Population Pharmacokinetic Modeling and Optimal Sampling Strategy for Bayesian Estimation of Amikacin Exposure in Critically Ill Septic Patients

Because the sepsis-induced pharmacokinetic (PK) modifications need to be considered in aminoglycoside dosing, the present study aimed to develop a population PK model for amikacin (AMK) in severe sepsis and to subsequently propose an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters. Concentration-time profiles for AMK were obtained from 88 critically ill septic patients during the first 24 hours of antibiotic treatment. The population PK model was developed using a nonlinear mixed effects modeling approach. Covariate analysis included demographic data, pathophysiological characteristics, and comedication. Optimal sampling times were selected based on a robust Bayesian design criterion. Taking into account clinical constraints, a two-point sampling approach was investigated. A two-compartment model with first-order elimination best fitted the AMK concentrations. Population PK estimates were 19.2 and 9.34 L for the central and peripheral volume of distribution and 4.31 and 2.21 L/h for the intercompartmental and total body clearance. Creatinine clearance estimated using the Cockcroft-Gault equation was retained in the final model. The two optimal sampling times were 1 hour and 6 hours after onset of the drug infusion. Predictive performance of individual Bayes estimates computed using the proposed optimal sampling strategy was reported: mean prediction errors were less than 5% and root mean square errors were less than 30%. The present study confirmed the significant influence of the creatinine clearance on the PK disposition of AMK during the first hours of treatment in critically ill septic patients. Based on the population estimates, an optimal sampling strategy suitable for Bayesian estimation of the drug PK parameters was developed, meeting the need of clinical practice.

[1]  E N Jonsson,et al.  Xpose--an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. , 1999, Computer methods and programs in biomedicine.

[2]  Lewis B. Sheiner,et al.  Some suggestions for measuring predictive performance , 1981, Journal of Pharmacokinetics and Biopharmaceutics.

[3]  M. Barclay,et al.  A suggested approach to once-daily aminoglycoside dosing. , 1995, British journal of clinical pharmacology.

[4]  E. Draper,et al.  APACHE II: A severity of disease classification system , 1985, Critical care medicine.

[5]  J. Vincent,et al.  Revisiting the loading dose of amikacin for patients with severe sepsis and septic shock , 2010, Critical care.

[6]  Andrew C. Hooker,et al.  Conditional Weighted Residuals (CWRES): A Model Diagnostic for the FOCE Method , 2007, Pharmaceutical Research.

[7]  Stephen Duffull,et al.  Some Considerations on the Design of Population Pharmacokinetic Studies , 2005, Journal of Pharmacokinetics and Pharmacodynamics.

[8]  M O Karlsson,et al.  Diagnosing Model Diagnostics , 2007, Clinical pharmacology and therapeutics.

[9]  M Tod,et al.  Implementation of OSPOP, an algorithm for the estimation of optimal sampling times in pharmacokinetics by the ED, EID and API criteria. , 1996, Computer methods and programs in biomedicine.

[10]  France Mentré,et al.  Bayesian design criteria: Computation, comparison, and application to a pharmacokinetic and a pharmacodynamic model , 1995, Journal of Pharmacokinetics and Biopharmaceutics.

[11]  M. Levy,et al.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference , 2003, Intensive care medicine.

[12]  E. Niclas Jonsson,et al.  Erratum to "PsN-Toolkit - A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM" [Comput. Methods Prog. Biomedicine 79 (2005) 241-257] , 2005, Comput. Methods Programs Biomed..

[13]  M. Foracchia,et al.  POPED, a software for optimal experiment design in population kinetics , 2004, Comput. Methods Programs Biomed..

[14]  H C Böttger,et al.  Use of Aminoglycosides in Critically Ill Patients: Individualization of Dosage Using Bayesian Statistics and Pharmacokinetic Principles , 1988, Therapeutic drug monitoring.

[15]  R. De Gaudio,et al.  Antibiotic pharmacokinetic and pharmacodynamic considerations in critical illness , 2004, Intensive Care Medicine.

[16]  M. Jolley.  Fluorescence polarization immunoassay for the determination of therapeutic drug levels in human plasma. , 1981, Journal of analytical toxicology.

[17]  Mitchell M. Levy,et al.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference , 2003, Intensive Care Medicine.

[18]  E. Ivers,et al.  Early Goal-Directed Therapy in the Treatment of Severe Sepsis and Septic Shock , 2001 .

[19]  J. Vincent,et al.  The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure , 1996, Intensive Care Medicine.

[20]  K. Ilett,et al.  Pharmacokinetics of Drugs Used in Critically Ill Adults , 1998, Clinical pharmacokinetics.

[21]  W. Buylaert,et al.  Pharmacokinetic and Pharmacodynamic Considerations When Treating Patients with Sepsis and Septic Shock , 2002, Clinical pharmacokinetics.

[22]  G. Castañeda-Hernández,et al.  Relationship between hemodynamic and vital support measures and pharmacokinetic variability of amikacin in critically ill patients with sepsis. , 1997, Critical care medicine.

[23]  M. Tod,et al.  Individualising Aminoglycoside Dosage Regimens after Therapeutic Drug Monitoring , 2001, Clinical pharmacokinetics.

[24]  J. M. Lanao,et al.  Influence of Clinical Diagnosis in the Population Pharmacokinetics of Amikacin in Intensive Care Unit Patients , 1998, Clinical drug investigation.

[25]  M. Barclay,et al.  Aminoglycoside toxicity and relation to dose regimen. , 1994, Adverse drug reactions and toxicological reviews.

[26]  France Mentré,et al.  Optimal Sampling Times for Bayesian Estimation of the Pharmacokinetic Parameters of Nortriptyline During Therapeutic Drug Monitoring , 1999, Journal of Pharmacokinetics and Biopharmaceutics.

[27]  David Roth,et al.  A simplified equation to predict glomerular filtration rate from serum creatinine , 2000 .

[28]  A. Domínguez-Gil,et al.  Pharmacokinetics of amikacin in intensive care unit patients , 1996, Journal of clinical pharmacy and therapeutics.

[29]  G. Castañeda-Hernández,et al.  Bayesian Approach to Control of Amikacin Serum Concentrations in Critically Ill Patients with Sepsis , 2000, The Annals of Pharmacotherapy.

[30]  P. Viale,et al.  Antimicrobial Therapy in Critically Ill Patients , 2005, Clinical pharmacokinetics.

[31]  P. Marik.  Aminoglycoside Volume of Distribution and Illness Severity in Critically Ill Septic Patients , 1993, Anaesthesia and intensive care.

[32]  G. Castañeda-Hernández,et al.  Amikacin Bayesian forecasting in critically ill patients with sepsis and cirrhosis. , 1997, Therapeutic drug monitoring.

[33]  E. Niclas Jonsson,et al.  PsN-Toolkit - A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM , 2005, Comput. Methods Programs Biomed..

[34]  E. Walter,et al.  Robust experiment design via stochastic approximation , 1985 .

[35]  J. Vincent,et al.  Serial evaluation of the SOFA score to predict outcome in critically ill patients. , 2001, JAMA.

[36]  J. Vincent,et al.  Empirical models for dosage optimization of four beta-lactams in critically ill septic patients based on therapeutic drug monitoring of amikacin. , 2010, Clinical biochemistry.

[37]  A. Bodenham,et al.  The Altered Pharmacokinetics and Pharmacodynamics of Drugs Commonly Used in Critically Ill Patients , 1988, Clinical pharmacokinetics.

[38]  Nicholas H. G. Holford,et al.  The Visual Predictive Check Superiority to Standard Diagnostic (Rorschach) Plots , 2005 .

[39]  M. H. Gault,et al.  Prediction of creatinine clearance from serum creatinine. , 1975, Nephron.

[40]  M. Barclay,et al.  Aminoglycosides--50 years on. , 1995, British journal of clinical pharmacology.

[41]  J. Dasta,et al.  Variability in aminoglycoside pharmacokinetics in critically ill surgical patients. , 1988, Critical care medicine.