A Quantitative Systems Pharmacology perspective on the importance of parameter identifiability



Sher A, Niederer SA, Mirams GR, Kirpichnikova A, Allen R, Pathmanathan P, Gavaghan DJ, Van Der Graaf PH & Noble D (2022) A Quantitative Systems Pharmacology perspective on the importance of parameter identifiability. Bulletin of Mathematical Biology, 84 (3), Art. No.: 39.

There is an inherent tension in Quantitative Systems Pharmacology (QSP) between the need to incorporate mathematical descriptions of complex physiology and drug targets with the necessity of developing robust, predictive and well-constrained models. In addition to this there is no "gold standard" for model development and assessment in QSP. Moreover, there can be confusion over terminology such as model and parameter identifiability; complex and simple models; virtual populations; and other concepts, which leads to potential miscommunication and misapplication of methodologies within modelling communities, both the QSP community and related disciplines. This perspective article highlights the pros and cons of using simple (often identifiable) vs. complex (more physiologically detailed but often non-identifiable) models, as well as aspects of parameter identifiability, sensitivity and inference methodologies for model development and analysis. The paper distills the central themes of the issue of identifiability and optimal model size and discusses open challenges.

Quantitative Systems Pharmacology; model identifiability; model development

Bulletin of Mathematical Biology: Volume 84, Issue 3

FundersThe Wellcome Trust
Publication date31/03/2022
Publication date online07/02/2022
Date accepted by journal30/11/2021

People (1)


Dr Anna Kirpichnikova

Dr Anna Kirpichnikova

Lecturer, Mathematics