Investigators
Chuck Alan Dorval, Kathleen Lamkin-Kennard, Mingchen Gao, Daniel DiLorenzo, Guillaume de Lartigue, Jennifer Blain Christen
Contact info (email)
chuck.dorval@utah.edu
1. Define context(s)
aid in clinical decision making
aid in clinical trial design
identify/explore new therapies
reveal new biological insights
Current Conformance Level / Target Conformance Level
Comprehensive
Primary goal of the model/tool/database
Inflammatory bowel disease (IBD) is an idiopathic disease caused by a dysregulated microbiome and immune response. By activating anti-inflammatory vagal-specific mechanisms, vagal nerve stimulation (VNS) may be therapeutic for IBD, but optimal stimulation parameters vary by disease and remain poorly understood. We propose to develop patient-specific simulations that can be used to predict disease specific parameters and that can be used to understand and optimize vagal nerve stimulation parameters. The model will consist of ML algorithms coupled to mechanistic models of the colonic and neuronal environments.
Biological domain of the model
Colonic Inflammation
Structure(s) of interest in the model
Gut, colon, nervous system, spinal cord
Spatial scales included in the model
10^-6 to 10^1 m
Time scales included in the model
10^-3 to 10^5 sec
2. Data for building and validating the model
| Data for building the model | Published? | Private? | How is credibility checked? | Current Conformance Level / Target Conformance Level |
|---|---|---|---|---|
| in vitro (primary cells cell, lines, etc.) | Yes | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. | Extensive | |
| ex vivo (excised tissues) | ||||
| in vivo pre-clinical (lower-level organism or small animal) | Yes | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. Data should also be obtained at multiple locations, as feasible. | Extensive | |
| in vivo pre-clinical (large animal) | ||||
| Human subjects/clinical | Yes | Specific individuals are private, Averaged data is available | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. Data should also be obtained from multiple locations, as feasible. | |
| Other: ________________________ |
| Data for validating the model | Published? | Private? | How is credibility checked? | Current Conformance Level / Target Conformance Level |
|---|---|---|---|---|
| in vitro (primary cells cell, lines, etc.) | Yes | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. | Extensive | |
| ex vivo (excised tissues) | ||||
| in vivo pre-clinical (lower-level organism or small animal) | Yes | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. Data should also be obtained at multiple locations, as feasible. | Extensive | |
| in vivo pre-clinical (large animal) | ||||
| Human subjects/clinical | Yes | Specific individuals are private, Averaged data is available | The data is checked to ensure that it meets requirements for consistency, is from primary sources, and the sources are well-defined. Data should also be obtained from multiple locations, as feasible. | Extensive |
| Other: ________________________ |
3. Validate within context(s)
| Who does it? | When does it happen? | How is it done? | Current Conformance Level / Target Conformance Level | |
|---|---|---|---|---|
| Verification | Developers and end users | Throughout development | Through comparisons to known mathematical solutions. The verification is done for code segments and for the entire model. | Extensive |
| Validation | Developers and end users | Throughout development | By comparing model predictions to experimental results. A range of conditions are simulated to ensure that model can accurately predict a range of conditions. | Extensive |
| Uncertainty quantification | Developers | Throughout development, specifically when new scenarios or parameters are added | By varying key model parameters over the range of uncertainty and quantifying the propagation of effects on model outputs. This will be done for each sub-node within the model as well as for the overall model. | Extensive |
| Sensitivity analysis | Developers and end users | Throughout development, specifically when new scenarios or parameters are added | By varying key model parameters over the range of uncertainty and quantifying the the sensitivity of the model outputs to the changes in parameter values. This will be done for each sub-node within the model as well as for the overall model. Post-processing tools will be implemented to aid in these analyses. | Extensive |
| Other:__________ | ||||
| Additional Comments |
4. Limitations
| Disclaimer statement (explain key limitations) | Who needs to know about this disclaimer? | How is this disclaimer shared with that audience? | Current Conformance Level / Target Conformance Level |
|---|---|---|---|
| Portions of the model may incorporate data from multiple species and may not be broadly applicable across species. | Clinicians, researchers interfacing with the models | User Documentation. A list of limitations is provided with each report from each model run and stated in the accompanying documentation. | Extensive |
| Portions of the model may not be fully validated since the data does not exist to validate these portions of the model. | Clinicians, researchers interfacing with the models | User Documentation. A list of limitations is provided with each report from each model run and stated in the accompanying documentation. | Extensive |
| The inflammation model neglects the presence of species in mucosal layers. | Clinicians, researchers interested in interfacing with the models | User Documentation. A list of limitations is provided with each report from each model run and stated in the accompanying documentation. | Extensive |
| The spatial resolution within the lamina propria and neuronal model components is limited due to currently available data in the literature. | Clinicians, researchers interested in interfacing with the models | User Documentation. A list of limitations is provided with each report from each model run and stated in the accompanying documentation. | Extensive |
| Some baseline biomarker levels will be approximated from the literature rather than from the machine learning algorithms due to limited availability of appropriate datasets. | Clinicians, researchers interested in interfacing with the models | User Documentation. A list of limitations is provided with each report from each model run and stated in the accompanying documentation. | Extensive |
5. Version control
| Current Conformance Level / Target Conformance Level |
|---|
| Adequate |
| Naming Conventions? | Repository? | Code Review? | |
|---|---|---|---|
| individual modeler | Yes | Yes (cloud based, offsite) | Yes |
| within the lab | Yes | Yes (cloud based, offsite) | Yes |
| collaborators | Yes | Yes (cloud based, offsite) | Yes |
6. Documentation
| Current Conformance Level / Target Conformance Level | |
|---|---|
| Code commented? | Extensive - code commenting will be done in accordance with best software engineering programming practices and ISO/IEC standards |
| Scope and intended use described? | Adequate - will be documented in all user documentation and supporting material in publications |
| User’s guide? | Extensive - a thorough users guide will be created for end users. |
| Developer’s guide? | Adequate - guidance for developers will be provided through the O2S2parc platform |
7. Dissemination
| Current Conformance Level / Target Conformance Level |
|---|
| Adequate |
| Target Audience(s): | “Inner circle” | Scientific community | Public |
|---|---|---|---|
| Simulations | Extensive through O2S2parc | Adequate through O2S2parc and publications | |
| Models | Extensive through O2S2parc | Adequate through O2S2parc and publications | |
| Software | Extensive through O2S2parc | ||
| Results | Adequate through O2S2parc | Extensive through publications | Adequate through publications |
| Implications of results | Adequate through O2S2parc | Extensive through publications | Adequate through publications |
8. Independent reviews
| Current Conformance Level / Target Conformance Level |
|---|
| Adequate |
| Reviewer(s) name & affiliation: | Clinical collaborators (TBD) in the laboratory of Dr. Daniel DiLorenzo, Loma Linda University. Biomedical Engineering faculty at participating institutions (To be named) |
|---|---|
| When was review performed? | Reviews will be performed every six months as new modules are released to O2S2parc |
| How was review performed and outcomes of the review? | New modules will be tested for functionality, reliability, and accuracy. The outcomes of the reviews will be shared with all PIs and used to guide future modifications to each module. |
9. Test competing implementations
| Current Conformance Level / Target Conformance Level |
|---|
| Adequate |
| Yes or No (briefly summarize) | |
|---|---|
| Were competing implementations tested? | Competing implementations will be tested prior to release of new modules each six months. |
| Did this lead to model refinement or improvement? | We anticipate that this should lead to continuous improvement. |
10. Conform to standards
| Current Conformance Level / Target Conformance Level |
|---|
| Extensive |
| Yes or No (briefly summarize) | |
|---|---|
| Are there operating procedures, guidelines, or standards for this type of multiscale modeling? | We will adhere to O2S2parc guidelines. |
| How do your modeling efforts conform? | Independent evaluators and end users will ensure that all software and documentation is consistent with O2S2parc standards. |