Quadratic and linear controls developing an optimal treatment for the use of BCG immunotherapy in superficial bladder cancer

Quadratic and linear controls developing an optimal treatment for the use of BCG immunotherapy in superficial bladder cancer

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Article ID: iaor201631
Volume: 37
Issue: 1
Start Page Number: 176
End Page Number: 189
Publication Date: Jan 2016
Journal: Optimal Control Applications and Methods
Authors: ,
Keywords: optimization, programming: quadratic, programming: linear, medicine
Abstract:

Our prime objective of the study is to exhibit the advantage to introduce a quadratic control in place of linear control in a cost function to be minimized, and that is associated to an optimal control problem that we formulate for a pre‐validated model of bacillus Calmette‐Guérin (BCG) immunotherapy in superficial bladder cancer. The compartmental model of interest is in the form of a nonlinear system of four ordinary differential equations that describe interactions between the used BCG strain, tumor cells, and immune responses. Previous studies reported that the optimal dose of BCG for treating bladder cancer is yet unknown. Hence, we aim to establish the optimization approach that can be applied for determining the values of the optimal BCG concentration along the therapy period to stimulate immune‐system cells and reduce cancer cells growth during BCG intravesical therapy. Pontryagin's maximum principle and the generalized Legendre–Clebsch condition are employed to provide the explicit formulations of the sought optimal controls. The optimality system is resolved numerically based on a fourth‐order iterative Runge–Kutta progressive‐regressive scheme, which is used to solve a two‐point boundary value problem.

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