Assessment of pharmacologic area under the curve when baselines are variable.

Pharm Res

Biomedical Engineering Department, Rutgers University, 599 Taylor Road, Piscataway, New Jersey 08854, USA.

Published: May 2011

AI Article Synopsis

  • The AUC (Area Under the Curve) is important for measuring drug exposure and evaluating variations in pharmacodynamic responses against a potentially non-zero baseline, which introduces uncertainty.
  • An algorithm was developed to calculate AUC relative to variable baselines, recognizing uncertainties and separating positive and negative AUC components for a better analysis of responses.
  • The algorithm was effectively tested using gene expression data to demonstrate its capability in capturing drug-induced transcriptional changes, highlighting the significance of accounting for baseline variability in AUC calculations.

Article Abstract

Purpose: 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.

Methods: 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.

Results: 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.

Conclusions: The variable nature of the baseline is an important aspect to consider when calculating the AUC.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152796PMC
http://dx.doi.org/10.1007/s11095-010-0363-8DOI Listing

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