Variants of the available methods for estimating antimicrobial effect kinetics in an in vitro dynamic model were analyzed. Two integral parameters characterizing antimicrobial effect duration (TE) and intensity (IE) are suggested to define and analyze the concentration-effect relationships in these models, irrespective of the method of recording. TE is defined by the time from the moment of antibiotic administration to the moment when the bacterial count again reaches its initial level. IE is defined by the area between the microbial growth curves in the presence and absence of an antibiotic. TE and IE were used to quantify the antimicrobial effects of sisomicin on Pseudomonas aeruginosa 58, Escherichia coli 93, and Klebsiella pneumoniae 5056, simulating the pharmacokinetic profiles of the drugs observed following intramuscular administration in therapeutic doses, including the variability of aminoglycoside concentrations in human blood.The development of dynamic models that allow the simulation of antibiotic pharmacokinetic profiles for the study of the kinetics of antimicrobial effect (AME) has provided a means for evaluating the role of the pharmacokinetic factor in the development of AME (5,8,10) and has stimulated the in vitro assessment of the relative effectiveness of various antibiotics and dosage regimens. However, despite strictly controlled conditions for experiments with dynamic models, conclusions about the preference of one drug or dosage regimen over another are essentially qualitative and not always unequivocal. This results to a considerable degree from deficiencies in the available methods for quantifying AME.The analysis of AME kinetics or, strictly speaking, the kinetics of microbial growth in the presence of an antibiotic traditionally employs models that describe the initial phase of cell growth inhibition under the action of the drug and compare microbial growth rates in the presence and absence of the antibiotic.It has been proposed that four parameters be evaluated to characterize more completely the quantitative change in microbial counts in the presence of an antibiotic. These include the time required for microbial count to be reduced by 99% (Tgg), the time required to reach the minimum count (Tmin), the minimum bacterial cell concentration (Bmin), and the time required for a subsequent 10-fold (1-log) increase in bacterial count (tulg) (19). Unfortunately, the last three parameters can be estimated only by counting CFU after samples are grown on solid nutrient media or with the microcalorimetric technique for Tgg (4). Since the high sensitivity of colony counts is "compensated" for by its insufficient accuracy, the estimates for the parameters Tgg, tjug, and especially Tmin may be only approximate. Moreover, the use of multiple parameters often does not allow the definitive assessment of AME, because of conflicting values of Tg, Bmin, and tjg. A comprehensive analysis of these and other AME parameters is presented elsewhere (8).In view of the above-mentioned considerations, we hav...

The general principles of in-vitro simulation of drug pharmacokinetic profiles for linear one-, two- and multi-compartment models are described. An in-vitro dynamic model constructed on the basis of these, incorporating a novel filtration unit to provide efficient filtration of drugs at constant inoculum size, was used to study the antimicrobial action of sisomicin on Escherichia coli A 20363, in conditions simulating the pharmacokinetic profile observed in humans after a single intramuscular dose of 1 mg/kg.

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