Quantitative systems pharmacology (QSP) proved to be a powerful tool to elucidate the underlying pathophysiological complexity that is intensified by the biological variability and overlapped by the level of sophistication of drug dosing regimens. Therapies combining immunotherapy with more traditional therapeutic approaches, including chemotherapy and radiation, are increasingly being used. These combinations are purposed to amplify the immune response against the tumor cells and modulate the suppressive tumor microenvironment (TME). In order to get the best performance from these combinatorial approaches and derive rational regimen strategies, a better understanding of the interaction of the tumor with the host immune system is needed. The objective of the current work is to provide new insights into the dynamics of immune-mediated TME and immune-oncology treatment. As a case study, we will use a recent QSP model by Kosinsky et al. [J. Immunother. Cancer 6, 17 (2018)] that aimed to reproduce the dynamics of interaction between tumor and immune system upon administration of radiation therapy and immunotherapy. Adopting a dynamical systems approach, we here investigate the qualitative behavior of the representative components of this QSP model around its key parameters. The ability of T cells to infiltrate tumor tissue, originally identified as responsible for individual therapeutic inter-variability [Y. Kosinsky et al., J. Immunother. Cancer 6, 17 (2018)], is shown here to be a saddle-node bifurcation point for which the dynamical system oscillates between two states: tumor-free or maximum tumor volume. By performing a bifurcation analysis of the physiological system, we identified equilibrium points and assessed their nature. We then used the traditional concept of basin of attraction to assess the performance of therapy. We showed that considering the therapy as input to the dynamical system translates into the changes of the trajectory shapes of the solutions when approaching equilibrium points and thus providing information on the issue of therapy.
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February 2021
Research Article|
February 16 2021
Dynamical systems analysis as an additional tool to inform treatment outcomes: The case study of a quantitative systems pharmacology model of immuno-oncology
Special Collection:
Dynamical Disease: A Translational Perspective
Aymen Balti;
Aymen Balti
1
Faculty of pharmacy, Université de Montréal
, Montreal, Quebec H3C 3J7, Canada
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Didier Zugaj;
Didier Zugaj
a)
2
Syneos Health, Clinical Pharmacology
, Quebec, Quebec G1P 0A2, Canada
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Frédérique Fenneteau;
Frédérique Fenneteau
1
Faculty of pharmacy, Université de Montréal
, Montreal, Quebec H3C 3J7, Canada
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Pierre-Olivier Tremblay;
Pierre-Olivier Tremblay
2
Syneos Health, Clinical Pharmacology
, Quebec, Quebec G1P 0A2, Canada
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Fahima Nekka
Fahima Nekka
b)
1
Faculty of pharmacy, Université de Montréal
, Montreal, Quebec H3C 3J7, Canada
3
Centre de recherches mathématiques, Université de Montréal
, Montreal, Quebec H3C 3J7, Canada
b)Author to whom correspondence should be addressed: fahima.nekka@umontreal.ca
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a)
Electronic mail: didier.zugaj@syneoshealth.com
b)Author to whom correspondence should be addressed: fahima.nekka@umontreal.ca
Note: This paper is part of the Focus Issue on Dynamical Disease: A Translational Perspective.
Chaos 31, 023124 (2021)
Article history
Received:
July 18 2020
Accepted:
January 22 2021
Citation
Aymen Balti, Didier Zugaj, Frédérique Fenneteau, Pierre-Olivier Tremblay, Fahima Nekka; Dynamical systems analysis as an additional tool to inform treatment outcomes: The case study of a quantitative systems pharmacology model of immuno-oncology. Chaos 1 February 2021; 31 (2): 023124. https://doi.org/10.1063/5.0022238
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