Dong-Jin Kim1,2, Dong-Hwan Lee3, Sangzin Ahn1, Jinah Jung1,2, Sungmin Kiem4, So Won Kim5, Jae-Gook Shin1,2. 1. Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, 47392, Korea. 2. Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan, 47392, Korea. 3. Hallym Institute for Clinical Medicine, Hallym University Medical Center, Anyang, 14068, Korea. 4. Department of Infection, Inje University Haeundae Paik Hospital, Busan, 48108, Korea. 5. Department of Pharmacology, Catholic Kwandong University College of Medicine, Gangneung, 25601, Korea.
Abstract
WHAT IS KNOWN AND OBJECTIVE: Although patients may have received vancomycin therapy with therapeutic drug monitoring (TDM), those treated with high-strength and long-term vancomycin therapy might have unstable and time-varying renal function. The methods used to estimate renal function should not be considered interchangeable with pharmacokinetic (PK) modeling and model-based estimation of vancomycin pharmacokinetics. While Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) for renal function estimation has been widely integrated into clinical practice, a population PK model including CKD-EPI has not been established. The study was aimed at developing a new population PK model for optimal vancomycin prediction in patients with time-varying and variable renal function to evaluate the interchangeability of estimation methods. METHODS: The most suitable population PK model was explored and evaluated using non-linear mixed-effect modelling for the best fit of vancomycin concentrations from patients who needed to maintain high trough vancomycin concentrations of >10 mg/L or >15 mg/L. Renal function was estimated using the Cockcroft-Gault (CG), Modification of Diet in Renal Disease (MDRD) and CKD-EPI equations. NONMEM 7.4 was used to develop the population PK model. RESULTS: A total of 328 vancomycin concentrations in 99 patients were used to develop the population PK model. Vancomycin pharmacokinetics was best described by a two-compartment model. The CKD-EPI equation for vancomycin clearance was included in the final model among the estimation methods of renal function. A new covariate model, including extended covariate parameters that explain changes in renal function from the population-predicted value and individual dosing time, provided the best explanation for vancomycin pharmacokinetics among the various models tested. WHAT IS NEW AND CONCLUSION: A new extended covariate model for vancomycin using the CKD-EPI method may afford suitable dose adjustment for high-strength and long-term vancomycin therapy that results in unstable renal function.
WHAT IS KNOWN AND OBJECTIVE: Although patients may have received vancomycin therapy with therapeutic drug monitoring (TDM), those treated with high-strength and long-term vancomycin therapy might have unstable and time-varying renal function. The methods used to estimate renal function should not be considered interchangeable with pharmacokinetic (PK) modeling and model-based estimation of vancomycin pharmacokinetics. While Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) for renal function estimation has been widely integrated into clinical practice, a population PK model including CKD-EPI has not been established. The study was aimed at developing a new population PK model for optimal vancomycin prediction in patients with time-varying and variable renal function to evaluate the interchangeability of estimation methods. METHODS: The most suitable population PK model was explored and evaluated using non-linear mixed-effect modelling for the best fit of vancomycin concentrations from patients who needed to maintain high trough vancomycin concentrations of >10 mg/L or >15 mg/L. Renal function was estimated using the Cockcroft-Gault (CG), Modification of Diet in Renal Disease (MDRD) and CKD-EPI equations. NONMEM 7.4 was used to develop the population PK model. RESULTS: A total of 328 vancomycin concentrations in 99 patients were used to develop the population PK model. Vancomycin pharmacokinetics was best described by a two-compartment model. The CKD-EPI equation for vancomycin clearance was included in the final model among the estimation methods of renal function. A new covariate model, including extended covariate parameters that explain changes in renal function from the population-predicted value and individual dosing time, provided the best explanation for vancomycin pharmacokinetics among the various models tested. WHAT IS NEW AND CONCLUSION: A new extended covariate model for vancomycin using the CKD-EPI method may afford suitable dose adjustment for high-strength and long-term vancomycin therapy that results in unstable renal function.