIC) and area under the serum concentration-time curve (AUC): MIC ratios are important predictors of outcome for these antimicrobial agents. Area under the inhibitory concentration-time curve (AUIC24) [i.e. AUC24/MIC] is a useful parameter for describing efficacy for these agents, while an adequate peak concentration: MIC ratio seems necessary to prevent selection of resistant organisms. For beta-lactam antibiotics, the duration of time that the serum concentration exceeds the MIC (T > MIC) was the significant pharmacokinetic/pharmacodynamic surrogate in cases where the bacterial inoculum was low, or where very sensitive organisms were tested. However, in studies using more resistant organisms or larger inoculum sizes there is some concentration-dependence to the observed effect. Studies using reasonable dosage intervals have demonstrated covariance between T > MIC and AUC/MIC ratio for beta-lactam antibiotics. Since glycopeptide antibiotics display relatively slow but concentration-independent killing, and are cell wall active agents similar to beta-lactams, it has been presumed that T > MIC is the important pharmacokinetic surrogate related to efficacy for these agents. Some studies have shown that a concentration multiple of the MIC may be necessary for successful outcome with vancomycin. AUIC24 may prove to be an important pharmacokinetic surrogate if both time and concentration are indeed important parameters. To select an appropriate antimicrobial agent, the clinician must consider many patient-specific as well as organism-specific factors. Utilisation of known pharmacokinetic/pharmacodynamic surrogate relationships should help to optimise treatment outcome.

Pharmacokinetic and pharmacodynamic activities of ciprofloxacin against strains of Streptococcus pneumoniae, Staphylococcus aureus, and Pseudomonas aeruginosa for which MICs are similar.

The serum bactericidal activity of ciprofloxacin against strains of Streptococcus pneumoniae, Staphylococcus aureus, and Pseudomonas aeruginosa for which MICs are similar (0.4 microgram/ml) was assessed with serum ultrafiltrates from five healthy volunteers receiving ciprofloxacin at 400 mg intravenously every 8 h. In addition, human serum was supplemented with ciprofloxacin to achieve a mean steady-state concentration (Css) that might be achieved in patients with renal failure, with total clearances of 3 to 4 liters/h (elimination rate constant, 0.08 h-1). The area under the inhibitory titer curve from 0 to 24 h (AUIC24) and the area under the bactericidal titer curve from 0 to 24 h (AUBC24) were both measured and predicted as the area under the concentration-time curve from 0 to 24 h (AUC24)/MIC and AUC24/MBC, respectively. We previously demonstrated that a breakpoint AUC24/MIC of 125 for ciprofloxacin had a significantly higher probability of treatment success than lower values, with 250 to 500 being optimal. Volunteer sera (mean Css, 1.55 to 2.48 micrograms/ml) achieved AUC24/MICs of 90 to 145. Supplemented serum (mean Css, 6.00 to 7.42 micrograms/ml) achieved AUC24/MICs of 350 to 450. Correlation coefficients for measured and predicted values of AUC24/MIC and AUC24/MBC were 0.826 and 0.941, respectively. The mean percent errors were not significantly different from zero for either AUIC24 or AUBC24 values (P > 0.1, P > 0.4). Time-kill curve studies were performed with low (1.55 to 2.48 micrograms/ml), intermediate (6.00 to 7.42 micrograms/ml), and high (15 to 25 micrograms/ml) concentrations of ciprofloxacin for the three organisms. At low concentrations (3 to 6 times the MIC) AUC24/MICs were <125 for two of five volunteers and the killing rates were considerably more rapid for P. aeruginosa than for S. pneumoniae or S.aureus. Intermediate concentrations (15 to 18 times the MIC) achieved optimal AUC24/MICs, and the killing rates were similar for the three organisms. A paradoxical decrease in the killing rate was seen at high concentrations (35 to 60 times the MIC). At clinically achievable concentrations, ciprofloxacin killed P. aeruginosa more rapidly than it did either S. pneumoniae or S. aureus.