Virtual dose mapping for radiation sterilization

Project Summary Because sterilization is often only considered after a medical device has been fully engineered and manufactured, the costs associated with failing to meet regulatory sterilization requirements are astronomical. In the best case, the sterilization configuration can be iteratively modified until the regulatory requirements are

met. This is an expensive and time-consuming endeavor. However, it is still preferable to the worst cases of having to redesign parts of the device or abandoning the device all together. This “trial-and-error” approach is prevalent throughout all aspects of sterilization. As another example, when

choosing between sterilization modalities, medical device companies often rely on rules-of-thumb which may lead to a suboptimal choice for their device. As such, the medical device industry needs a tool that will allow them to consider sterilization requirements early in the product development process, in the same way they would consider other engineering concerns

such as thermal management, stress distributions, and environmental sensitivity. The incorporation of such a tool into the product development process will allow for a first-class consideration of medical device safety as it relates to sterilization, which has a positive impact on public health. This project proposes to fill this gap in the computer-aided engineering market by developing a simulation tool

capable of predicting the outcome of radiation sterilization without having a fully engineered or manufactured product. From only the Computer Aided Design (CAD) model of the device, the proposed software will be able to calculate the full three-dimensional dose distribution that would be delivered during radiation sterilization. By

leveraging the validated Monte Carlo library Geant4, and the scalability and flexibility of cloud computing, the simulation tool will be fast, accurate, and user-friendly. Developing such a simulation tool involves architecting and implementing a flexible cloud computing infrastructure and user-friendly web interface. Through both a series of internal verification tests and usability

testing, this project will result in an accurate and verified cloud-based simulation tool for the medical device sterilization market.