Urologic studies have reported in several papers that the optimal dose of Bacillus Calmette-Guérin (BCG) immunotherapy in superficial bladder cancer, is still a subject of research. Our main goal from this paper, is to find treatment regimens that minimize the total number of tumors in the presence of a diffusion process. For this, we devise a stochastic model in the form of a nonlinear system of four stochastic differential equations (SDEs) that describe tumor-immune dynamics after BCG instillations. Therefore, we study the existence and the stability results. Then, we introduce a control function in the mathematical model, to represent the dose of BCG intravesical therapy, and we seek its optimal values through the application of a stochastic version of Pontryagin's maximum principle. Finally, we present some numerical simulations using iterative stochastic Runge-Kutta progressive-regressive schemes which we propose for solving the optimality system of the obtained stochastic two-point boundary value problem.

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In order to solve numerically the constant elasticity of variance (CEV) model for pricing of European call option, we propose in this work the Stochastic Runge-Kutta method. We compare the obtained results using this approache, with those given by the Monte Carlo method in Broadie-Kaya [4]. Further, we demonstrate the faster convergence rate of the error obtained by the proposed method. Finally a comparative numerical study is done using different values of the coefficient of elasticity.

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