Phillip J Bergen1, Jürgen B Bulitta2, Carl M J Kirkpatrick1, Kate E Rogers3, Megan J McGregor1, Steven C Wallis4, David L Paterson5, Jeffrey Lipman6, Jason A Roberts7, Cornelia B Landersdorfer8. 1. Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia. 2. Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, USA. 3. Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia. 4. Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane, Queensland, Australia. 5. The University of Queensland Center for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia. 6. Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane, Queensland, Australia Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia. 7. Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane, Queensland, Australia Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia. 8. Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA cornelia.landersdorfer@monash.edu.
Abstract
BACKGROUND: Pathophysiological changes in critically ill patients can cause severely altered pharmacokinetics and widely varying antibiotic exposures. The impact of altered pharmacokinetics on bacterial killing and resistance has not been characterized in the dynamic hollow-fibre in vitro infection model (HFIM). METHODS: A clinical Pseudomonas aeruginosa isolate (piperacillin MIC 4 mg/L) was studied in the HFIM (inoculum ∼10(7) cfu/mL). Pharmacokinetic profiles of three piperacillin dosing regimens (4 g 8-, 6- and 4-hourly, 30 min intravenous infusion) as observed in critically ill patients with augmented renal clearance (ARC), normal renal function or impaired renal function (creatinine clearances of 250, 110 or 30 mL/min, respectively) were simulated over 7 days. The time courses of total and less-susceptible populations and MICs were determined. Mechanism-based modelling was performed in S-ADAPT. RESULTS: For all regimens with ARC and regimens with 8- or 6-hourly dosing with normal renal function, initial killing of ≤∼2 log10 was followed by regrowth to 10(8)-10(9) cfu/mL at 48 h. For 8- and 6-hourly dosing at normal renal function, the proportion of less-susceptible colonies increased ∼10-100-fold above those in ARC and control arms. Regimens achieving an fCmin of ≥5× MIC resulted in bacterial killing of 3-4 log10 without regrowth and suppressed less-susceptible populations to ≤∼2 log10. The mechanism-based model successfully quantified the time course of bacterial growth, killing and regrowth. CONCLUSIONS: Only high piperacillin concentrations prevented regrowth of P. aeruginosa. Individualized dosing regimens that account for altered pharmacokinetics and aim for higher-than-standard antibiotic exposures to achieve an fCmin of ≥5× MIC were required to maximize bacterial killing and suppress emergence of resistance.
BACKGROUND: Pathophysiological changes in critically illpatients can cause severely altered pharmacokinetics and widely varying antibiotic exposures. The impact of altered pharmacokinetics on bacterial killing and resistance has not been characterized in the dynamic hollow-fibre in vitro infection model (HFIM). METHODS: A clinical Pseudomonas aeruginosa isolate (piperacillin MIC 4 mg/L) was studied in the HFIM (inoculum ∼10(7) cfu/mL). Pharmacokinetic profiles of three piperacillin dosing regimens (4 g 8-, 6- and 4-hourly, 30 min intravenous infusion) as observed in critically illpatients with augmented renal clearance (ARC), normal renal function or impaired renal function (creatinine clearances of 250, 110 or 30 mL/min, respectively) were simulated over 7 days. The time courses of total and less-susceptible populations and MICs were determined. Mechanism-based modelling was performed in S-ADAPT. RESULTS: For all regimens with ARC and regimens with 8- or 6-hourly dosing with normal renal function, initial killing of ≤∼2 log10 was followed by regrowth to 10(8)-10(9) cfu/mL at 48 h. For 8- and 6-hourly dosing at normal renal function, the proportion of less-susceptible colonies increased ∼10-100-fold above those in ARC and control arms. Regimens achieving an fCmin of ≥5× MIC resulted in bacterial killing of 3-4 log10 without regrowth and suppressed less-susceptible populations to ≤∼2 log10. The mechanism-based model successfully quantified the time course of bacterial growth, killing and regrowth. CONCLUSIONS: Only high piperacillin concentrations prevented regrowth of P. aeruginosa. Individualized dosing regimens that account for altered pharmacokinetics and aim for higher-than-standard antibiotic exposures to achieve an fCmin of ≥5× MIC were required to maximize bacterial killing and suppress emergence of resistance.
Authors: Sofie Dhaese; Aaron Heffernan; David Liu; Mohd Hafiz Abdul-Aziz; Veronique Stove; Vincent H Tam; Jeffrey Lipman; Jason A Roberts; Jan J De Waele Journal: Clin Pharmacokinet Date: 2020-10 Impact factor: 6.447
Authors: T Tängdén; V Ramos Martín; T W Felton; E I Nielsen; S Marchand; R J Brüggemann; J B Bulitta; M Bassetti; U Theuretzbacher; B T Tsuji; D W Wareham; L E Friberg; J J De Waele; V H Tam; Jason A Roberts Journal: Intensive Care Med Date: 2017-04-13 Impact factor: 17.440
Authors: Phillip J Bergen; Jürgen B Bulitta; Carl M J Kirkpatrick; Kate E Rogers; Megan J McGregor; Steven C Wallis; David L Paterson; Roger L Nation; Jeffrey Lipman; Jason A Roberts; Cornelia B Landersdorfer Journal: Antimicrob Agents Chemother Date: 2017-04-24 Impact factor: 5.191
Authors: Cornelia B Landersdorfer; Vanessa E Rees; Rajbharan Yadav; Kate E Rogers; Tae Hwan Kim; Phillip J Bergen; Soon-Ee Cheah; John D Boyce; Anton Y Peleg; Antonio Oliver; Beom Soo Shin; Roger L Nation; Jürgen B Bulitta Journal: Antimicrob Agents Chemother Date: 2018-03-27 Impact factor: 5.191
Authors: Rajbharan Yadav; Phillip J Bergen; Kate E Rogers; Carl M J Kirkpatrick; Steven C Wallis; Yuling Huang; Jürgen B Bulitta; David L Paterson; Jeffrey Lipman; Roger L Nation; Jason A Roberts; Cornelia B Landersdorfer Journal: Antimicrob Agents Chemother Date: 2019-12-20 Impact factor: 5.191
Authors: Rajbharan Yadav; Kate E Rogers; Phillip J Bergen; Jürgen B Bulitta; Carl M J Kirkpatrick; Steven C Wallis; David L Paterson; Roger L Nation; Jeffrey Lipman; Jason A Roberts; Cornelia B Landersdorfer Journal: Antimicrob Agents Chemother Date: 2018-04-26 Impact factor: 5.191
Authors: Anders Perner; Anthony C Gordon; Daniel De Backer; George Dimopoulos; James A Russell; Jeffrey Lipman; Jens-Ulrik Jensen; John Myburgh; Mervyn Singer; Rinaldo Bellomo; Timothy Walsh Journal: Intensive Care Med Date: 2016-10-01 Impact factor: 17.440