Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
PLoS One. 2013 Aug 1;8(8):e69301. doi: 10.1371/journal.pone.0069301. Print 2013.
The half-maximal inhibitory concentration IC[Formula: see text] is an important pharmacodynamic index of drug effectiveness. To estimate this value, the dose response relationship needs to be established, which is generally achieved by fitting monotonic sigmoidal models. However, recent studies on Human Immunodeficiency Virus (HIV) mutants developing resistance to antiviral drugs show that the dose response curve may not be monotonic. Traditional models can fail for nonmonotonic data and ignore observations that may be of biologic significance. Therefore, we propose a nonparametric model to describe the dose response relationship and fit the curve using local polynomial regression. The nonparametric approach is shown to be promising especially for estimating the IC[Formula: see text] of some HIV inhibitory drugs, in which there is a dose-dependent stimulation of response for mutant strains. This model strategy may be applicable to general pharmacologic, toxicologic, or other biomedical data that exhibits a nonmonotonic dose response relationship for which traditional parametric models fail.
半数最大抑制浓度 IC[Formula: see text]是药物疗效的一个重要药效学指标。为了估计这个值,需要建立剂量反应关系,这通常通过拟合单调的 S 型模型来实现。然而,最近对人类免疫缺陷病毒 (HIV) 突变体对抗病毒药物产生耐药性的研究表明,剂量反应曲线可能不是单调的。传统模型可能不适用于非单调数据,并且会忽略可能具有生物学意义的观察结果。因此,我们提出了一种非参数模型来描述剂量反应关系,并使用局部多项式回归拟合曲线。非参数方法在估计某些 HIV 抑制药物的 IC[Formula: see text]方面显示出了很大的潜力,对于这些药物,对于突变株存在着剂量依赖性的反应刺激。这种模型策略可能适用于一般的药理学、毒理学或其他表现出传统参数模型失败的非单调剂量反应关系的生物医学数据。