Investigation of the robustness of two models for assessing synergy in pre-clinical drug combination studies.

Anne Whitehead, Ting-Li Su, Helene Thygesen, Matthew Sperrin, Chris Harbron

    Research output: Contribution to journalArticlepeer-review


    Pre-clinical studies may be used to screen for synergistic combinations of drugs. The types of in vitro assays used for this purpose will depend upon the disease area of interest. In oncology, one frequently used study measures cell line viability: cells placed into wells on a plate are treated with doses of two compounds, and cell viability is assessed from an optical density measurement corrected for blank well values. These measurements are often transformed and analysed as cell survival relative to untreated wells. The monotherapies are assumed to follow the Hill equation with lower and upper asymptotes at 0 and 1, respectively. Additionally, a common variance about the dose-response curve may be assumed. In this paper, we consider two models for incorporating synergy parameters. We investigate the effect of different models of biological variation on the assessment of synergy from both of these models. We show that estimates of the synergy parameters appear to be robust, even when estimates of the other model parameters are biased. Using untransformed measurements provides better coverage of the 95% confidence intervals for the synergy parameters than using transformed measurements, and the requirement to fit the upper asymptote does not cause difficulties. Assuming homoscedastic variances appears to be robust. The added complexity of determining and fitting an appropriate heteroscedastic model does not seem to be justified.
    Original languageEnglish
    Pages (from-to)300-308
    Number of pages8
    JournalPharmaceutical Statistics
    Issue number5
    Publication statusPublished - 2013


    • Loewe additivity
    • drug combination
    • heteroscedasticity
    • interaction index
    • synergy


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