PubMed1997
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.