Literature DB >> 17543345

Cancer immunotherapy, mathematical modeling and optimal control.

F Castiglione1, B Piccoli.   

Abstract

Clinical immunologists, among other problems, routinely face a question: what is the best time and dose for a certain therapeutic agent to be administered to the patient in order to decrease/eradicate the pathological condition? In cancer immunotherapies the therapeutic agent is something able to elicit an immune response against cancer. The immune response has its own dynamics that depends on the immunogenicity of the therapeutic agent and on the duration of the immune response. The question then is "how can we decide when and how much of the drug to inject so to have a prolonged and effective immune response to the cancer?". This question can be addressed in mathematical terms in two stages: first one construct a mathematical model describing the cancer-immune interaction and secondly one applies the theory of optimal control to determine when and to which extent to stimulate the immune system by means of an immunotherapeutic agent administered in discrete variable doses within the therapeutic period. The solution of this mathematical problem is described and discussed in this article. We show that the method employed can be applied to find the optimal protocol in a variety of clinical problems where the kinetics of the drug or treatment and its influence on the physiologic/pathologic functions have been described by a system of ordinary differential equations.

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Year:  2007        PMID: 17543345     DOI: 10.1016/j.jtbi.2007.04.003

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  17 in total

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Authors:  Neil Senzer; Minal Barve; Joseph Kuhn; Anton Melnyk; Peter Beitsch; Martin Lazar; Samuel Lifshitz; Mitchell Magee; Jonathan Oh; Susan W Mill; Cynthia Bedell; Candice Higgs; Padmasini Kumar; Yang Yu; Fabienne Norvell; Connor Phalon; Nicolas Taquet; Donald D Rao; Zhaohui Wang; Chris M Jay; Beena O Pappen; Gladice Wallraven; F Charles Brunicardi; David M Shanahan; Phillip B Maples; John Nemunaitis
Journal:  Mol Ther       Date:  2011-12-20       Impact factor: 11.454

Review 2.  Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

Authors:  Anna Konstorum; Anthony T Vella; Adam J Adler; Reinhard C Laubenbacher
Journal:  J R Soc Interface       Date:  2017-06       Impact factor: 4.118

Review 3.  Dissecting the Tumor-Immune Landscape in Chimeric Antigen Receptor T-cell Therapy: Key Challenges and Opportunities for a Systems Immunology Approach.

Authors:  Gregory M Chen; Andrew Azzam; Yang-Yang Ding; David M Barrett; Stephan A Grupp; Kai Tan
Journal:  Clin Cancer Res       Date:  2020-03-03       Impact factor: 12.531

4.  Dynamic interplay between tumour, stroma and immune system can drive or prevent tumour progression.

Authors:  R J Seager; Cynthia Hajal; Fabian Spill; Roger D Kamm; Muhammad H Zaman
Journal:  Converg Sci Phys Oncol       Date:  2017-07-28

5.  An agent-based modeling framework linking inflammation and cancer using evolutionary principles: description of a generative hierarchy for the hallmarks of cancer and developing a bridge between mechanism and epidemiological data.

Authors:  Gary An; Swati Kulkarni
Journal:  Math Biosci       Date:  2014-08-01       Impact factor: 2.144

6.  Mass drug administration: the importance of synchrony.

Authors:  Daozhou Gao; Thomas M Lietman; Chao-Ping Dong; Travis C Porco
Journal:  Math Med Biol       Date:  2017-06-01       Impact factor: 1.854

7.  Modeling of Combination Chemotherapy and Immunotherapy for Lung Cancer.

Authors:  Louis T Curtis; Hermann B Frieboes
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2019-07

8.  Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Authors:  Carlos Vilas; Eva Balsa-Canto; Maria-Sonia G García; Julio R Banga; Antonio A Alonso
Journal:  BMC Syst Biol       Date:  2012-07-02

Review 9.  Theoretical modeling techniques and their impact on tumor immunology.

Authors:  Anna Lena Woelke; Manuela S Murgueitio; Robert Preissner
Journal:  Clin Dev Immunol       Date:  2010-12-23

10.  Why Do CD8+ T Cells become Indifferent to Tumors: A Dynamic Modeling Approach.

Authors:  Colin Campbell; Ranran Zhang; Jeremy S Haley; Xin Liu; Thomas Loughran; Todd D Schell; Réka Albert; Juilee Thakar
Journal:  Front Physiol       Date:  2011-07-11       Impact factor: 4.566

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