El Haout, S., Fatani, M., Farha, N., AlSawaftah, N., Mortula, M., Husseini, G.: Modeling the Effects of Chemotherapy and Immunotherapy on Tumor Growth. Journal Of Biomedical Nanotechnology. 17, 2505-2518, 2021
Pratap, J.: An optimal control strategy for mathematically modeling cancer combination therapy. ArXiv Preprint ArXiv:2101.12120, 2021
Nave, O.: A mathematical model for treatment using chemo-immunotherapy. Heliyon. 8, e09288, 2022
Unni, P., Seshaiyer, P.: Mathematical modeling, analysis, and simulation of tumor dynamics with drug interventions. Computational And Mathematical Methods In Medicine, 2019
Sharma, S., Samanta, G.: Analysis of the dynamics of a tumor{immune system with chemotherapy and immunotherapy and quadratic optimal control. Differential Equations And Dynamical Systems. 24, 149-171, 2016
Rodrigues, D., Mancera, P., Carvalho, T., Gonccalves, L.: A mathematical model for chemoimmunotherapy of chronic lymphocytic leukemia. Applied Mathematics And Computation. 349, 118-133, 2019
Hellal, H., Elabsy, H., Elkaranshawy, H.: Mathematical Model for Combined Radiotherapy and Chemotherapy that Fits with Experimental Data. Journal Of Physics: Conference Series. 2287, 012013, 2022
Bekker, R., Kim, S., Pilon-Thomas, S., Enderling, H.: Mathematical modeling of radiotherapy and its impact on tumor interactions with the immune system. Neoplasia. 28, 100796, 2022
Butuc, I., Mirestean, C., Iancu, D.: A nonlinear model in the dynamics of tumourimmune system combined with radiotherapy. UPB Sci. Bull., Ser. A. 81, 311-322, 2019
Pinho, S., Bacelar, F., Andrade, R., Freedman, H.: A mathematical model for the effect of anti-angiogenic therapy in the treatment of cancer tumours by chemotherapy. Nonlinear Analysis: Real World Applications. 14, 815-828, 2013
Esen, O., Cetin, E., Esen, S.: A mathematical immunochemoradiotherapy model: A multiobjective approach. Nonlinear Analysis: Real World Applications. 9, 511-517, 2008
Kuznetsov, M., Kolobov, A.: Algorithm of optimization of fractionated radiotherapy within its combination with antiangiogenic therapy by means of mathematical modeling. ITM Web Of Conferences. 31, 02001 ,2020
Kuznetsov, M., Gubernov, V., Kolobov, A.: Analysis of anticancer efficiency of combined fractionated radiotherapy and antiangiogenic therapy via mathematical modelling. Russian Journal Of Numerical Analysis And Mathematical Modelling.
33, 225-242, 2018
Hutchinson, L., Mueller, H., Gaffney, E., Maini, P., Wagg, J., Phipps, A., Boetsch, C., Byrne, H., Ribba, B.: Modeling longitudinal preclinical tumor size data to identify transient dynamics in tumor response to antiangiogenic drugs. CPT: Pharmacometrics & Systems Pharmacology. 5, 636-645, 2016
Rosch, K., Scholz, M., Hasenclever, D.: Modeling combined chemo-and immunotherapy of high-grade non-Hodgkin lymphoma. Leukemia & Lymphoma. 57, 1697-1708, 2016
Yang, J., Tang, S., Cheke, R.: Modelling pulsed immunotherapy of tumour{immune interaction. Mathematics And Computers In Simulation. 109, 92-112, 2015
Saleem, M., Farman, M., Ahmad, A., Meraj, M. 31.: Mathematical model based assessment of the cancer control by chemo-immunotherapy. Pure And Applied Biology (PAB). 7, 678-683, 2018
Moustad, A.: Set-valued analysis of anti-angiogenic therapy and radiotherapy. Mathematical Modelling And Numerical Simulation With Applications. 2, 187-196, 2022
Kassara, K., Moustad, A.: Angiogenesis inhibition and tumor-immune interactions with chemotherapy by a control set-valued method. Mathematical Biosciences. 231, 135-143, 2011
Moustad, A.: General anti-angiogenic therapy protocols with chemotherapy. International Journal Of Mathematical Modelling & Computations. 11, 2021
Moustad, A.: Feedback protocols for anti-angiogenic therapy in the treatment of cancer tumors by chemotherapy. International Journal on Optimization and Applications. 2, 17-24, 2022
Moustad, A.: General Chemotherapy Protocols. Journal Of Applied Dynamic Systems And Control. 4, 18-25, 2021
Dehingia, K., Sarmah, H., Hosseini, K., Sadri, K., Salahshour, S., Park, C.: An optimal control problem of immuno-chemotherapy in presence of gene therapy. AIMS Mathematics. 6, 11530-11549, 2021
Piretto, E., Delitala, M., Ferraro, M.: Combination therapies and intra-tumoral competition: Insights from mathematical modeling. Journal Of Theoretical Biology. 446, 149-159, 2018
Abdeljalil, S., Essid, A., Aouadi, S.: Analysis of a tumor growth model with a nonlocal boundary condition. ArXiv Preprint ArXiv:2205.12167, 2022
Roy, S., Pal, S.: Optimal personalized therapies in colon-cancer induced immune response using a Fokker-Planck framework. ArXiv Preprint ArXiv:2209.03812, 2022
Malinzi, J., Eladdadi, A., Sibanda, P.: Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment. Journal Of Biological Dynamics. 11, 244-274, 2017
Nono, M., Ngouonkadi, E., Bowong, S., Fotsin, H.: Spatiotemporal dynamics and optimal control of glioma virotherapy enhanced by MEK Inhibitors. Results In Control And Optimization. 7, 100101, 2022
Pomeroy, A., Schmidt, E., Sorger, P., Palmer, A.: Drug independence and the curability of cancer by combination chemotherapy. Trends In Cancer, 2022
Abaid Ur Rehman, M., Ahmad, J., Hassan, A., Awrejcewicz, J., Pawlowski, W., Karamti, H., Alharbi, F.: The Dynamics of a Fractional-Order Mathematical Model of Cancer Tumor Disease. Symmetry. 14, 1694, 2022
Panwar, V., Uduman, P.: Existence a nd Uniqueness of Solutions for Mixed Immunotherapy and Chemotherapy Cancer Treatment Fractional Model with Caputo- Fabrizio Derivative. Progress In Fractional Differentiation And Applications An International Journal. 8, 243-251, 2022
Farayolaa, M., Shaea, S., Siama, F., Mahmudb, R., Ajadic, S.: Mathematical modeling of cancer treatments with fractional derivatives: An Overview. Malaysian Journal Of Fundamental And Applied Sciences. 17, 389-401, 2021
Baleanu, D., Jajarmi, A., Sajjadi, S., Mozyrska, D.: A new fractional model and optimal control of a tumor-immune surveillance with non-singular derivative operator. Chaos: An Interdisciplinary Journal Of Nonlinear Science. 29, 083127 ,2019
Yildiz, T., Arshad, S., Baleanu, D.: Optimal chemotherapy and immunotherapy schedules for a cancer-obesity model with Caputo time fractional derivative. ArXiv Preprint ArXiv:1804.06259, 2018
Sweilam, N., Rihan, F., Seham, A.: A fractional-order delay differential model with optimal control for cancer treatment based on synergy between anti-angiogenic and immune cell therapies. Discrete & Continuous Dynamical Systems-S. 13, 2403, 2020
Erjaee, G., Ostadzad, M., Amanpour, S., Lankarani, K.: Dynamical analysis of the interaction between effector immune and cancer cells and optimal control of chemotherapy. Nonlinear Dynamics, Psychology, And Life Sciences. 17, 449-463, 2013
Shamsaraa, E., Esmailyb, H., Bahrampourc, A.: Mathematical Model of Optimal Chemotherapy and Oncolytic Virotherapy. Filomat. 34, 5195-5206, 2020
Rihan, F., Lakshmanan, S., Maurer, H.: Optimal control of tumour-immune model with time-delay and immuno-chemotherapy. Applied Mathematics And Computation. 353, 147-165, 2019
Das, P., Das, S., Upadhyay, R., Das, P.: Optimal treatment strategies for delayed cancer-immune system with multiple therapeutic approach. Chaos, Solitons & Fractals. 136, 109806, 2020
Moussa, K., Fiacchini, M., Alamir, M.: Probabilistically certied region of attraction of a tumor growth model with combined chemo-and immunotherapy. International Journal Of Robust And Nonlinear Control. 2022
Deepak, K., Sanjeev, K.: A mathematical model of radioimmunotherapy for tumor treatment. African Journal Of Mathematics And Computer Science Research. 3, 101-106, 2010
Kok, H., Rhoon, G., Herrera, T., Overgaard, J., Crezee, J.: Biological modeling in thermoradiotherapy: present status and ongoing developments toward routine clinical use. International Journal Of Hyperthermia. 39, 1126-1140, 2022
Ahmadi, E., Zarei, J., Razavi-Far, R., Saif, M.: A dual approach for positive T-S fuzzy controller design and its application to cancer treatment under immunotherapy and chemotherapy. Biomedical Signal Processing And Control. 58, 101822, 2020
Roguia, S., Mohamed, N.: An optimized rbf-neural network for breast cancer classication. International Journal Of Informatics And Applied Mathematics. 1, 24-34, 2019
Engeland, C., Heidbuechel, J., Araujo, R., Jenner, A.: Improving immunovirotherapies: the intersection of mathematical modelling and experiments. ImmunoInformatics, 100011, 2022
Bunonyo, K., Ebiwareme, L.: Tumor growth mathematical modeling and application of chemo-immunotherapy and radiotherapy treatments. Int J Stat Appl Math. 7(2), 123-132, 2022
Aubin, J.P.: Viability Theory. Modern Birkhauser Classics, Birkhauser Boston. 2009
Grimes, W., Achache, M.: An Infeasible Interior-point Algorithm for Monotone Linear Complementarity Problems. International Journal Of Informatics And Applied Mathematics. 4, 53-59, 2021
Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis
Year 2023,
Volume: 6 Issue: 1, 40 - 56, 16.06.2023
In this paper we set-valued analyze the problem of asymptotic stabilizing the tumor size. A mathematical model of exponential tumor growing caused by carcinogenic substance is considered, with chemotherapy, immunotherapy, and radiotherapy effects. We control the model to be viable in therapeutic domains, and reverse the exponential growing of the tumor size. The obtained controls derive from the derivative cone of therapeutic domains as solution of minimizing problem.
El Haout, S., Fatani, M., Farha, N., AlSawaftah, N., Mortula, M., Husseini, G.: Modeling the Effects of Chemotherapy and Immunotherapy on Tumor Growth. Journal Of Biomedical Nanotechnology. 17, 2505-2518, 2021
Pratap, J.: An optimal control strategy for mathematically modeling cancer combination therapy. ArXiv Preprint ArXiv:2101.12120, 2021
Nave, O.: A mathematical model for treatment using chemo-immunotherapy. Heliyon. 8, e09288, 2022
Unni, P., Seshaiyer, P.: Mathematical modeling, analysis, and simulation of tumor dynamics with drug interventions. Computational And Mathematical Methods In Medicine, 2019
Sharma, S., Samanta, G.: Analysis of the dynamics of a tumor{immune system with chemotherapy and immunotherapy and quadratic optimal control. Differential Equations And Dynamical Systems. 24, 149-171, 2016
Rodrigues, D., Mancera, P., Carvalho, T., Gonccalves, L.: A mathematical model for chemoimmunotherapy of chronic lymphocytic leukemia. Applied Mathematics And Computation. 349, 118-133, 2019
Hellal, H., Elabsy, H., Elkaranshawy, H.: Mathematical Model for Combined Radiotherapy and Chemotherapy that Fits with Experimental Data. Journal Of Physics: Conference Series. 2287, 012013, 2022
Bekker, R., Kim, S., Pilon-Thomas, S., Enderling, H.: Mathematical modeling of radiotherapy and its impact on tumor interactions with the immune system. Neoplasia. 28, 100796, 2022
Butuc, I., Mirestean, C., Iancu, D.: A nonlinear model in the dynamics of tumourimmune system combined with radiotherapy. UPB Sci. Bull., Ser. A. 81, 311-322, 2019
Pinho, S., Bacelar, F., Andrade, R., Freedman, H.: A mathematical model for the effect of anti-angiogenic therapy in the treatment of cancer tumours by chemotherapy. Nonlinear Analysis: Real World Applications. 14, 815-828, 2013
Esen, O., Cetin, E., Esen, S.: A mathematical immunochemoradiotherapy model: A multiobjective approach. Nonlinear Analysis: Real World Applications. 9, 511-517, 2008
Kuznetsov, M., Kolobov, A.: Algorithm of optimization of fractionated radiotherapy within its combination with antiangiogenic therapy by means of mathematical modeling. ITM Web Of Conferences. 31, 02001 ,2020
Kuznetsov, M., Gubernov, V., Kolobov, A.: Analysis of anticancer efficiency of combined fractionated radiotherapy and antiangiogenic therapy via mathematical modelling. Russian Journal Of Numerical Analysis And Mathematical Modelling.
33, 225-242, 2018
Hutchinson, L., Mueller, H., Gaffney, E., Maini, P., Wagg, J., Phipps, A., Boetsch, C., Byrne, H., Ribba, B.: Modeling longitudinal preclinical tumor size data to identify transient dynamics in tumor response to antiangiogenic drugs. CPT: Pharmacometrics & Systems Pharmacology. 5, 636-645, 2016
Rosch, K., Scholz, M., Hasenclever, D.: Modeling combined chemo-and immunotherapy of high-grade non-Hodgkin lymphoma. Leukemia & Lymphoma. 57, 1697-1708, 2016
Yang, J., Tang, S., Cheke, R.: Modelling pulsed immunotherapy of tumour{immune interaction. Mathematics And Computers In Simulation. 109, 92-112, 2015
Saleem, M., Farman, M., Ahmad, A., Meraj, M. 31.: Mathematical model based assessment of the cancer control by chemo-immunotherapy. Pure And Applied Biology (PAB). 7, 678-683, 2018
Moustad, A.: Set-valued analysis of anti-angiogenic therapy and radiotherapy. Mathematical Modelling And Numerical Simulation With Applications. 2, 187-196, 2022
Kassara, K., Moustad, A.: Angiogenesis inhibition and tumor-immune interactions with chemotherapy by a control set-valued method. Mathematical Biosciences. 231, 135-143, 2011
Moustad, A.: General anti-angiogenic therapy protocols with chemotherapy. International Journal Of Mathematical Modelling & Computations. 11, 2021
Moustad, A.: Feedback protocols for anti-angiogenic therapy in the treatment of cancer tumors by chemotherapy. International Journal on Optimization and Applications. 2, 17-24, 2022
Moustad, A.: General Chemotherapy Protocols. Journal Of Applied Dynamic Systems And Control. 4, 18-25, 2021
Dehingia, K., Sarmah, H., Hosseini, K., Sadri, K., Salahshour, S., Park, C.: An optimal control problem of immuno-chemotherapy in presence of gene therapy. AIMS Mathematics. 6, 11530-11549, 2021
Piretto, E., Delitala, M., Ferraro, M.: Combination therapies and intra-tumoral competition: Insights from mathematical modeling. Journal Of Theoretical Biology. 446, 149-159, 2018
Abdeljalil, S., Essid, A., Aouadi, S.: Analysis of a tumor growth model with a nonlocal boundary condition. ArXiv Preprint ArXiv:2205.12167, 2022
Roy, S., Pal, S.: Optimal personalized therapies in colon-cancer induced immune response using a Fokker-Planck framework. ArXiv Preprint ArXiv:2209.03812, 2022
Malinzi, J., Eladdadi, A., Sibanda, P.: Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment. Journal Of Biological Dynamics. 11, 244-274, 2017
Nono, M., Ngouonkadi, E., Bowong, S., Fotsin, H.: Spatiotemporal dynamics and optimal control of glioma virotherapy enhanced by MEK Inhibitors. Results In Control And Optimization. 7, 100101, 2022
Pomeroy, A., Schmidt, E., Sorger, P., Palmer, A.: Drug independence and the curability of cancer by combination chemotherapy. Trends In Cancer, 2022
Abaid Ur Rehman, M., Ahmad, J., Hassan, A., Awrejcewicz, J., Pawlowski, W., Karamti, H., Alharbi, F.: The Dynamics of a Fractional-Order Mathematical Model of Cancer Tumor Disease. Symmetry. 14, 1694, 2022
Panwar, V., Uduman, P.: Existence a nd Uniqueness of Solutions for Mixed Immunotherapy and Chemotherapy Cancer Treatment Fractional Model with Caputo- Fabrizio Derivative. Progress In Fractional Differentiation And Applications An International Journal. 8, 243-251, 2022
Farayolaa, M., Shaea, S., Siama, F., Mahmudb, R., Ajadic, S.: Mathematical modeling of cancer treatments with fractional derivatives: An Overview. Malaysian Journal Of Fundamental And Applied Sciences. 17, 389-401, 2021
Baleanu, D., Jajarmi, A., Sajjadi, S., Mozyrska, D.: A new fractional model and optimal control of a tumor-immune surveillance with non-singular derivative operator. Chaos: An Interdisciplinary Journal Of Nonlinear Science. 29, 083127 ,2019
Yildiz, T., Arshad, S., Baleanu, D.: Optimal chemotherapy and immunotherapy schedules for a cancer-obesity model with Caputo time fractional derivative. ArXiv Preprint ArXiv:1804.06259, 2018
Sweilam, N., Rihan, F., Seham, A.: A fractional-order delay differential model with optimal control for cancer treatment based on synergy between anti-angiogenic and immune cell therapies. Discrete & Continuous Dynamical Systems-S. 13, 2403, 2020
Erjaee, G., Ostadzad, M., Amanpour, S., Lankarani, K.: Dynamical analysis of the interaction between effector immune and cancer cells and optimal control of chemotherapy. Nonlinear Dynamics, Psychology, And Life Sciences. 17, 449-463, 2013
Shamsaraa, E., Esmailyb, H., Bahrampourc, A.: Mathematical Model of Optimal Chemotherapy and Oncolytic Virotherapy. Filomat. 34, 5195-5206, 2020
Rihan, F., Lakshmanan, S., Maurer, H.: Optimal control of tumour-immune model with time-delay and immuno-chemotherapy. Applied Mathematics And Computation. 353, 147-165, 2019
Das, P., Das, S., Upadhyay, R., Das, P.: Optimal treatment strategies for delayed cancer-immune system with multiple therapeutic approach. Chaos, Solitons & Fractals. 136, 109806, 2020
Moussa, K., Fiacchini, M., Alamir, M.: Probabilistically certied region of attraction of a tumor growth model with combined chemo-and immunotherapy. International Journal Of Robust And Nonlinear Control. 2022
Deepak, K., Sanjeev, K.: A mathematical model of radioimmunotherapy for tumor treatment. African Journal Of Mathematics And Computer Science Research. 3, 101-106, 2010
Kok, H., Rhoon, G., Herrera, T., Overgaard, J., Crezee, J.: Biological modeling in thermoradiotherapy: present status and ongoing developments toward routine clinical use. International Journal Of Hyperthermia. 39, 1126-1140, 2022
Ahmadi, E., Zarei, J., Razavi-Far, R., Saif, M.: A dual approach for positive T-S fuzzy controller design and its application to cancer treatment under immunotherapy and chemotherapy. Biomedical Signal Processing And Control. 58, 101822, 2020
Roguia, S., Mohamed, N.: An optimized rbf-neural network for breast cancer classication. International Journal Of Informatics And Applied Mathematics. 1, 24-34, 2019
Engeland, C., Heidbuechel, J., Araujo, R., Jenner, A.: Improving immunovirotherapies: the intersection of mathematical modelling and experiments. ImmunoInformatics, 100011, 2022
Bunonyo, K., Ebiwareme, L.: Tumor growth mathematical modeling and application of chemo-immunotherapy and radiotherapy treatments. Int J Stat Appl Math. 7(2), 123-132, 2022
Aubin, J.P.: Viability Theory. Modern Birkhauser Classics, Birkhauser Boston. 2009
Grimes, W., Achache, M.: An Infeasible Interior-point Algorithm for Monotone Linear Complementarity Problems. International Journal Of Informatics And Applied Mathematics. 4, 53-59, 2021
Moustafid, A. (2023). Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis. International Journal of Informatics and Applied Mathematics, 6(1), 40-56. https://doi.org/10.53508/ijiam.1211906
AMA
Moustafid A. Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis. IJIAM. June 2023;6(1):40-56. doi:10.53508/ijiam.1211906
Chicago
Moustafid, Amine. “Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis”. International Journal of Informatics and Applied Mathematics 6, no. 1 (June 2023): 40-56. https://doi.org/10.53508/ijiam.1211906.
EndNote
Moustafid A (June 1, 2023) Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis. International Journal of Informatics and Applied Mathematics 6 1 40–56.
IEEE
A. Moustafid, “Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis”, IJIAM, vol. 6, no. 1, pp. 40–56, 2023, doi: 10.53508/ijiam.1211906.
ISNAD
Moustafid, Amine. “Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis”. International Journal of Informatics and Applied Mathematics 6/1 (June 2023), 40-56. https://doi.org/10.53508/ijiam.1211906.
JAMA
Moustafid A. Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis. IJIAM. 2023;6:40–56.
MLA
Moustafid, Amine. “Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis”. International Journal of Informatics and Applied Mathematics, vol. 6, no. 1, 2023, pp. 40-56, doi:10.53508/ijiam.1211906.
Vancouver
Moustafid A. Viability Control of Chemo-Immunotherapy and Radiotherapy by Set-Valued Analysis. IJIAM. 2023;6(1):40-56.