Summary
The concept of accelerating bacterial eradication and accomplishing a more rapid clinical cure by optimising dosing of antimicrobial agents is coming to fruition after many years of research. By integrating the pharmacokinetic parameters of an antibiotic with measures of microorganism susceptibility such as the minimum inhibitory concentration (MIC), it is possible to optimise both clinical and bacteriological cure. Recently, area under the inhibitory curve (AUIC) has been introduced as the 24-hour area under the curve (AUC) divided by the MIC. The AUIC has been shown to be an effective parameter to predict infectious outcome and it has the advantage that it can be easily calculated by estimating the patient’s creatinine clearance and using population clearance of drugs vs creatinine clearance equations. In this review, total clearance vs creatinine clearance equations were derived for 53 antimicrobials, using pharmacokinetic data extracted from the literature. These equations were then validated by calculating half-life and AUC (for specific doses) and comparing the results to published values and ranges. In the validation phases the percentage error for each antibiotic equation was variable, ranging from 0.5 to 61% when estimating half-life, and 0.35 to 51% when estimating AUC. When a subset of antimicrobials was validated against values derived from studies of AUC vs decreasing creatinine clearance, the majority of percentage errors were within 0.35 to 56%, with only a minimal number of outliers over the studied ranges of renal function (0–129 ml/min/70kg). Possible explanations for these outliers include multiple routes of elimination and research based on populations different to those used to derive the original equation. Percentage errors were within acceptable ranges, when considering that most antimicrobials have a large therapeutic/toxic ratio. By targeting an AUIC value of 350, well above the theoretical threshold therapeutic value of 125, doses associated with an accelerated bacterial eradication rate are possible without substantially overdosing the patient. This remains true even if the calculated values from these equations are greater than a 50% overestimation.
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Amsden, G.W., Ballow, C.H. & Schentag, J.J. Population Pharmacokinetic Methods to Optimise Antibiotic Effects. Drug Invest. 5, 256–268 (1993). https://doi.org/10.1007/BF03259590
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DOI: https://doi.org/10.1007/BF03259590