title: Aminoglycoside nephrotoxicity: modeling, simulation, and control.
abstract: The main constraints on the administration of aminoglycosides are the risks of nephrotoxicity and ototoxicity, which can lead to acute, renal, vestibular, and auditory toxicities. In the present study we focused on nephrotoxicity. No reliable predictor of nephrotoxicity has been found to date. We have developed a deterministic model which describes the pharmacokinetic behavior of aminoglycosides (with a two-compartment model), the kinetics of aminoglycoside accumulation in the renal cortex, the effects of aminoglycosides on renal cells, the resulting effects on renal function by tubuloglomerular feedback, and the resulting effects on serum creatinine concentrations. The pharmacokinetic parameter values were estimated by use of the NPEM program. The estimated pharmacodynamic parameter values were obtained after minimization of the least-squares objective function between the measured and the calculated serum creatinine concentrations. A simulation program assessed the influences of the dosage regimens on the occurrence of nephrotoxicity. We have also demonstrated the relevancy of modeling of the circadian rhythm of the renal function. We have shown the ability of the model to fit with 49 observed serum creatinine concentrations for a group of eight patients treated for endocarditis by comparison with 49 calculated serum creatinine concentrations (r(2) = 0.988; P < 0.001). We have found that for the same daily dose, the nephrotoxicity observed with a thrice-daily administration schedule appears more rapidly, induces a greater decrease in renal function, and is more prolonged than those that occur with less frequent administration schedules (for example, once-daily administration). Moreover, for once-daily administration, we have demonstrated that the time of day of administration can influence the incidence of aminoglycoside nephrotoxicity. The lowest level of nephrotoxicity was observed when aminoglycosides were administered at 1:30 p.m. Clinical application of this model might make it possible to adjust aminoglycoside dosage regimens by taking into account both the efficacies and toxicities of the drugs.
authors.affiliation: UMR CNRS 5558-ADCAPT, Service Pharmaceutique, Hôpital Antoine Charial, Hospices Civils de Lyon, Francheville, France.
authors.forename: Florent
authors.initials: F
authors.lastname: Rougier
authors.forename: Daniel
authors.initials: D
authors.lastname: Claude
authors.forename: Michel
authors.initials: M
authors.lastname: Maurin
authors.forename: Alexandre
authors.initials: A
authors.lastname: Sedoglavic
authors.forename: Michel
authors.initials: M
authors.lastname: Ducher
authors.forename: Stéphane
authors.initials: S
authors.lastname: Corvaisier
authors.forename: Roger
authors.initials: R
authors.lastname: Jelliffe
authors.forename: Pascal
authors.initials: P
authors.lastname: Maire
mesh_terms: D000328:Adult; D000465:Algorithms; D000583:Amikacin / Q000009:adverse effects / Q000493:pharmacokinetics; D000900:Anti-Bacterial Agents / Q000009:adverse effects* / Q000493:pharmacokinetics; D019540:Area Under Curve; D002940:Circadian Rhythm / Q000502:physiology; D003198:Computer Simulation; D003404:Creatinine / Q000378:metabolism; D005260:Female; D006801:Humans; D007672:Kidney Cortex / Q000378:metabolism; D007674:Kidney Diseases / Q000139:chemically induced* / Q000473:pathology; D007677:Kidney Function Tests; D008297:Male; D008954:Models, Biological; D014640:Vancomycin / Q000009:adverse effects / Q000493:pharmacokinetics
chemical_list: D000900:Anti-Bacterial Agents; D014640:Vancomycin; D000583:Amikacin; D003404:Creatinine