ABSTRACT
Purpose
Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa.
Methods
A published murine dose fractionation study was replicated in silico. The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated.
Results
The previous murine study data were well replicated with fT > MIC selected as the best predictor. However, for increased dosing frequencies fAUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK fT > MIC and fAUC/MIC had similar predictive capacities with preference for fT > MIC when short t1/2 and fAUC/MIC when long t1/2.
Conclusions
A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.
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Abbreviations
- AUC:
-
Area under the curve
- c.i.:
-
Continuous infusion
- CL:
-
Clearance
- CLCR :
-
Creatinine CL
- Cmax :
-
Maximum concentration
- fAUC/MIC:
-
Unbound AUC divided by the MIC
- fCmax/MIC:
-
Unbound Cmax divided by the MIC
- fT > MIC:
-
Unbound time above the MIC
- fu:
-
Fraction unbound
- h:
-
Hour
- i.v.:
-
Intra venous
- k:
-
Rate constant
- ka :
-
Absorption rate
- MIC:
-
Minimum inhibitory concentration
- PD:
-
Pharmacodynamic
- PK:
-
Pharmacokinetic
- q:
-
Dose interval
- Q:
-
Inter compartmental CL
- R2 :
-
Coefficient of determination
- s.c.:
-
Sub cutaneous
- SCr:
-
Serum creatinine
- T:
-
Time
- t1/2 :
-
Half-life (elimination)
- t1/2β :
-
Half-life of the β-phase
- TDM:
-
Therapeutic drug monitoring
- V:
-
Volume
- Vc:
-
Central Volume (of distribution)
- Vp:
-
Peripheral volume (of distribution)
- w:
-
Week
- WT:
-
Weight
REFERENCES
European Medicines Agency. CHMP/EWP/2655/99 - Points to consider on pharmacokinetics and pharmacodynamics in the development of antibacterial medicinal products. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003420.pdf. Accessed 29 Jan 2015.
European Medicines Agency. Concept Paper on revision of the points to consider on pharmacokinetics and pharmacodynamics in the development of antibacterial medicinal products (CHMP/EWP/2655/99) and conversion to a CHMP guideline. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2014/02/WC500162135.pdf. Accessed 29 Jan 2015.
U.S. Food and Drug Administration. Developing antimicrobial drugs — General considerations for clinical trials (Draft Guidance). http://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm064980.htm. Accessed 20 Jan 2015.
Craig WA. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin Infect Dis: Off Publ Infect Dis Soc Am. 1998;26:1–10.
Gloede J, Scheerans C, Derendorf H, Kloft C. In vitro pharmacodynamic models to determine the effect of antibacterial drugs. J Antimicrob Chemother. 2010;65:186–201.
Lodise TP, Lomaestro BM, Drusano GL, P. Society of Infectious Diseases. Application of antimicrobial pharmacodynamic concepts into clinical practice: focus on beta-lactam antibiotics: insights from the Society of Infectious Diseases Pharmacists. Pharmacotherapy. 2006;26:1320–32.
Mouton JW, Dudley MN, Cars O, Derendorf H, Drusano GL. Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs: an update. J Antimicrob Chemother. 2005;55:601–7.
Mouton JW, Brown DF, Apfalter P, Canton R, Giske CG, Ivanova M, et al. The role of pharmacokinetics/pharmacodynamics in setting clinical MIC breakpoints: the EUCAST approach. Clin Microbiol Infect: Off Publ Eur Soc Clin Microbiol Infect Dis. 2012;18:E37–45.
Nielsen EI, Friberg LE. Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs. Pharmacol Rev. 2013;65:1053–90.
Mohamed AF, Cars O, Friberg LE. A pharmacokinetic/pharmacodynamic model developed for the effect of colistin on Pseudomonas aeruginosa in vitro with evaluation of population pharmacokinetic variability on simulated bacterial killing. J Antimicrob Chemother. 2014;69:1350–1361.
Mohamed AF, Karaiskos I, Plachouras D, Karvanen M, Pontikis K, Jansson B, et al. Application of a loading dose of colistin methanesulfonate in critically ill patients: population pharmacokinetics, protein binding, and prediction of bacterial kill. Antimicrob Agents Chemother. 2012;56:4241–9.
Mohamed AF, Nielsen EI, Cars O, Friberg LE. A pharmacokinetic-pharmacodynamic model for gentamicin and its adaptive resistance with predictions of dosing schedules in newborn infants. Antimicrob Agents Chemother. 2012;56:179–88.
Nielsen EI, Viberg A, Lowdin E, Cars O, Karlsson MO, Sandstrom M. Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments. Antimicrob Agents Chemother. 2007;51:128–36.
Mizunaga S, Kamiyama T, Fukuda Y, Takahata M, Mitsuyama J. Influence of inoculum size of Staphylococcus aureus and Pseudomonas aeruginosa on in vitro activities and in vivo efficacy of fluoroquinolones and carbapenems. J Antimicrob Chemother. 2005;56:91–6.
Mohamed AF, Kristoffersson AN, Karvanen M, Cars O, Nielsen EI, Friberg LE. Interaction of colistin and meropenem on a wild-type and a resistant strain of pseudomonas aeruginosa in-vitro as quantified in a mechanism-based model. J Antimicrob Chemother (in press).
Drusano GL. Prevention of resistance: a goal for dose selection for antimicrobial agents. Clin Infect Dis: Off Publ Infect Dis Soc Am. 2003;36:S42–50.
Roberts JA, Paul SK, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, et al. DALI: defining antibiotic levels in intensive care unit patients: are current beta-lactam antibiotic doses sufficient for critically ill patients? Clin Infect Dis: Off Publ Infect Dis Soc Am. 2014;58:1072–83.
Huttner A, Harbarth S, Hope WW, Lipman J, Roberts JA. Therapeutic drug monitoring of the β-lactam antibiotics: what is the evidence and which patients should we be using it for? J J Antimicrob Chemother. 2015;70:3178–3183
Karlsson MO, Beal SL, Sheiner LB. Three new residual error models for population PK/PD analyses. J Pharmacokinet Biopharm. 1995;23:651–72.
Katsube T, Yamano Y, Yano Y. Pharmacokinetic-pharmacodynamic modeling and simulation for in vivo bactericidal effect in murine infection model. J Pharm Sci. 2008;97:1606–14.
Li C, Kuti JL, Nightingale CH, Nicolau DP. Population pharmacokinetic analysis and dosing regimen optimization of meropenem in adult patients. J Clin Pharmacol. 2006;46:1171–8.
van den Anker JN, Pokorna P, Kinzig-Schippers M, Martinkova J, de Groot R, Drusano GL, et al. Meropenem pharmacokinetics in the newborn. Antimicrob Agents Chemother. 2009;53:3871–9.
Sugihara K, Sugihara C, Matsushita Y, Yamamura N, Uemori M, Tokumitsu A, et al. In vivo pharmacodynamic activity of tomopenem (formerly CS-023) against Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus in a murine thigh infection model. Antimicrob Agents Chemother. 2010;54:5298–302.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16:31–41.
West GB, Brown JH, Enquist BJ. A general model for the origin of allometric scaling laws in biology. Science. 1997;276:122–6.
Jonsson EN, Wade JR, Karlsson MO. Comparison of some practical sampling strategies for population pharmacokinetic studies. J Pharmacokinet Biopharm. 1996;24:245–63.
Kitamura Y, Yoshida K, Kusama M, Sugiyama Y. A proposal of a pharmacokinetic/pharmacodynamic (PK/PD) index map for selecting an optimal PK/PD index from conventional indices (AUC/MIC, Cmax/MIC, and TAM) for antibiotics. Drug Metab Pharmacokinet. 2014;29:455–462.
Turnidge JD. The pharmacodynamics of beta-lactams. Clin Infect Dis: Off Publ Infect Dis Soc Am. 1998;27:10–22.
EUCAST. Meropenem - Rationale for the EUCAST clinical breakpoints. www.eucast.org. Accessed 29 Jan 2015.
MacGowan A. Revisiting Beta-lactams - PK/PD improves dosing of old antibiotics. Curr Opin Pharmacol. 2011;11:470–6.
Nielsen EI, Cars O, Friberg LE. Pharmacokinetic/pharmacodynamic (PK/PD) indices of antibiotics predicted by a semimechanistic PKPD model: a step toward model-based dose optimization. Antimicrob Agents Chemother. 2011;55:4619–30.
Craig W, Ebert S. Killing and regrowth of bacteria in vitro: a review. Scand J Infect Dis Suppl. 1989;74:63–70.
Drusano G, Lodise T, Melnick D, Liu W, Oliver A, Mena A, et al. Meropenem penetration into epithelial lining fluid in mice and humans and delineation of exposure targets. Antimicrob Agents Chemother. 2011;55:3406–12.
Rowland M, Peck C, Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol. 2011;51:45–73.
ACKNOWLEDGMENTS AND DISCLOSURES
This work was in part supported by funding from F. Hoffmann-La Roche Ltd, Switzerland and by the Swedish Foundation for Strategic Research.
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Kristoffersson, A.N., David-Pierson, P., Parrott, N.J. et al. Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs. Pharm Res 33, 1115–1125 (2016). https://doi.org/10.1007/s11095-016-1856-x
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DOI: https://doi.org/10.1007/s11095-016-1856-x