Lederer Simone, Dijkstra Tjeerd M H, Heskes Tom
Institute for Computing and Information Sciences, Radboud University, Nijmegen, Netherlands.
Max Planck Institute for Developmental Biology, Tübingen, Germany.
Front Pharmacol. 2018 Feb 6;9:31. doi: 10.3389/fphar.2018.00031. eCollection 2018.
High-throughput techniques allow for massive screening of drug combinations. To find combinations that exhibit an interaction effect, one filters for promising compound combinations by comparing to a response without interaction. A common principle for no interaction is Loewe Additivity which is based on the assumption that no compound interacts with itself and that two doses from different compounds having the same effect are equivalent. It then should not matter whether a component is replaced by the other or vice versa. We call this assumption the Loewe Additivity Consistency Condition (LACC). We derive explicit and implicit null reference models from the Loewe Additivity principle that are equivalent when the LACC holds. Of these two formulations, the implicit formulation is the known General Isobole Equation (Loewe, 1928), whereas the explicit one is the novel contribution. The LACC is violated in a significant number of cases. In this scenario the models make different predictions. We analyze two data sets of drug screening that are non-interactive (Cokol et al., 2011; Yadav et al., 2015) and show that the LACC is mostly violated and Loewe Additivity not defined. Further, we compare the measurements of the non-interactive cases of both data sets to the theoretical null reference models in terms of bias and mean squared error. We demonstrate that the explicit formulation of the null reference model leads to smaller mean squared errors than the implicit one and is much faster to compute.
高通量技术允许对药物组合进行大规模筛选。为了找到表现出相互作用效应的组合,人们通过与无相互作用的反应进行比较来筛选有前景的化合物组合。无相互作用的一个常见原则是洛氏加和性,它基于这样的假设:没有化合物与自身相互作用,并且来自不同化合物的具有相同效应的两个剂量是等效的。那么,一个成分被另一个成分替代与否应该无关紧要。我们将这个假设称为洛氏加和性一致性条件(LACC)。我们从洛氏加和性原则推导出显式和隐式零参考模型,当LACC成立时它们是等效的。在这两种表述中,隐式表述是已知的通用等效线方程(洛氏,1928年),而显式表述是新的贡献。在大量情况下,LACC不成立。在这种情况下,这些模型会做出不同的预测。我们分析了两个非交互式药物筛选数据集(科科尔等人,2011年;亚达夫等人,2015年),并表明LACC大多不成立,洛氏加和性未定义。此外,我们将两个数据集的非交互式情况的测量值与理论零参考模型在偏差和均方误差方面进行了比较。我们证明,零参考模型的显式表述比隐式表述导致更小的均方误差,并且计算速度快得多。