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In vitro pharmacodynamic modelling of anidulafungin against Candida spp.

Este es el resumen de nuestra publicación titulada «In vitro pharmacodynamic modelling of anidulafungin against Candida spp.» que aparecerá en breve en la revista International Journal of Antimicrobial Agents sobre un modelo farmacodinámico de la actividad de la anidulafungina contra diferentes especies del hongo Candida.

Felicito a mis colegas Sandra Gil Alonso, Nerea Jauregizar, Ignacio Ortega, Elena Eraso y Elena Suarez por su excelente trabajo.

El trabajo completo está en International Journal of Antimicrobial Agents.

Highlights

  • An alternative pharmacodynamic (PD) approach has been proposed to offer detailed information about antimicrobial efficacy.
  • Mathematical modelling of time–kill curve data was performed using a non-linear mixed-effects approach as appropriate with NONMEM 7.
  • Anidulafungin EC50 and Emax parameters were estimated for nine strains of Candida included in the clades of C. albicans, C. glabrata and C. parapsilosis.
  • We have established an appropriate in vitro PD model to describe the activity of anidulafungin againstCandida.

Abstract

The aim of this study was to fit anidulafungin in vitro static time–kill data from nine strains of Candida with a pharmacodynamic (PD) model in order to describe the antifungal activity of this drug against Candida spp. Time–kill data from strains of Candida albicans, Candida glabrata and Candida parapsilosis clades were best fit using an adapted sigmoidal Emax model and resulted in a set of PD parameters (Emax, EC50 and Hill factor) for each fungal strain. The data were analysed with NONMEM 7. Anidulafungin was effective in a species- and concentration-dependent manner against the strains of C. glabrata and C. parapsilosis clades as observed with the EC50 estimates. Maximum killing rate constant (Emax) values were higher against C. glabrata and C. parapsilosis complex strains. In conclusion, we demonstrated that the activity of anidulafungin against Candida can be accurately described using an adapted sigmoidal Emax model.

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