![]() ![]() ![]() Software tools that allow for comparison of different reference models are therefore highly needed for an unbiased analysis of drug combination experiments (e.g. The assumptions being made in these reference models are different from each other, which may produce inconsistent conclusions about the degree of synergy. Commonly-utilized reference models include the Highest single agent (HSA) model ( Berenbaum, 1989), the Loewe additivity model ( Loewe, 1953), the Bliss independence model ( Bliss, 1939), and more recently, the Zero interaction potency (ZIP) model ( Yadav et al., 2015). To quantify the degree of synergy or antagonism, the combination response is often compared against the expected combination response, under the assumption of non-interaction calculated using a reference model ( Tang et al., 2015). Recently, high-throughput drug screening has made it possible to assay a large number of compounds, where a pair of drugs is plated in a dose–response matrix, thus enabling the assessment of drug combination effects at various dose levels ( Mathews Griner et al., 2014 Mott et al., 2015). For improved efficacy, there is a critical need to identify drug combinations, which target both the cancer driver and bypass signals ( Al-Lazikani et al., 2012). However, multiple clinical studies have shown that even when there is a dramatic initial treatment response, cancer cells with high mutational potential and functional redundancy can easily develop drug resistance via a network of compensating or bypassing pathways ( Knight et al., 2010). ![]() Making cancer treatment more personalized and effective is one of the grand challenges of our health care system. ![]()
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