Photodynamic therapy: Toward a systemic computational model.

We have designed a systemic model to understand the effect of Photodynamic Therapy (PDT) on long time scales. The model takes into account cell necrosis due to oxygen reactive species, cell apoptosis through the caspase pathway and the competition between healthy and tumor cells. We attempted to describe the system using state of the art computational techniques (necrosis and apoptosis) and simple models that allow a deeper understanding of the long time scale processes involved (healing and tumor growth). We analyzed the influence of the surface and tumor depth on the effectiveness of different treatment plans and we proposed, for the set of parameters used in this work, an optimum timing between sessions of PDT.

In silico modelling of apoptosis induced by photodynamic therapy.

Photodynamic therapy (PDT) is an emergent technique used for the treatment of several diseases. After PDT, cells die by necrosis, apoptosis or autophagy. Necrosis is produced immediately during photodynamic therapy by high concentration of reactive oxygen species, apoptosis and autophagy are triggered by mild or low doses of light and photosensitizer. In this work we model the cell response to low doses of PDT assuming a bi-dimensional matrix of interacting cells. For each cell of the matrix we simulate in detail, with the help of the Gillespie's algorithm, the two main chemical pathways leading to apoptosis. We unveil the role of both pathways in the cell death rate of the tumor, as well as the relevance of several molecules in the process. Our model suggests values of concentrations for several species of molecules to enhance the effectiveness of PDT.