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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. While previous efforts focused on pharmaceuticals and recovery agents to physiological insults, new BioGears efforts seek to model the negative physiology responses to chemical agents. 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 either Cyanides or Pulmonary Agents. This project would include components of research, mathematical modeling, integration, and testing.
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. 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 come in, 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, mathematical modeling, integration, and testing.
In today’s pandemic climate, BioGears is shifting gears (haha get it) and expanding its focus of bodily responses to external substances and threats. BioGears’ expanded whole blood model and substance transporter have proven effective and modular regarding chemical substances 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 oral drug delivery system for toxin inhalation; however, the primary focus of this project is on implementing the toxin physiological reactions and validating the results against clinical data.
BioGears currently utilizes a burn model based on (insert reference here). Implementation of a burn in the engine requires an input of body location and total body surface area burned. The model uses these inputs with basic rule of nines calculations to affect inflammation and cardiovascular models in accordance with clinical data. BioGears then models 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.
The contributor will work with the BioGears team to create examples and documentation of bindings. 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. This will require strong knowledge of the target language to properly test the cross language dll loading. Strong software engineering skills will be used to properly develop unit test of each language binding to prove that the resulting hooks work as intended. Some tweaks will be required to the existing templates to accommodate language limitations. The selected student will work side by side our existing team to identify the required changes and develop mitigations.
##Additional ideas While the above ideas are our current teams 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.