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Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches.
van Os, Wisse; Zeitlinger, Markus.
Afiliação
  • van Os W; Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria.
  • Zeitlinger M; Department of Clinical Pharmacology, Medical University of Vienna, 1090 Vienna, Austria.
Antibiotics (Basel) ; 10(12)2021 Dec 04.
Article em En | MEDLINE | ID: mdl-34943697
ABSTRACT
Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time-kill curves, in contrast, depict bacterial response over time. In vitro dynamic time-kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time-kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Antibiotics (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Áustria

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Antibiotics (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Áustria