What is it about?
The publication deals with how one can utilize pharmacological response-time series in order to better understand what quantitative properties are governing the onset, intensity and duration of the pharmacological effect when plasma or tissue exposure of drugs are lacking
Featured Image
Photo by Daniele Levis Pelusi on Unsplash
Why is it important?
Traditionally pharmacological data are presented as dose-response graphs where a single response time measure or the total area under the response-time curve is plotted agaimst the administered dose. By modelling the complete response-time course(s) as such one utilizes hidden information about the causes of a pharmacological effect in a more efficient way. By modelling the response-time courses one gain knowledge and the model becomes the repository of all data and not just a transformation.
Perspectives
This approach has a tremendous potential in that drug data from several studies may be pooled and analyzed jointly when proper exposure data are lacking or sparse. More recently the DRT-approach has gained momentum in both Clinical and pre-Clinical studies of oncology medicines.
Professor Johan Gabrielsson
Sveriges lantbruksuniversitet
Read the Original
This page is a summary of: Dose-Response-Time Data Analysis: An Underexploited Trinity, Pharmacological Reviews, December 2018, American Society for Pharmacology & Experimental Therapeutics (ASPET),
DOI: 10.1124/pr.118.015750.
You can read the full text:
Contributors
The following have contributed to this page
