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Predicting the antistaphylococcal effects of daptomycin–rifampicin combinations in an in vitro dynamic model

The Journal of Antibiotics volume 73, pages 101–107 (2020)Cite this article

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Abstract

To predict the effects of combined use of antibiotics on their pharmacodynamics, the susceptibility of Staphylococcus aureus to daptomycin–rifampicin combinations was tested at concentration ratios equal to the ratios of daptomycin and rifampicin 24-h areas under the concentration-time curve (AUC24s) simulated in an in vitro dynamic model. In combination with rifampicin, daptomycin MICs decreased 2- to 31-fold, whereas rifampicin MICs were similar with or without daptomycin. The enhanced susceptibility of S. aureus to daptomycin combined with rifampicin resulted in both an increase of the actual AUC24/MIC ratios and also more pronounced antibacterial effects compared with single treatments. The areas between the control growth and time-kill curves (ABBCs) determined in combined and single daptomycin treatments were plotted against AUC24/MIC on the same graph (r2 0.90). These findings suggest that the effects of daptomycin–rifampicin combinations can be predicted by AUC24/MICs of daptomycin using its MIC determined at pharmacokinetically derived daptomycin-to-rifampicin concentration ratios.

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Funding

The work performed at the Department of Pharmacokinetics & Pharmacodynamics of Gause Institute of New Antibiotics was supported by the Russian Science Foundation (RSF) under Grant number 18-15-00433.

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Authors and Affiliations

  1. Gause Institute of New Antibiotics, Moscow, Russia

    Maria V. Golikova, Elena N. Strukova, Yury A. Portnoy & Alexander A. Firsov

  2. Mount Auburn Hospital, Harvard Medical School, Cambridge, MA, USA

    Stephen H. Zinner

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  1. Maria V. Golikova
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  2. Elena N. Strukova
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  3. Yury A. Portnoy
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  4. Stephen H. Zinner
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  5. Alexander A. Firsov
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Correspondence to Alexander A. Firsov.

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Golikova, M.V., Strukova, E.N., Portnoy, Y.A. et al. Predicting the antistaphylococcal effects of daptomycin–rifampicin combinations in an in vitro dynamic model. J Antibiot 73, 101–107 (2020). https://doi.org/10.1038/s41429-019-0249-x

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