Control of the Amount of Oncolytic Virus Injection by Considering Time Delay

Oncolytic viral therapy is a new promising strategy against cancer. Oncolytic viruses can replicate in cancer cells rather than in normal cells, leading to lysis of the tumor mass. Besides, oncotic viruses can stimulate the immune system. Since cancer viral therapy applies a virus infection, its complex dynamics should be analyzed using a mathematical model in order to identify its most effective treatment mechanism. During cancer viral therapy, there is a time delay from the initial virus infection of the tumor cells up to the time those infected cells reach the stage of being able to infect other cells. It is important to understand how the delay affects the cancer viral therapy. For this purpose, a mathematical model is introduced to identify this delay. To analyze the effects of delay on virus therapy, the model was reconstructed by adding both virus therapy and immunotherapy control. Finally, using a numerical simulation, a fuzzy PDC controller was designed for the first time. Numerical results showed that with proper control, the tumor cell population decreased to below 10% over time. It is also observed that the use of a delay-independent stability criterion for the design of the PDC controller has reduced the sensitivity of the system response to increasing time delay to an acceptable level. Since the studied system is introduced only in one reference and only the optimal controller is applied, the comparison shows the superiority and power of the designed fuzzy PDC controller.