Journal
TRENDS IN PHARMACOLOGICAL SCIENCES
Volume 41, Issue 11, Pages 882-895Publisher
CELL PRESS
DOI: 10.1016/j.tips.2020.09.005
Keywords
-
Categories
Ask authors/readers for more resources
The model-informed drug discovery and development paradigm is now well established among the pharmaceutical industry and regulatory agencies. This success has been mainly due to the ability of pharmacometrics to bring together different modeling strategies, such as population pharmacokinetics/pharmacodynamics (PK/PD) and systems biology/pharmacology. However, there are promising quantitative approaches that are still seldom used by pharmacometricians and that deserve consideration. One such case is the stochastic modeling approach, which can be important when modeling small populations because random events can have a huge impact on these systems. In this review, we aim to raise awareness of stochastic models and how to combine themwith existingmodeling techniques, with the ultimate goal ofmaking future drug-disease models more versatile and realistic.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available