The union between structural and practical identifiability makes strength in reducing oncological model complexity: a case study
type: Item
instance of: scholarly article
title: The union between structural and practical identifiability makes strength in reducing oncological model complexity: a case study
zbMATH Open document ID: 1398.93040
DOI: 10.1155/2018/2380650
author: Maria Pia Saccomani
author: Karl Thomaseth
published in: Complexity
publication date: 2018-09-26T00:00:00Z
review text: Summary: Mathematical models are increasingly proposed to describe tumor's dynamic response to treatments with the aims of improving their efficacy. The most widely used are nonlinear ODE models, whose identification is often difficult due to experimental limitations. We focus on the issue of parameter estimation in model-based oncological studies. Given their complexity, many of these models are unidentifiable having an infinite number of parameter solutions. These equivalently describe experimental data but are associated with different dynamic evolution of unmeasurable variables. We propose a joint use of two different identifiability methodologies, \textit{structural identifiability} and \textit{practical identifiability}, which are traditionally regarded as disjoint. This new methodology provides the number of parameter solutions, the analytic relations between the unidentifiable parameters useful to reduce model complexity, a ranking between parameters revealing the most reliable estimates, and a way to disentangle the various causes of nonidentifiability. It is implementable by using available differential algebra software and statistical packages. This methodology can constitute a powerful tool for the oncologist to discover the behavior of inaccessible variables of clinical interest and to correctly address the experimental design. A complex model to study ``in vivo'' antitumor activity of interleukin-21 on tumor eradication in different cancers in mice is illustrated.
Mathematics Subject Classification ID: 93A30
Mathematics Subject Classification ID: 92C37
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 93E10
zbMATH DE Number: 6944078
describes a project that uses: LAPACK
describes a project that uses: R
describes a project that uses: NONMEM
describes a project that uses: DAISY
describes a project that uses: AMIGO
describes a project that uses: COPASI
describes a project that uses: COMBOS
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/2380650
OpenAlex ID: W2790327763
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description: scientific article; zbMATH DE number 6944078