Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, New Jersey 08854, USA.
Pharm Res. 2011 May;28(5):1081-9. doi: 10.1007/s11095-010-0363-8. Epub 2011 Jan 14.
The area under the curve (AUC) is commonly used to assess the extent of exposure of a drug. The same concept can be applied to generally assess pharmacodynamic responses and the deviation of a signal from its baseline value. When the initial condition for the response of interest is not zero, there is uncertainty in the true value of the baseline measurement. This necessitates the consideration of the AUC relative to baseline to account for this inherent uncertainty and variability in baseline measurements.
An algorithm to calculate the AUC with respect to a variable baseline is developed by comparing the AUC of the response curve with the AUC of the baseline while taking into account uncertainty in both measurements. Furthermore, positive and negative components of AUC (above and below baseline) are calculated separately to allow for the identification of biphasic responses.
This algorithm is applied to gene expression data to illustrate its ability to capture transcriptional responses to a drug that deviate from baseline and to synthetic data to quantitatively test its performance.
The variable nature of the baseline is an important aspect to consider when calculating the AUC.
曲线下面积（AUC）通常用于评估药物暴露程度。同样的概念也可以用于一般评估药效反应和信号与基线值的偏差。当感兴趣的反应的初始条件不为零时，基线测量的真实值存在不确定性。这需要考虑相对于基线的 AUC，以解释基线测量中固有的不确定性和变异性。
通过比较响应曲线的 AUC 与基线的 AUC，同时考虑到两种测量的不确定性，开发了一种计算相对于变量基线的 AUC 的算法。此外，还分别计算 AUC 的正负分量（高于和低于基线），以允许识别双相反应。
将该算法应用于基因表达数据，以说明其捕获药物引起的偏离基线的转录反应的能力，并应用于合成数据对其性能进行定量测试。
在计算 AUC 时，基线的可变性是一个重要的考虑因素。
