Pharmacokinetic-Pharmacodynamic Modeling of Antibacterial Drugs

Nielsen, Elisabet I.; Friberg, Lena E.

doi:10.1124/pr.111.005769

Cited by 265 publications

(346 citation statements)

References 221 publications

(275 reference statements)

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“…Pharmacokinetic‐pharmacodynamic (PK‐PD) modeling has been proven useful to link preclinical information to clinical information to comprehensively assess antibacterial effects and place them in a clinical context 4. The in vitro ‐based PK‐PD models have also been shown to predict PK‐PD indices from in vivo studies,5 corroborating the translational value of in vitro information.…”

Section: Study Highlightsmentioning

confidence: 91%

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Wicha

Huisinga

Kloft

2017

CPT Pharmacometrics Syst. Pharmacol.

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Broad‐spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad‐spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model mimicking a simplified bacterial life‐cycle of S. aureus was developed upon time‐kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK‐PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK‐PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN‐MER might be favorable over LZD‐MER due to an unfavorable antagonistic interaction between LZD and MER.

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Section: Study Highlightsmentioning

confidence: 91%

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Wicha

Huisinga

Kloft

2017

CPT Pharmacometrics Syst. Pharmacol.

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“…This dynamic information, however, is rarely coupled with clinical PK in a mechanistic manner, even though the potential of mechanism‐based PK/PD‐models for selection of dosing regimens for antibiotics has been demonstrated in several published studies 95, 96. An aspect of this is the importance of and potential need to account for “host” and immune competence.…”

Section: Applicationsmentioning

confidence: 99%

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4–5 December 2014)

Musuamba

Manolis²,

Holford

et al. 2017

CPT Pharmacom & Syst Pharma

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Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late‐stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well‐established and regulatory‐acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4–5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP‐Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)‐based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well‐designed dose‐finding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scientifically rigorous understanding of the dosing rationale.

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“…The 8, 12 and 24 time-points were selected to evaluate bacterial load in case of thrice-a-day, twice-a-day and once-a-day dose regimens respectively; whereas, 9.5 h time-point was selected for internal evaluation as the second inoculum was added to in vitro system at 9.5 h to mimic harsher in vivo conditions. The relationship between the effect and the corresponding PK/PD indices was evaluated according to a sigmoidal E max type function as described in equation 2 [9,6]. The E max model describes the concentration-effect relationship in terms of a baseline effect or E 0 , hence taking into account the baseline condition which can significantly affect the maximum activity of antibiotic i.e.…”

Section: Semi-mechanistic Pharmacokinetic/pharmacodynamic Modeling Anmentioning

confidence: 99%

“…The dosing regimens of antibiotics are based on MIC estimates (a surrogate PD marker for antibacterial response characterization) and the quantification of exposure (changes in concentration of individual components of dose combination) -response (the reduction of bacterial count) relationship [6,7]. The exposure-response relationships help in evaluating the PK/PD indices [8,9] and further identifying the efficacy drivers for understanding the potential activity of antibacterial agents.…”

Section: Introductionmentioning

confidence: 99%

“…After pharmacodynamic selection of drugs combination to combat MRSA, the second step is to optimize dose regimens using their pharmacokinetic/pharmacodynamic (PK/PD) relationships [6,7]. The dosing regimens of antibiotics are based on MIC estimates (a surrogate PD marker for antibacterial response characterization) and the quantification of exposure (changes in concentration of individual components of dose combination) -response (the reduction of bacterial count) relationship [6,7].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dose optimization of ceftriaxone-vancomycin combination using fractional inhibitory concentration kinetics in resistant bacteria

Sharma

Singla²,

Chaudhary³

et al. 2016

ADMET DMPK

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Pharmacokinetic-Pharmacodynamic Modeling of Antibacterial Drugs

Cited by 265 publications

References 221 publications

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies AgainstStaphylococcus AureusExploitingIn VitroInformation

Advanced Methods for Dose and Regimen Finding During Drug Development: Summary of the EMA/EFPIA Workshop on Dose Finding (London 4–5 December 2014)

Dose optimization of ceftriaxone-vancomycin combination using fractional inhibitory concentration kinetics in resistant bacteria

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