Pharmacodynamic modelling reveals synergistic interaction between docetaxel and SCO-101 in a docetaxel-resistant triple negative breast cancer cell line

https://doi.org/10.1016/j.ejps.2020.105315Get rights and content
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Highlights

  • Combination of SCO-101 and docetaxel show synergistic interaction in resistant TNBC cells.

  • Key information regarding dose ratios and dose levels of docetaxel and SCO-101.

  • Use case for GPDI model, underlining the importance of quantifying interactions.

  • Promising new combination therapy for the treatment of resistant cancers.

Abstract

One of the primary barriers in treating cancer patients is the development of resistance to the available treatments. This is the case for treatment of triple negative breast cancer (TNBC) with docetaxel, which is part of the neoadjuvant treatment for TNBC. The novel compound SCO-101 is under investigation for its potential treatment effect in several types of drug resistant cancer. The aim of this study was to establish a pharmacodynamic model that captures the effect of docetaxel, SCO-101, and the combination on cell survival in docetaxel resistant MDA-MB-231 TNBC cells. Several combination models were compared and a recently published combination model, the general pharmacodynamic interaction model (GPDI), provided the best fit. The model allowed for description and quantification of the interaction between docetaxel and SCO-101 with respects to both maximal effect and potency. Based on this model, SCO-101 has a synergistic effect with docetaxel. This synergy is not present in the maximal effect, but the combination of SCO-101 and docetaxel showed an approximately 60% increase in potency compared to docetaxel alone. Furthermore, the predicted model surface for the combination provided key information regarding promising dose ratios and dose levels for further studies of the combination. Lastly, the study presents a use case for the GPDI model, which provides a way to quantify and interpret drug-drug interactions.

Keywords

Combination therapy
Cancer research
Preclinical development
PK-PD modelling
Drug–drug interactions

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