Objectives: To develop a pharmacokinetic model describing total and unbound teicoplanin concentrations in patients with haematological malignancy and to perform Monte Carlo simulations to evaluate target attainment of unbound trough concentrations with various dose regimens. Methods: This was a hospital-based clinical trial (EudraCT 2013-004535-72). The dosing regimen was 600/800 mg q12h for three doses then 600/800 mg daily. Serial total and unbound teicoplanin concentrations were collected. Maximum protein binding was estimated from serum albumin concentration. Population pharmacokinetic analyses and Monte Carlo simulations were conducted using Pmetrics®. Target total and unbound trough concentrations were ≥20 and ≥1.5 mg/L, respectively. Results: Thirty adult patients were recruited with a mean (SD) bodyweight of 69.1 (15.8) kg, a mean (SD) CLCR of 72 (41) mL/min and a median (IQR) serum albumin concentration of 29 (4) g/L. A three-compartment complex binding pharmacokinetic model best described the concentration-time data. Total and unbound teicoplanin concentrations were related by serum albumin concentration and a dissociation constant. CLCR and bodyweight were supported as covariates for CL and volume of the central compartment, respectively. Dosing simulations showed that high CLCR was associated with reduced probability of achieving target total and unbound trough concentrations. Low serum albumin concentration was associated with a reduced probability of attaining target total but not unbound trough concentrations. A method to estimate the unbound teicoplanin concentration from the measured total concentration at different serum albumin concentration was demonstrated. Conclusions: Standard teicoplanin dosing regimens should be used with caution in patients with haematological malignancy. Bodyweight, CLCR and serum albumin concentration are important considerations for appropriate dosing.
Objectives: To develop a pharmacokinetic model describing total and unbound teicoplanin concentrations in patients with haematological malignancy and to perform Monte Carlo simulations to evaluate target attainment of unbound trough concentrations with various dose regimens. Methods: This was a hospital-based clinical trial (EudraCT 2013-004535-72). The dosing regimen was 600/800 mg q12h for three doses then 600/800 mg daily. Serial total and unbound teicoplanin concentrations were collected. Maximum protein binding was estimated from serum albumin concentration. Population pharmacokinetic analyses and Monte Carlo simulations were conducted using Pmetrics®. Target total and unbound trough concentrations were ≥20 and ≥1.5 mg/L, respectively. Results: Thirty adult patients were recruited with a mean (SD) bodyweight of 69.1 (15.8) kg, a mean (SD) CLCR of 72 (41) mL/min and a median (IQR) serum albumin concentration of 29 (4) g/L. A three-compartment complex binding pharmacokinetic model best described the concentration-time data. Total and unbound teicoplanin concentrations were related by serum albumin concentration and a dissociation constant. CLCR and bodyweight were supported as covariates for CL and volume of the central compartment, respectively. Dosing simulations showed that high CLCR was associated with reduced probability of achieving target total and unbound trough concentrations. Low serum albumin concentration was associated with a reduced probability of attaining target total but not unbound trough concentrations. A method to estimate the unbound teicoplanin concentration from the measured total concentration at different serum albumin concentration was demonstrated. Conclusions: Standard teicoplanin dosing regimens should be used with caution in patients with haematological malignancy. Bodyweight, CLCR and serum albumin concentration are important considerations for appropriate dosing.
Authors: Rochelle L Ryan; Dwane Jackson; George Hopkins; Victoria Eley; Rebecca Christensen; Andre A J Van Zundert; Steven C Wallis; Jeffrey Lipman; Suzanne L Parker; Jason A Roberts Journal: Antimicrob Agents Chemother Date: 2022-06-28 Impact factor: 5.938
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Authors: Vesa Cheng; Mohd H Abdul-Aziz; Fay Burrows; Hergen Buscher; Young-Jae Cho; Amanda Corley; Eileen Gilder; Hyung-Sook Kim; Sung Yoon Lim; Shay McGuinness; Rachael Parke; Claire Reynolds; Sam Rudham; Steven C Wallis; Susan A Welch; John F Fraser; Kiran Shekar; Jason A Roberts Journal: Clin Pharmacokinet Date: 2022-03-06 Impact factor: 5.577
Authors: Astrid Broeker; Matthias G Vossen; Florian Thalhammer; Steven C Wallis; Jeffrey Lipman; Jason A Roberts; Sebastian G Wicha Journal: Pharm Res Date: 2020-05-14 Impact factor: 4.200
Authors: Joon Sik Choi; Jong Min Kim; Dongsub Kim; Si Ho Kim; Heeyeon Cho; Hyung Doo Park; Soo Youn Lee; Cheol In Kang; Yae Jean Kim Journal: J Korean Med Sci Date: 2020-11-30 Impact factor: 2.153