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Regulatory Science Tools Catalog

The Regulatory Science Tools Catalog provides a peer-reviewed resource for use where standards and qualified Medical Device Development Tools (MDDTs) do not yet exist. These tools do not replace FDA-recognized standards or MDDTs. This catalog collates a variety of regulatory science tools that the FDA's Center for Devices and Radiological Health's (CDRH) Office of Science and Engineering Labs (OSEL) developed. If you are considering using a tool from this catalog in your marketing submissions, note that these tools have not been qualified as Medical Device Development Tools and the FDA has not evaluated the suitability of these tools within any specific context of use. You may request feedback or meetings for medical device submissions as part of the Q-Submission Program.


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This regulatory science tool presents Python-based software for evaluating computer models that predict the number of COVID-19 deaths or hospitalizations expected in a specific locality.
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This regulatory science tool presents a method for assessing credibility of patient-specific computational models implemented in medical device software. 
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A series of benchmark problems with known exact solutions that can be used to verify if tissue-level (e.g., ventricular, atrial) computational models of cardiac electrophysiology have been implemented correctly
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This study demonstrates the application of gold-standard method of manufactured solutions (MMS) code verification to verify a commercial finite element code for elastostatic solid mechanics analyses relevant to medical devices. The Python/SymPy code used to generate source terms is available as supplemental material.
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A finite element model of the human shoulder for simulating humeral abduction and calculating outputs such as contact force, contact pressure, contact area, stress, and strain.
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A "threshold-based" validation approach that provides a well-defined acceptance criterion, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity.