Muhammad Usman1,2, Otto R Frey3, Georg Hempel4. 1. Department of Pharmaceutical and Medicinal Chemistry - Clinical Pharmacy, University of Muenster, Corrensstr. 48, 48149, Muenster, Germany. 2. Institute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences, Lahore, Pakistan. 3. Department of Pharmacy, Hospital of Heidenheim, Heidenheim, Germany. 4. Department of Pharmaceutical and Medicinal Chemistry - Clinical Pharmacy, University of Muenster, Corrensstr. 48, 48149, Muenster, Germany. georg.hempel@uni-muenster.de.
Abstract
OBJECTIVES: The aim of this study was to evaluate different dosage regimens of meropenem in elderly patients in relation with renal function using a population pharmacokinetic (popPK) model. METHODS: The data of 178 elderly patients treated with meropenem was collected from different sources. A popPK model was developed by using NONMEM® and the influence of different covariates on meropenem CL and V1 was observed. Monte Carlo dosing simulations were performed at steady state to observe the % T > MIC for targets of 40, 60 and 80% of dosage intervals at different levels of creatinine clearance (CLCR). RESULTS: The data was described by a two-compartment model and the values of parameter estimates for CL, V1, Q and V2 were 5.27 L/h, 17.2 L, 9.92 L/h and 10.6 L, respectively. The CLCR, body weight and centre had a significant influence on meropenem CL while no direct influence of age was observed. Extended infusions had pharmacokinetic and pharmacodynamic (PK/PD) breakpoint one dilution greater than corresponding short infusion regimens for each target of % T > MIC. CONCLUSION: Meropenem CL was significantly lower in the elderly compared to CL reported in younger patients due to the reduced renal function. An extended infusion of 1000 mg q8h can be considered for empirical treatment of infections in elderly patients when CLCR is ≤ 50 mL/min. A continuous infusion of 3000 mg daily dose is preferred if CLCR > 50 mL/min. However, a higher daily dose of meropenem would be required for resistant strains (MIC >8 mg/L) of bacteria if CLCR is >100 mL/min.
OBJECTIVES: The aim of this study was to evaluate different dosage regimens of meropenem in elderly patients in relation with renal function using a population pharmacokinetic (popPK) model. METHODS: The data of 178 elderly patients treated with meropenem was collected from different sources. A popPK model was developed by using NONMEM® and the influence of different covariates on meropenem CL and V1 was observed. Monte Carlo dosing simulations were performed at steady state to observe the % T > MIC for targets of 40, 60 and 80% of dosage intervals at different levels of creatinine clearance (CLCR). RESULTS: The data was described by a two-compartment model and the values of parameter estimates for CL, V1, Q and V2 were 5.27 L/h, 17.2 L, 9.92 L/h and 10.6 L, respectively. The CLCR, body weight and centre had a significant influence on meropenem CL while no direct influence of age was observed. Extended infusions had pharmacokinetic and pharmacodynamic (PK/PD) breakpoint one dilution greater than corresponding short infusion regimens for each target of % T > MIC. CONCLUSION:Meropenem CL was significantly lower in the elderly compared to CL reported in younger patients due to the reduced renal function. An extended infusion of 1000 mg q8h can be considered for empirical treatment of infections in elderly patients when CLCR is ≤ 50 mL/min. A continuous infusion of 3000 mg daily dose is preferred if CLCR > 50 mL/min. However, a higher daily dose of meropenem would be required for resistant strains (MIC >8 mg/L) of bacteria if CLCR is >100 mL/min.
Entities:
Keywords:
Elderly; Meropenem; NONMEM®; Population pharmacokinetics; Simulations
Authors: Ron J Keizer; Michel van Benten; Jos H Beijnen; Jan H M Schellens; Alwin D R Huitema Journal: Comput Methods Programs Biomed Date: 2010-06-02 Impact factor: 5.428
Authors: Andrew A Udy; Julie M Varghese; Mahdi Altukroni; Scott Briscoe; Brett C McWhinney; Jacobus P Ungerer; Jeffrey Lipman; Jason A Roberts Journal: Chest Date: 2012-07 Impact factor: 9.410
Authors: Wolfgang A Krueger; Jurgen Bulitta; Martina Kinzig-Schippers; Cornelia Landersdorfer; Ulrike Holzgrabe; Kurt G Naber; George L Drusano; Fritz Sörgel Journal: Antimicrob Agents Chemother Date: 2005-05 Impact factor: 5.191
Authors: Martin G Kees; Iris K Minichmayr; Stefan Moritz; Stefanie Beck; Sebastian G Wicha; Frieder Kees; Charlotte Kloft; Thomas Steinke Journal: J Clin Pharmacol Date: 2015-09-18 Impact factor: 3.126
Authors: Arantxazu Isla; Alicia Rodríguez-Gascón; Iñaki F Trocóniz; Lorea Bueno; María Angeles Solinís; Javier Maynar; José Angel Sánchez-Izquierdo; José Luis Pedraz Journal: Clin Pharmacokinet Date: 2008 Impact factor: 6.447
Authors: Kiran Shekar; John F Fraser; Fabio Silvio Taccone; Susan Welch; Steven C Wallis; Daniel V Mullany; Jeffrey Lipman; Jason A Roberts Journal: Crit Care Date: 2014-12-12 Impact factor: 9.097
Authors: Dagan O Lonsdale; Emma H Baker; Karin Kipper; Charlotte Barker; Barbara Philips; Andrew Rhodes; Mike Sharland; Joseph F Standing Journal: Br J Clin Pharmacol Date: 2018-11-26 Impact factor: 4.335
Authors: J W C Alffenaar; S L Stocker; L Davies Forsman; A Garcia-Prats; S K Heysell; R E Aarnoutse; O W Akkerman; A Aleksa; R van Altena; W Arrazola de Oñata; P K Bhavani; N Van't Boveneind-Vrubleuskaya; A C C Carvalho; R Centis; J M Chakaya; D M Cirillo; J G Cho; L D Ambrosio; M P Dalcolmo; P Denti; K Dheda; G J Fox; A C Hesseling; H Y Kim; C U Köser; B J Marais; I Margineanu; A G Märtson; M Munoz Torrico; H M Nataprawira; C W M Ong; R Otto-Knapp; C A Peloquin; D R Silva; R Ruslami; P Santoso; R M Savic; R Singla; E M Svensson; A Skrahina; D van Soolingen; S Srivastava; M Tadolini; S Tiberi; T A Thomas; Z F Udwadia; D H Vu; W Zhang; S G Mpagama; T Schön; G B Migliori Journal: Int J Tuberc Lung Dis Date: 2022-06-01 Impact factor: 3.427