Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, 75124, Sweden.
Nat Commun. 2017 Dec 14;8(1):2129. doi: 10.1038/s41467-017-01929-y.
Assessment of pharmacodynamic (PD) drug interactions is a cornerstone of the development of combination drug therapies. To guide this venture, we derive a general pharmacodynamic interaction (GPDI) model for ≥2 interacting drugs that is compatible with common additivity criteria. We propose a PD interaction to be quantifiable as multidirectional shifts in drug efficacy or potency and explicate the drugs' role as victim, perpetrator or even both at the same time. We evaluate the GPDI model against conventional approaches in a data set of 200 combination experiments in Saccharomyces cerevisiae: 22% interact additively, a minority of the interactions (11%) are bidirectional antagonistic or synergistic, whereas the majority (67%) are monodirectional, i.e., asymmetric with distinct perpetrators and victims, which is not classifiable by conventional methods. The GPDI model excellently reflects the observed interaction data, and hence represents an attractive approach for quantitative assessment of novel combination therapies along the drug development process.
药效学(PD)药物相互作用的评估是联合药物治疗开发的基石。为了指导这一尝试,我们为≥2 种相互作用的药物推导出一个通用的药效学相互作用(GPDI)模型,该模型与常见的加性标准兼容。我们提出药效学相互作用可以量化为药物疗效或效力的多向变化,并阐明药物作为受害者、施害者甚至同时两者的角色。我们在酿酒酵母的 200 个组合实验数据集上评估了 GPDI 模型对传统方法的有效性:22%的相互作用呈加性,少数(11%)的相互作用呈双向拮抗或协同作用,而大多数(67%)的相互作用呈单向作用,即不对称,有明显的施害者和受害者,这不能用传统方法进行分类。GPDI 模型极好地反映了观察到的相互作用数据,因此代表了一种有吸引力的方法,可用于沿药物开发过程对新型组合疗法进行定量评估。