Pieter J Colin1,2, Karel Allegaert3,4,5, Alison H Thomson6, Daan J Touw7,8, Michael Dolton9, Matthijs de Hoog10, Jason A Roberts11, Eyob D Adane12, Masato Yamamoto13, Dolores Santos-Buelga14, Ana Martín-Suarez14, Nicolas Simon15, Fabio S Taccone16, Yoke-Lin Lo17,18, Emilia Barcia19, Michel M R F Struys20,21, Douglas J Eleveld20. 1. Department of Anesthesiology, University Medical Center Groningen, University of Groningen, P.O. Box 30001, 9700 RB, Groningen, The Netherlands. p.j.colin@umcg.nl. 2. Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium. p.j.colin@umcg.nl. 3. Pediatric Intensive Care, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands. 4. Department of Neonatology, Erasmus MC, Sophia Children's Hospital, Rotterdam, The Netherlands. 5. Department of Development and Regeneration, KU Leuven, Louvain, Belgium. 6. Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK. 7. Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. 8. Department of Pharmacy, Section Pharmacokinetics, Toxicology and Targeting, University of Groningen, Groningen, The Netherlands. 9. Faculty of Pharmacy, University of Sydney, Sydney, NSW, Australia. 10. Department of Pediatrics, Erasmus University and University Hospital Rotterdam/Sophia Children's Hospital, Rotterdam, The Netherlands. 11. University of Queensland Centre for Clinical Research and School of Pharmacy, The University of Queensland, Brisbane, QLD, Australia. 12. Raabe College of Pharmacy, Ohio Northern University, Ada, OH, USA. 13. Department of Neuropsychopharmacology and Hospital Pharmacy, Nagoya University Graduate School of Medicine, Nagoya, Japan. 14. Department of Pharmacy and Pharmaceutical Technology, University of Salamanca, Salamanca, Spain. 15. Aix-Marseille University, INSERM, IRD, SESSTIM, Hop Sainte Marguerite, Service de Pharmacologie Clinique, CAP, Marseille, France. 16. Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium. 17. Department of Pharmacy, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. 18. Department of Pharmacy Practice, School of Pharmacy, International Medical University, Kuala Lumpur, Malaysia. 19. Department of Pharmaceutics and Food Technology, School of Pharmacy, Universidad Complutense de Madrid, Madrid, Spain. 20. Department of Anesthesiology, University Medical Center Groningen, University of Groningen, P.O. Box 30001, 9700 RB, Groningen, The Netherlands. 21. Department of Anesthesia and Peri-operative Medicine, Ghent University, Ghent, Belgium.
Abstract
BACKGROUND AND OBJECTIVES: Uncertainty exists regarding the optimal dosing regimen for vancomycin in different patient populations, leading to a plethora of subgroup-specific pharmacokinetic models and derived dosing regimens. We aimed to investigate whether a single model for vancomycin could be developed based on a broad dataset covering the extremes of patient characteristics. Furthermore, as a benchmark for current dosing recommendations, we evaluated and optimised the expected vancomycin exposure throughout life and for specific patient subgroups. METHODS: A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 different studies in different patient populations. Steady-state exposure was simulated and compared across patient subgroups for two US Food and Drug Administration/European Medicines Agency-approved drug labels and optimised doses were derived. RESULTS: The final model uses postmenstrual age, weight and serum creatinine as covariates. A 35-year-old, 70-kg patient with a serum creatinine level of 0.83 mg dL-1 (73.4 µmol L-1) has a V1, V2, CL and Q2 of 42.9 L, 41.7 L, 4.10 L h-1 and 3.22 L h-1. Clearance matures with age, reaching 50% of the maximal value (5.31 L h-1 70 kg-1) at 46.4 weeks postmenstrual age then declines with age to 50% at 61.6 years. Current dosing guidelines failed to achieve satisfactory steady-state exposure across patient subgroups. After optimisation, increased doses for the Food and Drug Administration label achieve consistent target attainment with minimal (± 20%) risk of under- and over-dosing across patient subgroups. CONCLUSIONS: A population model was developed that is useful for further development of age and kidney function-stratified dosing regimens of vancomycin and for individualisation of treatment through therapeutic drug monitoring and Bayesian forecasting.
BACKGROUND AND OBJECTIVES: Uncertainty exists regarding the optimal dosing regimen for vancomycin in different patient populations, leading to a plethora of subgroup-specific pharmacokinetic models and derived dosing regimens. We aimed to investigate whether a single model for vancomycin could be developed based on a broad dataset covering the extremes of patient characteristics. Furthermore, as a benchmark for current dosing recommendations, we evaluated and optimised the expected vancomycin exposure throughout life and for specific patient subgroups. METHODS: A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 different studies in different patient populations. Steady-state exposure was simulated and compared across patient subgroups for two US Food and Drug Administration/European Medicines Agency-approved drug labels and optimised doses were derived. RESULTS: The final model uses postmenstrual age, weight and serum creatinine as covariates. A 35-year-old, 70-kg patient with a serum creatinine level of 0.83 mg dL-1 (73.4 µmol L-1) has a V1, V2, CL and Q2 of 42.9 L, 41.7 L, 4.10 L h-1 and 3.22 L h-1. Clearance matures with age, reaching 50% of the maximal value (5.31 L h-1 70 kg-1) at 46.4 weeks postmenstrual age then declines with age to 50% at 61.6 years. Current dosing guidelines failed to achieve satisfactory steady-state exposure across patient subgroups. After optimisation, increased doses for the Food and Drug Administration label achieve consistent target attainment with minimal (± 20%) risk of under- and over-dosing across patient subgroups. CONCLUSIONS: A population model was developed that is useful for further development of age and kidney function-stratified dosing regimens of vancomycin and for individualisation of treatment through therapeutic drug monitoring and Bayesian forecasting.
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