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Ideas List
Note: all projects can be scaled for either a 175 or 350 hour project based on use of current models and idea scope. We recommend reaching out to the current BioGears team via their slack channel and openly discussing ideas during proposal submission regarding which is a better fit for your goals, ideas, and availability.
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 and Biological (CB) agent implemented was a nerve agent, Sarin. We want a contributor to come in and use the existing relevant foundation to expand the CB agent classes supported by BioGears to include mustard or another proposed agent through proper coding implementation of input and response variables. The selected contributor will work side by side our existing team to identify the required changes and develop mitigations. This project would include components of research (10%), mathematical modeling (25%), integration (25%), and testing/refining (40%). The expected outcomes from this project would be a new substance file added to the BioGears substance library with appropriate physiological response tuning and validation. Additionally, we expect at least one new validation scenario added to our substance validation protocols to track the new additions in future simulation testing. This project is good for less experienced coders and engineers, particularly those with an interest in the biological field. Possible mentors for this project include Nathan Tatum, Austin Baird, Steven White and Ashley McGuirk.
Overall Rating: Easy
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. The selected contributor will work side by side our existing team to identify the required changes and develop mitigations. This project would include components of research (15%), mathematical modeling (25%), integration (20%), and testing/refining (40%). The expected outcomes from this project would be an integrated physiological response, including validation testing as it pertains to both an individual response or as part of a larger physiological problem. As such, we expect at least one new validation scenario added to our validation protocols to track the new additions in future simulation testing. This project will also require a higher focus on system verification to ensure model updates do not negatively impact other models. Required skills for this project include mathematical modeling, coding in C++, and an interest in biological applications. Possible mentors for this project include Nathan Tatum, Austin Baird, and Ashley McGuirk.
Overall Rating: Medium
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 or plague). 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. The selected contributor 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 (20%), integration (30%), and testing/refining (30%).The expected outcomes from this project would be modified substance files with relevant input based on research of the approved biological agent, a new substance file added to the BioGears substance library with appropriate physiological response tuning, and extensive validation based on clinical physiological response curves and any model additions' impact on the engine as a whole. We also expect at least one new validation scenario added to our validation protocols to track the new additions in future simulation testing. This project is requires someone who is both an experienced researcher and coder/engineer, who will be working in multiple parts of the code base and potentially modifying code in each of python, c++, and/or xsd files. We prefer a candidate with an interest in the biological field. Possible mentors for this project include Nathan Tatum and Ashley McGuirk.
Overall Rating: Hard
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. Proposed projects can include a number of factors not yet accounted for and if this project interests you, we encourage you to reach out to learn more about the existing model. The selected contributor will work side by side our existing team to identify the required changes and develop mitigations. This project would include components of research (10%), mathematical modeling (25%), integration (25%), and testing/refining (40%). The expected outcomes from this project would be updates to the existing burn model that extend validation capabilities to at least 35% TBSA. We will look for the candidate to rerun existing validation to make sure the current working range is unaffected. Finally, we expect at least one new validation scenario added to our validation protocols to track the new additions in future simulation testing. This project would require some moderate coding knowledge and the ability to work well with others, as it will require collaboration to understand and manipulate existing code. We would also prefer someone with an interest or some knowledge of biology, as it will assist in understanding the biological effect models in place. Possible mentors for this project include Nathan Tatum, Austin Baird, and Steven White.
Overall Rating: Medium
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, at which point 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 tests 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 language's personality. This opportunity is ideal for any engineering/developer focused candidate and requires little prior knowledge to the physiology domain of the BioGears project. The selected contributor 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%).
The expected outcomes of this project would be.
- New CMake targets in BioGears for generating the choice languages bindings
- A libBiogears_ dynamic library with the compiled bindings
- An additional folder in the outputs directory which includes the swig generated language files.
- A new test application in the target language which demonstrates how to use the bindings to act as a tutorial for end users.
Some skills required to complete this would be understanding of build systems. Strong understanding of the target language and its runtime environment. Ability to communicate work progress with the core team. Also, we would prefer someone with an understanding of C++ and the CMake build system. Prior CMake experience is not required, but will simplify the kickoff process of the project most candidates will need to learn the SWIG meta template language as they are working on the project. Possible mentors for this project include Austin Baird and Steven White.
Overall Rating: Medium
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.