TY - GEN
T1 - The Optimal Control of Tumor Virotherapy Treatment Model with External Supplies
AU - Musafir, Raqqasyi Rahmatullah
AU - Trisilowati,
AU - Shofianah, Nur
N1 - Publisher Copyright:
© 2022 American Institute of Physics Inc.. All rights reserved.
PY - 2022/8/2
Y1 - 2022/8/2
N2 - This paper focuses on optimal control of a tumor virotherapy treatment model with external supplies such as chemo-drugs or viral injection. This model contains four subpopulation compartments: uninfected tumor cells by viruses, infected tumor cells, oncolytic viruses, and immune cells. The model is given by the system of ordinary differential equations. Chemo-drugs can slow down the growth of tumor cells and immune cells while the viral injection accelerate the growth of oncolytic viruses. We defined a positive control with maximum tolerated dosage (MTDs) as upper bound, that is, u1 and u2 represent chemotherapy drug dosage and viral injection dosage, respectively. The objective of this optimal control is to minimize tumor density and side effects of the controls. Here, we get optimal control by applying Pontryagin's Minimum Principle. Numerical simulation is implemented using the Forward-Backward Sweep Method with three strategies: u1 only, u2 only, and u1 with u2, respectively. Here, we set u1 weight much larger than u2 weight, that is, 50 and 1, respectively. The simulation shows that the third strategy (u1 with u2) has minimum side effects and density of tumors than the others controls combination. The chemo-drugs can be consumed as much as MTDs in the first quarter and need to be reduced to depletion at the end of controls. The viral injection can be consumed up to 80 percent of the MTDs at the start and needs to be reduced exponentially until the end at the period of the controls.
AB - This paper focuses on optimal control of a tumor virotherapy treatment model with external supplies such as chemo-drugs or viral injection. This model contains four subpopulation compartments: uninfected tumor cells by viruses, infected tumor cells, oncolytic viruses, and immune cells. The model is given by the system of ordinary differential equations. Chemo-drugs can slow down the growth of tumor cells and immune cells while the viral injection accelerate the growth of oncolytic viruses. We defined a positive control with maximum tolerated dosage (MTDs) as upper bound, that is, u1 and u2 represent chemotherapy drug dosage and viral injection dosage, respectively. The objective of this optimal control is to minimize tumor density and side effects of the controls. Here, we get optimal control by applying Pontryagin's Minimum Principle. Numerical simulation is implemented using the Forward-Backward Sweep Method with three strategies: u1 only, u2 only, and u1 with u2, respectively. Here, we set u1 weight much larger than u2 weight, that is, 50 and 1, respectively. The simulation shows that the third strategy (u1 with u2) has minimum side effects and density of tumors than the others controls combination. The chemo-drugs can be consumed as much as MTDs in the first quarter and need to be reduced to depletion at the end of controls. The viral injection can be consumed up to 80 percent of the MTDs at the start and needs to be reduced exponentially until the end at the period of the controls.
UR - https://www.scopus.com/pages/publications/85136802955
U2 - 10.1063/5.0082986
DO - 10.1063/5.0082986
M3 - Conference contribution
AN - SCOPUS:85136802955
T3 - AIP Conference Proceedings
BT - 8th Symposium on Biomathematics, Symomath 2021
A2 - Megawati, Noorma Yulia
A2 - Susyanto, Nanang
A2 - Ertiningsih, Dwi
A2 - Sari, Eminugroho Ratna
A2 - Saptaningtyas, Fitriana Yuli
A2 - Tantrawan, Made
A2 - Amalia, Oki Almas
A2 - Susiana, null
PB - American Institute of Physics Inc.
T2 - 8th Symposium on Biomathematics: Bridging Mathematics and Covid-19 Through Multidisciplinary Collaboration, Symomath 2021
Y2 - 16 July 2021 through 17 July 2021
ER -