Inter- and intraquinolone predictors of antimicrobial effect in an in vitro dynamic model: new insight into a widely used concept.
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 (microg x h/ml)/(microg/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 (Teff). Specific and nonsuperimposed IE versus log AUC/MIC or log AUCeff relationships were inherent in each of the treatments: TRO given q.d. (r2 = 0.97 and 0.96), CIP given q.d. (r2 = 0.98 and 0.96), and CIP given b.i.d. (r2 = 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-Teff relationships plotted for the different quinolones and dosing regimens were nonspecific and virtually superimposed (r2 = 0.95). Hence, AUC/MIC, AUCeff and Teff were equally good predictors of the AME of each of the quinolones and each dosing regimen taken separately, whereas Teff 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 Teff 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 (Teff). Teff may be able to accurately predict the AME of one quinolone on the basis of the data obtained for another quinolone.
Firsov
A A
AA
Department of Pharmacokinetics, Centre of Science & Technology LekBioTech, Moscow, Russia. biotec@glas.apc.org
Shevchenko
A A
AA
Vostrov
S N
SN
Zinner
S H
SH
D000890:Anti-Infective Agents / Q000493:pharmacokinetics*; D019540:Area Under Curve; D002939:Ciprofloxacin / Q000493:pharmacokinetics*; D015169:Colony Count, Microbial; D004926:Escherichia coli / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism*; D024841:Fluoroquinolones; D007711:Klebsiella pneumoniae / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism*; D008826:Microbial Sensitivity Tests; D009287:Naphthyridines / Q000493:pharmacokinetics*; D011550:Pseudomonas aeruginosa / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism*; D013997:Time Factors
D000890:Anti-Infective Agents; D024841:Fluoroquinolones; D009287:Naphthyridines; D002939:Ciprofloxacin; C080163:trovafloxacin