Photodynamic therapy (PDT) is used for treating a variety of medical conditions including cancer. Even after many years of PDT research and the large-scale use of PDT treatments by physicians, there are many aspects of PDT, such as quantitative predictions for diffusive light propagation and the kinetics of the light-material interactions, that are not well understood. This can lead to a large variation in treatment results In particular, the dosimetry for treatments is challenging and it is difficult to determine the lasr light energies and the photosensitizer (PS) concentrations that are optimal. In this Phase I SBIR, Simphotek (prime institution), Tech-X (subaward institution) and University of Pennsylvania School of Medicine, i.e. UPenn (subaward institution) will investigate the feasibility of experimentally (UPenn) and computationally (Simphotek/Tech-X) guiding novel and easy-to-use mathematical and numerical methods for PDT. The software product(s) that result(s from the Phase I and Phase II SBIRs will be commercialized for PDT researchers, companies and medical personnel. This exploratory, yet crucial, project combines the knowledge of experts in several disciplines, including optics, mathematics and computer science (Simphotek), numerical algorithms for fast graphical processing units (GPUs) and Monte Carlo calculations (Tech-X) and medical physicists and translational biologists in PDT (UPenn). The commercialized software that results from the Phase I and Phase II SBIRs, will direct the resulting products to PS and PDT researchers and to PDT users worldwide.
In this Phase I project, Simphotek, Inc., Tech-X Corporation and faculty members of the University of Pennsylvania propose to determine the feasibility of combining fast computational methods of light propagation with kinetic rate equations for tissue photophysical processes in order to develop an easy-to-use software program that will model photodynamic therapy (PDT). The simulation software will be directed to PDT researchers and to physicians to improve PDT treatments. The longer-term goal is to develop fully-functional, user-friendly software for PDT researchers and physicians that predicts the optimal conditions for PDT treatments given inputs of photosensitizer parameters, optical properties of tissue and tumor biology.