Application of Bayesian estimation for the prediction of an appropriate dosage regimen of amikacin.
A Bayesian approach was developed to determine an amikacin dosage regimen to achieve the desired plasma concentrations for each patient. Statistical characteristics of pharmacokinetic parameters were first evaluated in a group of patients (reference population), which when combined with three individual plasma concentrations of drug led to a Bayesian estimation of individual pharmacokinetic parameters. By using these parameters, an individual dosage regimen was then established to avoid residual and peak amikacin concentrations of up to 3 and 25 micrograms/mL, respectively. In a test group of 33 patients, adapted amikacin dosage regimens ranged from 4 to 43 mg/kg/d, with schedules requiring up to four infusions per day. Infusion time varied from 40 min to 4 h. These differences in drug administration protocol result from the wide interindividual variability of amikacin pharmacokinetic parameters. Performance of the developed methodology was evaluated by computing bias and precision of the estimated total body clearance and of the trough and peak amikacin concentrations that were reached after dosage regimen determinations.