Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam, The Netherlands.
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, The Netherlands.
Bull Math Biol. 2020 Jul 31;82(8):103. doi: 10.1007/s11538-020-00780-5.
Oncolytic virotherapy is known as a new treatment to employ less virulent viruses to specifically target and damage cancer cells. This work presents a cellular automata model of oncolytic virotherapy with an application to pancreatic cancer. The fundamental biomedical processes (like cell proliferation, mutation, apoptosis) are modeled by the use of probabilistic principles. The migration of injected viruses (as therapy) is modeled by diffusion through the tissue. The resulting diffusion-reaction equation with smoothed point viral sources is discretized by the finite difference method and integrated by the IMEX approach. Furthermore, Monte Carlo simulations are done to quantitatively evaluate the correlations between various input parameters and numerical results. As we expected, our model is able to simulate the pancreatic cancer growth at early stages, which is calibrated with experimental results. In addition, the model can be used to predict and evaluate the therapeutic effect of oncolytic virotherapy.
溶瘤病毒治疗被认为是一种利用毒力较弱的病毒来特异性靶向和破坏癌细胞的新疗法。本工作提出了一种溶瘤病毒治疗的细胞自动机模型，并将其应用于胰腺癌。通过使用概率原理对基本的生物医学过程（如细胞增殖、突变、细胞凋亡）进行建模。通过组织内扩散来模拟注射病毒（作为治疗方法）的迁移。使用有限差分法对具有平滑点病毒源的扩散-反应方程进行离散化，并通过 IMEX 方法进行积分。此外，还进行了蒙特卡罗模拟，以定量评估各种输入参数与数值结果之间的相关性。正如我们所预期的那样，我们的模型能够模拟早期胰腺癌的生长，并且与实验结果相吻合。此外，该模型还可用于预测和评估溶瘤病毒治疗的疗效。
