scholarly journals Inter- and Intraquinolone Predictors of Antimicrobial Effect in an In Vitro Dynamic Model: New Insight into a Widely Used Concept

1998 ◽  
Vol 42 (3) ◽  
pp. 659-665 ◽  
Author(s):  
Alexander A. Firsov ◽  
Alexander A. Shevchenko ◽  
Sergey N. Vostrov ◽  
Stephen H. Zinner
Keyword(s):  
Dynamic Model ◽  
Half Life ◽  
Antimicrobial Effect ◽  
Data Sets ◽  
Time Curve ◽  
Linear Relationships ◽  
Control Growth ◽  
Dosing Regimens ◽  
Time Kill

ABSTRACT Earlier efforts to search for pharmacokinetic and bacteriological predictors of fluoroquinolone antimicrobial effects (AMEs) have resulted in conflicting findings. To elucidate whether these conflicts are real or apparent, several predictors of the AMEs of two pharmacokinetically different antibiotics, trovafloxacin (TRO) and ciprofloxacin (CIP), as well as different dosing regimens of CIP were examined. The AMEs of TRO given once daily (q.d.) and CIP given q.d. and twice daily (b.i.d.) against Escherichia coli,Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied in an in vitro dynamic model. Different monoexponential pharmacokinetic profiles were simulated with a TRO half-life of 9.2 h and a CIP half-life of 4.0 h to provide similar eightfold ranges of the area under the concentration-time curve (AUC)-to-MIC ratios, from 54 to 432 and from 59 to 473 (μg · h/ml)/(μg/ml), respectively. In each case the observation periods were designed to incorporate full-term regrowth phases in the time-kill curves, and the AME was expressed by its intensity (IE ; the area between the control growth and time-kill and regrowth curves up to the point at which the viable counts of regrowing bacteria are close to the maximum values observed without drug). Species-independent linear relationships were established between IE and log AUC/MIC, log AUC above MIC (log AUCeff), and time above the MIC (T eff). Specific and nonsuperimposedIE versus log AUC/MIC or log AUCeffrelationships were inherent in each of the treatments: TRO given q.d. (r 2 = 0.97 and 0.96), CIP given q.d. (r 2 = 0.98 and 0.96), and CIP given b.i.d. (r 2 = 0.95 and 0.93). This suggests that in order to combine data sets obtained with individual quinolones to examine potential predictors, one must be sure that these sets may be combined. Unlike AUC/MIC and AUCeff, the IE -T effrelationships plotted for the different quinolones and dosing regimens were nonspecific and virtually superimposed (r 2 = 0.95). Hence, AUC/MIC, AUCeff, and T eff were equally good predictors of the AME of each of the quinolones and each dosing regimen taken separately, whereas T eff was also a good predictor of the AMEs of the quinolones and their regimens taken together. However, neither the quinolones nor the dosing regimens could be distinguished solely on the basis of T eff, whereas they could be distinguished on the basis of AUC/MIC or AUCeff. Thus, two types of predictors of the quinolone AME may be identified: intraquinolone and/or intraregimen predictors (AUC/MIC, AUCeff and Teff) and an interquinolone and interregimen predictor (T eff). T eff may be able to accurately predict the AME of one quinolone on the basis of the data obtained for another quinolone.

scholarly journals Relationships of the Area under the Curve/MIC Ratio to Different Integral Endpoints of the Antimicrobial Effect: Gemifloxacin Pharmacodynamics in an In Vitro Dynamic Model

2001 ◽  
Vol 45 (3) ◽  
pp. 927-931 ◽  
Author(s):  
Alexander A. Firsov ◽  
Irene Y. Lubenko ◽  
Yury A. Portnoy ◽  
Stephen H. Zinner ◽  
Sergey N. Vostrov
Keyword(s):  
Area Under The Curve ◽  
Antimicrobial Effect ◽  
Time Curve ◽  
Marginal Value ◽  
Actual Effect ◽  
Control Growth ◽  
Effect Duration ◽  
Kill Curve ◽  
Time Kill

ABSTRACT Most integral endpoints of the antimicrobial effect are determined over an arbitrarily chosen time period, such as the dosing interval (τ), regardless of the actual effect duration. Unlike the τ-related endpoints, the intensity of the antimicrobial effect (I E) does consider its duration—from time zero to the time when bacterial counts on the regrowth curve achieve the same maximal numbers as in the absence of the antimicrobial. To examine the possible impact of this fundamental difference on the relationships of the antimicrobial effect to the ratio of the area under the concentration-time curve (AUC) to the MIC, a clinical isolate ofStaphylococcus aureus was exposed to simulated gemifloxacin pharmacokinetics over a 40-fold range of AUC/MIC ratios, from 11 to 466 h. In each run, I E and four τ-related endpoints, including the area under the time-kill curve (AUBC), the area above the curve (AAC), the area between the control growth and time-kill curves (ABBC), and the ABBC related to the area under the control growth curve (AUGC), were calculated for τ = 24 h. Unlike the I E, which displayed pseudolinear relationships with the AUC/MIC ratio; each τ-related endpoint showed a distinct saturation at potentially therapeutic AUC/MIC ratios (116 to 466 h) when the antimicrobial effect persisted longer than τ. This saturation results from the underestimation of the true effect and may be eliminated if ABBC, AAC, and AUBC (but not AUGC) are modified and determined in the same manner as the I E to consider the actual effect duration. These data suggest a marginal value of the τ-related endpoints as indices of the total antimicrobial effect. Since all of them respond to AUC/MIC ratio changes less than theI E, the latter is preferable in comparative pharmacodynamic studies.

scholarly journals A New Approach to In Vitro Comparisons of Antibiotics in Dynamic Models: Equivalent Area under the Curve/MIC Breakpoints and Equiefficient Doses of Trovafloxacin and Ciprofloxacin against Bacteria of Similar Susceptibilities

1998 ◽  
Vol 42 (11) ◽  
pp. 2841-2847 ◽  
Author(s):  
Alexander A. Firsov ◽  
Sergey N. Vostrov ◽  
Alexander A. Shevchenko ◽  
Yury A. Portnoy ◽  
Stephen H. Zinner
Keyword(s):  
Antimicrobial Agents ◽  
Dynamic Models ◽  
Area Under The Curve ◽  
Time Curve ◽  
Linear Relationships ◽  
Control Growth ◽  
Wide Range ◽  
Equivalent Area ◽  
Time Kill

ABSTRACT Time-kill studies, even those performed with in vitro dynamic models, often do not provide definitive comparisons of different antimicrobial agents. Also, they do not allow determinations of equiefficient doses or predictions of area under the concentration-time curve (AUC)/MIC breakpoints that might be related to antimicrobial effects (AMEs). In the present study, a wide range of single doses of trovafloxacin (TR) and twice-daily doses of ciprofloxacin (CI) were mimicked in an in vitro dynamic model. The AMEs of TR and CI against gram-negative bacteria with similar susceptibilities to both drugs were related to AUC/MICs that varied over similar eight-fold ranges [from 54 to 432 and from 59 to 473 (μg · h/ml)/(μg/ml), respectively]. The observation periods were designed to include complete bacterial regrowth, and the AME was expressed by its intensity (the area between the control growth in the absence of antibiotics and the antibiotic-induced time-kill and regrowth curves up to the point where viable counts of regrowing bacteria equal those achieved in the absence of drug [I E]). In each experiment monoexponential pharmacokinetic profiles of TR and CI were simulated with half-lives of 9.2 and 4.0 h, respectively. Linear relationships between I E and log AUC/MIC were established for TR and CI against three bacteria: Escherichia coli (MIC of TR [MICTR] = 0.25 μg/ml; MIC of CI [MICCI] = 0.12 μg/ml), Pseudomonas aeruginosa (MICTR = 0.3 μg/ml; MICCI = 0.15 μg/ml), and Klebsiella pneumoniae(MICTR = 0.25 μg/ml; MICCI = 0.12 μg/ml). The slopes and intercepts of these relationships differed for TR and CI, and the I E-log AUC/MIC plots were not superimposed, although they were similar for all bacteria with a given antibiotic. By using the relationships betweenI E and log AUC/MIC, TR was more efficient than CI. The predicted value of the AUC/MIC breakpoint for TR [mean for all three bacteria, 63 (μg · h/ml)/(μg/ml)] was approximately twofold lower than that for CI. Based on theI E-log AUC/MIC relationships, the respective dose (D)-response relationships were reconstructed. Like the I E-log AUC/MIC relationships, theI E-log D plots showed TR to be more efficient than CI. Single doses of TR that are as efficient as two 500-mg doses of CI (500 mg given every 12 h) were similar for the three strains (199, 226, and 203 mg). This study suggests that in vitro evaluation of the relationships between I E and AUC/MIC or D might be a reliable basis for comparing different fluoroquinolones and that the results of such comparative studies may be highly dependent on their experimental design and datum quantitation.

scholarly journals Parameters of bacterial killing and regrowth kinetics and antimicrobial effect examined in terms of area under the concentration-time curve relationships: action of ciprofloxacin against Escherichia coli in an in vitro dynamic model.

1997 ◽  
Vol 41 (6) ◽  
pp. 1281-1287 ◽  
Author(s):  
A A Firsov ◽  
S N Vostrov ◽  
A A Shevchenko ◽  
G Cornaglia
Keyword(s):  
Escherichia Coli ◽  
Zero Point ◽  
Antimicrobial Effect ◽  
Time Shift ◽  
Independent Effect ◽  
Time Curve ◽  
Bacterial Killing ◽  
Control Growth ◽  
Observation Period

Although many parameters have been described to quantitate the killing and regrowth of bacteria, substantial shortcomings are inherent in most of them, such as low sensitivity to pharmacokinetic determinants of the antimicrobial effect, an inability to predict a total effect, insufficient robustness, and uncertain interrelations between the parameters that prevent an ultimate determination of the effect. To examine different parameters, the kinetics of killing and regrowth of Escherichia coli (MIC, 0.013 microg/ml) were studied in vitro by simulating a series of ciprofloxacin monoexponential pharmacokinetic profiles. Initial ciprofloxacin concentrations varied from 0.02 to 19.2 microg/ml, whereas the half-life of 4 h was the same in all experiments. The following parameters were calculated and estimated: the time to reduce the initial inoculum (N0) 10-, 100-, and 1,000-fold (T90%, T99%, and T99.9%, respectively), the rate constant of bacterial elimination (k(elb)), the nadir level (Nmin) in the viable count (N)-versus-time (t) curve, the time to reach Nmin (t(min)), the numbers of bacteria that survived (Ntau) by the end of the observation period (tau), the area under the bacterial killing and regrowth curve (log N(A)-t curve) from the zero point (time zero) to tau (AUBC), the area above this curve (AAC), the area between the control growth curve (log N(C)-t curve) and the bacterial killing and regrowth curve (log N(A)-t curve) from the zero point to tau (ABBC) or to the time point when log N(A) reaches the maximal values observed in the log N(C)-t curve (I(E); intensity of the effect), and the time shift between the control growth and regrowth curves (T(E); duration of the effect). Being highly sensitive to the AUC, I(E), and T(E) showed the most regular AUC relationships: the effect expressed by I(E) or T(E) increased systematically when the AUC or initial concentration of ciprofloxacin rose. Other parameters, especially T90%, T99%, T99.9%, t(min), and log N0 - log Nmin = delta log Nmin, related to the AUC less regularly and were poorly sensitive to the AUC. T(E) proved to be the best predictor and t(min) proved to be the worst predictor of the total antimicrobial effect reflected by I(E). Distinct feedback relationships between the effect determination and the experimental design were demonstrated. It was shown that unjustified shortening of the observation period, i.e., cutting off the log N(A)-t curves, may lead to the degeneration of the AUC-response relationships, as expressed by log N0 - log Ntau = delta log Ntau, AUBC, AAC, or ABBC, to a point where it gives rise to the false idea of an AUC- or concentration-independent effect. Thus, use of I(E) and T(E) provides the most unbiased, robust, and comprehensive means of determining the antimicrobial effect.

scholarly journals MIC-Based Interspecies Prediction of the Antimicrobial Effects of Ciprofloxacin on Bacteria of Different Susceptibilities in an In Vitro Dynamic Model

1998 ◽  
Vol 42 (11) ◽  
pp. 2848-2852 ◽  
Author(s):  
Alexander A. Firsov ◽  
Sergey N. Vostrov ◽  
Alexander A. Shevchenko ◽  
Stephen H. Zinner ◽  
Giuseppe Cornaglia ◽  
...  
Keyword(s):  
Dynamic Model ◽  
Bacterial Species ◽  
Maximal Effect ◽  
Bacterial Strains ◽  
Time Curve ◽  
Antimicrobial Effects ◽  
E Coli ◽  
Kill Curve ◽  
Time Kill

ABSTRACT Multiple predictors of fluoroquinolone antimicrobial effects (AMEs) are not usually examined simultaneously in most studies. To compare the predictive potentials of the area under the concentration-time curve (AUC)-to-MIC ratio (AUC/MIC), the AUC above MIC (AUCeff), and the time above MIC (T eff), the kinetics of killing and regrowth of four bacterial strains exposed to monoexponentially decreasing concentrations of ciprofloxacin were studied in an in vitro dynamic model. The MICs of ciprofloxacin for clinical isolates ofStaphylococcus aureus, Escherichia coli11775 (I) and 204 (II), and Pseudomonas aeruginosa were 0.6, 0.013, 0.08, and 0.15 μg/ml, respectively. The simulated values of AUC were designed to provide similar 1,000-fold (S. aureus, E. coli I, and P. aeruginosa) or 2,000-fold (E. coli II) ranges of the AUC/MIC. In each case except for the highest AUC/MIC ratio, the observation periods included complete regrowth in the time-kill curve studies. The AME was expressed by its intensity,I E (the area between the control growth and time-kill and regrowth curves up to the point where the viable counts of regrowing bacteria are close to the maximum values observed without drug). For most AUC ranges the I E-AUC curves were fitted by an E max (maximal effect) model, whereas the effects observed at very high AUCs were greater than those predicted by the model. The AUCs that produced 50% of maximal AME were proportional to the MICs for the strains studied, but maximal AMEs (I E max ) and the extent of sigmoidicity (s) were not related to the MIC. BothT eff and log AUC/MIC correlated well withI E (r 2 = 0.98 in both cases) in a species-independent fashion. UnlikeT eff or log AUC/MIC, a specific relationship between I E and log AUCeff was inherent in each strain. Although each I E and log AUCeff plot was fitted by linear regression (r 2 = 0.97 to 0.99), these plots were not superimposed and therefore are bacterial species dependent. Thus, AUC/MIC and T eff were better predictors of ciprofloxacin’s AME than AUCeff. This study suggests that optimal predictors of the AME produced by a given quinolone (intraquinolone predictors) may be established by examining its AMEs against bacteria of different susceptibilities.T eff was shown previously also to be the best interquinolone predictor, but unlike AUC/MIC, it cannot be used to compare different quinolones. AUC/MIC might be the best predictor of the AME in comparisons of different quinolones.

scholarly journals Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model.

1996 ◽  
Vol 40 (3) ◽  
pp. 627-632 ◽  
Author(s):  
K J Madaras-Kelly ◽  
B E Ostergaard ◽  
L B Hovde ◽  
J C Rotschafer
Keyword(s):  
Antibacterial Effect ◽  
Antimicrobial Effect ◽  
Time Curve ◽  
Emax Model ◽  
Concentration Time ◽  
Mueller Hinton ◽  
Kill Curve ◽  
Time Kill ◽  
Mueller Hinton Broth

Several investigators have suggested that the 24-h area under the concentration-time curve (AUC)/MIC ratio (AUC/MIC24 or AUIC24) can be used to make comparisons of antimicrobial activity between fluoroquinolone antibiotics. Limited data exist regarding the generic predictive ability of AUC/MIC24 for the antimicrobial effects of fluoroquinolones. The purposes of the present investigation were to determine if the AUC/MIC24 can be used as a generic outcome predictor of fluoroquinolone antibacterial activity and to determine if a similar AUC/MIC24 breakpoint can be established for different fluoroquinolones. Using an in vitro pharmacodynamic model, 29 duplicate concentration time-kill curve experiments simulated AUC/MIC24s ranging from 52 to 508 SIT-1.h (inverse serum inhibitory titer integrated over time) with ciprofloxacin or ofloxacin against three strains of Pseudomonas aeruginosa. Each 24-h experiment was performed in cation-supplemented Mueller-Hinton broth with a starting inoculum of 10(6) CFU/ml. At timed intervals cation-supplemented Mueller-Hinton broth samples were collected for CFU and fluoroquinolone concentration determinations. Transformation of bacterial counts into the cumulative bacterial effect parameter of the 24-h area under the effect curve (AUEC24) was performed for each concentration time-kill curve. Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC24, 24-h AUC, peak concentration [Cmax] to MIC ratios [Cmax:MIC], etc.) with ln AUEC24. To identify threshold breakpoint AUC/MIC24s, AUEC24s were stratified by the magnitude of AUC/MIC24 into subgroups, which were analyzed for differences in antibacterial effect. The Kruskal-Wallis test and subsequent Tukey's multiple comparison test were used to determine which AUC/MIC subgroups were significantly different. Multiple regression analysis revealed that only AUC/MIC24 (r2 = 0.65) and MIC (r2 = 0.03) were significantly correlated with antibacterial effect. At similar AUC/MIC24s, yet different MICs, Cmaxs, or elimination half-lives, the AUEC24s were similar for both fluoroquinolones. The relationship between AUC/MIC24 and ln AUEC24 was best described by a sigmoidal maximal antimicrobial effect (Emax) model (r2 = 0.72; Emax = 9.1; AUC/MIC50 = 119 SIT-1.h; S = 2.01 [S is an exponent that reflects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC24 values of < 100 SIT-1.h were significantly different (P < 0.05) from the AUC/MIC24 values of > 100 SIT-1.h. An ofloxacin AUC/MIC24 of > 100 SIT-1.h and an AUC/MIC24 of < 100 SIT-1.h exhibited a trend toward a significant difference (P > 0.05 but < 0.1). The inverse relationship between drug exposure and MIC increase postexposure was described by a sigmoidal fixed Emax model (AUC/MIC24, r2 = 0.40; AUC/MIC50 = 95 SIT-1.h; S = 1.97; Cmax:MIC, r2 = 0.41; Cmax:MIC50 = 7.3; S = 2.01). These data suggest that AUC/MIC24 may be the most descriptive measurement of fluoroquinolone antimicrobial activity against P. aeruginosa, that ofloxacin and ciprofloxacin have similar AUC/MIC24 threshold breakpoints at approximately 100 SIT-1.h, that the concentration-dependent selection of resistant organisms may parallel the threshold breakpoint of the antimicrobial effect, and that AUC/MIC24 generically describes the antibacterial effects of different fluoroquinolones.

scholarly journals Comparative Pharmacodynamics of Gatifloxacin and Ciprofloxacin in an In Vitro Dynamic Model: Prediction of Equiefficient Doses and the Breakpoints of the Area under the Curve/MIC Ratio

2000 ◽  
Vol 44 (4) ◽  
pp. 879-884 ◽  
Author(s):  
Sergey N. Vostrov ◽  
Olga V. Kononenko ◽  
Irene Y. Lubenko ◽  
Stephen H. Zinner ◽  
Alexander A. Firsov
Keyword(s):  
Present Report ◽  
Area Under The Curve ◽  
Antimicrobial Effect ◽  
Time Curve ◽  
E Coli ◽  
Clinical Dose ◽  
Linear Relationships ◽  
New Quinolones ◽  
The Impact

ABSTRACT To demonstrate the impact of the pharmacokinetics of gatifloxacin (GA) relative to those of ciprofloxacin (CI) on the antimicrobial effect (AME), the killing and regrowth kinetics of two differentially susceptible clinical isolates each of Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae were studied. With each organism, a series of monoexponential pharmacokinetic profiles of GA (half-life [t 1/2], 7 h) and CI (t 1/2 = 4 h) were simulated to mimic different single doses of GA and two 12-h doses of CI. The respective eightfold ranges of the ratios of the area under the concentration-time curve (AUC) to the MIC were 58 to 466 and 116 to 932 (μg · h/ml)/(μg/ml). The species- and strain-independent linear relationships observed between the intensity of AME (IE ) and log AUC/MIC were not superimposed for GA and CI (r 2 = 0.99 in both cases). The predicted AUC/MIC ratio for GA that might be equivalent to a clinically relevant AUC/MIC breakpoint for CI was estimated to be 102 rather than 125 (μg · h/ml)/(μg/ml). The respective MIC breakpoints were 0.32 μg/ml (for a 400-mg dose of GA) and 0.18 μg/ml (for two 500-mg doses of CI). On the basis of the IE -log AUC/MIC relationships, equiefficient 24-h doses (D 24hs) of GA and CI were calculated for hypothetical strains of S. aureus, E. coli, andK. pneumoniae for which the MICs were equal to the MICs at which 50% of isolates are inhibited. To provide an “acceptable”IE equal to 200 (log CFU/ml) · h, i.e., the IE provided by AUC/MIC of 125 (μg · h/ml)/(μg/ml) for ciprofloxacin, theD 24hs of GA for all three organisms were much lower (115, 30, and 60 mg) than the clinically proposed 400-mg dose. Although the usual dose of CI (two doses of 500 mg) would be in excess for E. coli and K. pneumoniae(D 24h = two doses of 40 mg and two doses of 115 mg, respectively), even the highest clinical dose of CI (two doses of 750 mg) might be insufficient for S. aureus(D 24h, > two doses of 1,000 mg). The method of generalization of data obtained with specific organisms to other representatives of the same species described in the present report might be useful for prediction of the AMEs of new quinolones.

scholarly journals Verification of a Novel Approach to Predicting Effects of Antibiotic Combinations: In Vitro Dynamic Model Study with Daptomycin and Gentamicin against Staphylococcus aureus

Antibiotics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 538
Author(s):  
Maria V. Golikova ◽  
Elena N. Strukova ◽  
Yury A. Portnoy ◽  
Stephen H. Zinner ◽  
Alexander A. Firsov
Keyword(s):  
Staphylococcus Aureus ◽  
Dynamic Model ◽  
Antimicrobial Effect ◽  
Aureus Strain ◽  
Combined Treatments ◽  
Antibacterial Effects ◽  
Multiple Dosing ◽  
Time Curve ◽  
Concentration Ratios

To explore whether susceptibility testing with antibiotic combinations at pharmacokinetically derived concentration ratios is predictive of the antimicrobial effect, a Staphylococcus aureus strain was exposed to daptomycin and gentamicin alone or in combination in multiple dosing experiments. The susceptibility of the S. aureus strain to daptomycin and gentamicin in combination was tested at concentration ratios equal to the ratios of 24 h areas under the concentration–time curve (AUC24s) of antibiotics simulated in an in vitro dynamic model in five-day treatments. The MICs of daptomycin and gentamicin decreased in the presence of each other; this led to an increase in the antibiotic AUC24/MIC ratios and the antibacterial effects. Effects of single and combined treatments were plotted against the AUC24/MIC ratios of daptomycin or gentamicin, and a significant sigmoid relationship was obtained. Similarly, when the effects of single and combined treatments were related to the total exposure of both drugs (the sum of AUC24/MIC ratios (∑AUC24/MIC)), a significant sigmoid relationship was obtained. These findings suggest that (1) the effects of antibiotic combinations can be predicted by AUC24/MICs using MICs of each antibacterial determined at pharmacokinetically derived concentration ratios; (2) ∑AUC24/MIC is a reliable predictor of the antibacterial effects of antibiotic combinations.

scholarly journals Pharmacodynamics of a Long-Acting Echinocandin, CD101, in a Neutropenic Invasive-Candidiasis Murine Model Using an Extended-Interval Dosing Design

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Alexander J. Lepak ◽  
Miao Zhao ◽  
Brian VanScoy ◽  
Paul G. Ambrose ◽  
David R. Andes
Keyword(s):  
Invasive Candidiasis ◽  
Half Life ◽  
Intraperitoneal Administration ◽  
Time Curve ◽  
Content Type ◽  
Elimination Half ◽  
Dosing Regimens ◽  
Dosing Strategies ◽  
Long Acting

ABSTRACT Echinocandins are important in the prevention and treatment of invasive candidiasis but limited by current dosing regimens that include daily intravenous administration. The novel echinocandin CD101 has a prolonged half-life of approximately 130 h in humans, making it possible to design once-weekly dosing strategies. The present study examined the pharmacodynamic activity of CD101 using the neutropenic invasive candidiasis mouse model against select Candida albicans (n = 4), C. glabrata (n = 3), and C. parapsilosis (n = 3) strains. The CD101 MIC ranged from 0.03 to 1 mg/liter. Plasma pharmacokinetic measurements were performed using uninfected mice after intraperitoneal administration of 1, 4, 16, and 64 mg/kg. The elimination half-life was prolonged at 28 to 41 h. Neutropenic mice were infected with each strain by lateral tail vein injection, treated with a single dose of CD101, and monitored for 7 days, at which time the organism burden was enumerated from the kidneys. Dose-dependent activity was observed for each organism. The pharmacokinetic/pharmacodynamic (PK/PD) index of the area under the concentration-time curve over 24 h in the steady state divided by the MIC (AUC/MIC index) correlated well with efficacy (R 2, 0.74 to 0.93). The median stasis 24-h free-drug AUC/MIC targets were as follows: for C. albicans, 2.92; for C. glabrata, 0.07; and for C. parapsilosis, 2.61. The PK/PD targets for 1-log10 kill endpoint were 2- to 4-fold higher. Interestingly, the aforementioned PK/PD targets of CD101 were numerically lower for all three species than those of other echinocandins. In summary, CD101 is a promising, novel echinocandin with advantageous pharmacokinetic properties and potent in vivo pharmacodynamic activity.

scholarly journals Activities of Tigecycline (GAR-936) against Legionella pneumophila In Vitro and in Guinea Pigs with L. pneumophila Pneumonia

2003 ◽  
Vol 47 (2) ◽  
pp. 533-540 ◽  
Author(s):  
Paul H. Edelstein ◽  
William J. Weiss ◽  
Martha A. C. Edelstein
Keyword(s):  
Guinea Pig ◽  
Legionella Pneumophila ◽  
Guinea Pigs ◽  
Time Curve ◽  
Once Daily ◽  
Susceptibility Data ◽  
Days Of Therapy ◽  
Dosing Regimens ◽  
Legionnaires Disease

ABSTRACT The activities of tigecycline (Wyeth Research) against extracellular and intracellular Legionella pneumophila and for the treatment of guinea pigs with L. pneumophila pneumonia were studied. The tigecycline MIC at which 50% of strains are inhibited for 101 different Legionella sp. strains was 4 μg/ml versus 0.125 and 0.25 μg/ml for azithromycin and erythromycin, respectively. Tigecycline was about as active as erythromycin (tested at 1 μg/ml) against the F889 strain of L. pneumophila grown in guinea pig alveolar macrophages and more active than erythromycin against the F2111 strain. Azithromycin (0.25 μg/ml) was more active than (F889) or as active as (F2111) tigecycline (1 μg/ml) in the macrophage model. When tigecycline was given (7.5 mg/kg of body weight subcutaneously once) to guinea pigs with L. pneumophila pneumonia, the mean peak serum and lung levels were 2.3 and 1.8 μg/ml (1.2 and 1.5 μg/g) at 1 and 2 h postinjection, respectively. The serum and lung areas under the concentration time curve from 0 to 24 h were 13.7 and 15.8 μg · h/ml, respectively. Thirteen of 16 guinea pigs with L. pneumophila pneumonia treated with tigecycline (7.5 mg/kg subcutaneously once daily for 5 days) survived for 7 days post-antimicrobial therapy, as did 11 of 12 guinea pigs treated with azithromycin (15 mg/kg intraperitoneally once daily for 2 days). None of 12 guinea pigs treated with saline survived. Tigecycline-treated guinea pigs had average end of therapy lung counts of 1 × 106 CFU/g (range, 2.5 × 104 to 3.2 × 106 CFU/g) versus <1 × 102 CFU/g for azithromycin (range, undetectable to 100 CFU/g). A second guinea pig study examined the ability of tigecycline to clear L. pneumophila from the lung after 5 to 9 days of therapy; bacterial concentrations 1 day posttherapy ranged from log10 4.2 to log10 5.5 CFU/g for four different dosing regimens. Tigecycline is about as effective as erythromycin against intracellular L. pneumophila, but tigecycline inactivation by the test media confounded the interpretation of susceptibility data. Tigecycline was effective at preventing death from pneumonia in an animal model of Legionnaires' disease, warranting human clinical trials of the drug for the disease.

Prediction of the Effects of Inoculum Size on the Antimicrobial Action of Trovafloxacin and Ciprofloxacin againstStaphylococcus aureus and Escherichia coli in an In Vitro Dynamic Model

1999 ◽  
Vol 43 (3) ◽  
pp. 498-502 ◽  
Author(s):  
Alexander A. Firsov ◽  
Sergey N. Vostrov ◽  
Olga V. Kononenko ◽  
Stephen H. Zinner ◽  
Yury A. Portnoy
Keyword(s):  
Escherichia Coli ◽  
Dynamic Models ◽  
Antimicrobial Effect ◽  
Inoculum Size ◽  
Antimicrobial Action ◽  
Time Curve ◽  
Mean Values ◽  
E Coli ◽  
Inoculum Effect

ABSTRACT The effect of inoculum size (N 0) on antimicrobial action has not been extensively studied in in vitro dynamic models. To investigate this effect and its predictability, killing and regrowth kinetics of Staphylococcus aureus andEscherichia coli exposed to monoexponentially decreasing concentrations of trovafloxacin (as a single dose) and ciprofloxacin (two doses at a 12-h interval) were compared atN 0 = 106 and 109 CFU/ml (S. aureus) and at N 0 = 106, 107, and 109 CFU/ml (E. coli). A series of pharmacokinetic profiles of trovafloxacin and ciprofloxacin with respective half-lives of 9.2 and 4 h were simulated at different ratios of area under the concentration-time curve (AUC) to MIC (in [micrograms × hours/milliliter]/[micrograms/milliliter]): 58 to 466 with trovafloxacin and 116 to 932 with ciprofloxacin for S. aureus and 58 to 233 and 116 to 466 for E. coli, respectively. Although the effect of N 0 was more pronounced for E. coli than for S. aureus, only a minor increase in minimum numbers of surviving bacteria and an almost negligible delay in their regrowth were associated with an increase of the N 0 for both organisms. TheN 0-induced reductions of the intensity of the antimicrobial effect (IE , area between control growth and the killing-regrowth curves) were also relatively small. However, the N 0 effect could not be eliminated either by simple shifting of the time-kill curves obtained at higherN 0s by the difference between the higher and lowest N 0 or by operating withIE s determined within theN 0-adopted upper limits of bacterial numbers (IE ′s). By using multivariate correlation and regression analyses, linear relationships betweenIE and log AUC/MIC and logN 0 related to the respective mean values [(log AUC/MIC)average and (logN 0)average] were established for both trovafloxacin and ciprofloxacin against each of the strains (r 2 = 0.97 to 0.99). The antimicrobial effect may be accurately predicted at a given AUC/MIC of trovafloxacin or ciprofloxacin and at a given N 0 based on the relationship IE = a + b [(log AUC/MIC)/(log AUC/MIC)average] − c [(logN 0)/(logN 0)average]. Moreover, the relative impacts of AUC/MIC and N 0 onIE may be evaluated. Since the c/bratios for trovafloxacin and ciprofloxacin against E. coliwere much lower (0.3 to 0.4) than that for ampicillin-sulbactam as examined previously (1.9), the inoculum effect with the quinolones may be much less pronounced than with the β-lactams. The described approach to the analysis of the inoculum effect in in vitro dynamic models might be useful in studies with other antibiotic classes.

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