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Ideas List
Substances, including drugs, gases, and hormones, are transported through the body within the bloodstream and airflow in the Cardiovascular and Respiratory Systems, respectively. This provides important nutrients and waste removal for normal physiologic function. Some of BioGears most successful efforts focus on pharmaceuticals and recovery agents to physiological insults, aka medical countermeasures. New BioGears efforts seek to model the negative physiology responses to chemical agents and the medical countermeasures that can be used based on the time response of diagnosis. The first implemented Chemical, Biological, Radioactive, Nuclear (CBRN) agent implemented was a nerve agent, Sarin. We want a contributor to come in and use the existing relevant foundation to expand the CBRN agent classes supported by BioGears to include mustard or another proposed agent through proper coding implementation of input and response variables. This project would include components of research (10%), mathematical modeling (25%), integration (25%), and testing/refining (40%).
When BioGears is used to model physiological insults, it is important to accurately model the full bodily response so that interventions can be implemented appropriately. Medical countermeasure simulations are limited by the effectiveness of the underlying injury/disease state models. BioGears currently has implementation for Sarin, a nerve agent. The physiologically relevant biomarkers associated with nerve agents are pupillary response, cardiovascular function, respiratory function, and nicotinic/muscarinic responses. While BioGears currently supports some of these physiological responses, we are looking for a contributor to research the most common and medically relevant responses not yet implemented (i.e., seizure response), and refine the Sarin response model. This project would include components of research (15%), mathematical modeling (25%), integration (20%), and testing/refining (40%).
In today’s pandemic climate, BioGears is shifting gears (haha get it) and expanding its focus of bodily responses to external substances and threats to increase its relevance in preventative medical simulations. BioGears’ expanded whole blood model and substance transporter have proven effective and modular regarding both chemical substances and cellular proliferation making the next logical step implementing biological toxins (starting with anthrax). Current BioGears models may be utilized as is or with modifications to help in new model implementation, such as the negative antigen interactions in the bloodstream; however, the primary focus of this project is on implementing the appropriate time response of the toxin physiological reactions and validating the results against clinical data. This project would include components of research (20%), mathematical modeling (20%), integration (30%), and testing/refining (30%).
BioGears currently implements burn wounds in the engine as a function of bodily location and total body surface area (TBSA) burned. Current published work regarding this model can be found at https://ieeexplore.ieee.org/abstract/document/8857686. Using basic burn triaging rule of nines calculations (a method of estimating tbsa), BioGears simulates inflammation and cardiovascular/respiratory distress in accordance with clinical data. BioGears then models medical countermeasures such as burn resuscitation through injection of fluids and other medical care inputs. However, when looking at burn triaging, we noticed the model works much more efficiently at lower burn percentages. We would like a contributor to bring ideas for either a refined burn effect model or a refined fluid resuscitation model to handle burns specifically in the 25-35 percent TBSA range. This project would include components of research (10%), mathematical modeling (25%), integration (25%), and testing/refining (40%).
To expand accessibility, the BioGears the team would like to see Python available natively in Python and Rust. Our existing SWIG based language bindings for C# need testing when targeting Python and Rust output languages. A candidate may choose to work on one or both target languages, they will work with the BioGears team to become familiar with our existing templates and modify them as required by the target language. This project will require strong software engineering and communication skills to develop a suite of unit test to run against each binding. Our team will work with the candidate to provide examples of how each binding is used in its native language and suggest directions for the swig template modifications. As each language has its own capabilities and limitations some target specific modifications will be needed to work around each languages personality. This opportunity is ideal for any engineering focused candidate and requires little prior knowledge to the physiology domain of the BioGears project. The selected student will work side by side our existing team to identify the required changes and develop mitigations. This project would include components of research (20%), mathematical modeling (0%), integration/development (40%), and testing/refining (40%).
While the above ideas are our current team's priorities all Enhancement issues on https://github.com/BioGearsEngine/core/issues can be reviewed for submission and would be considered given a strong enough submission.