Investigators
Dr. Souvik Roy, Dr. Suvra Pal, Dr. Richard Medford
Contact info (email)
souvik.roy@uta.edu
1. Define context(s)
aid in clinical decision making
identify/explore new therapies
reveal new biological insights
Current Conformance Level / Target Conformance Level
Adequate
Primary goal of the model/tool/database
The main goal of this project is to develop a software based on a novel mathematical framework that uses individual COVID-19 patient data to obtain accurate personalized treatment strategies. We aim to achieve this goal using an extensive pharmacokinetic model building, an optimal control approach for parameter estimation, and tools from statistical sensitivity analysis to devise new and efficient treatment strategies. Our proposed framework will be highly beneficial for health professionals to make fast and accurate decisions about treatment strategies, without the need for numerous clinical trials, thereby assisting the world in its fight against COVID-19.
Biological domain of the model
Infectious diseases (COVID-19)
Structure(s) of interest in the model
Respiratory system
Spatial scales included in the model
10^-6 to 10^-4 metres
Time scales included in the model
1 to 30 days, depending on the patient data.
Other uses for the model (optional)
Our model can be used by clinicians to assess fast and accurate treatments for a large class of infectious diseases besides COVID-19.
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.) | ||||
| ex vivo (excised tissues) | ||||
| in vivo pre-clinical (lower-level organism or small animal) | ||||
| in vivo pre-clinical (large animal) | ||||
| Human subjects/clinical | Yes | Deidentified individual COVID-19 patient gene expression data is available | Peer-reviewed and published data | Adequate |
| 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.) | ||||
| ex vivo (excised tissues) | ||||
| in vivo pre-clinical (lower-level organism or small animal) | ||||
| in vivo pre-clinical (large animal) | ||||
| Human subjects/clinical | Yes | Deidentified individual COVID-19 patient gene expression data is available | Peer-reviewed and published data | Adequate |
| Other: ________________________ |
3. Validate within context(s)
| Who does it? | When does it happen? | How is it done? | Current Conformance Level / Target Conformance Level | |
|---|---|---|---|---|
| Verification | Project research team | Throughout development of the software with an independent peer-review prior to release | There is an assessment of software risk and line by line review and global testing to insure code meets conceptual implementation | Extensive |
| Validation | Developers and end-users will perform the validation | Throughout the development of the software | 3-fold cross validation technique will be performed and FDR rates will be calculated to assess accuracy. An FDR < 20% will imply that the model is validated. | Extensive |
| Uncertainty quantification | the model is designed to propagate uncertainty, so this requirement is met by virtue of the model development and application | Every time the model is run for a new scenario | Normalization of data to remove noise and optimal control approach for robustness. | Extensive |
| Sensitivity analysis | Dr Suvra Pal | Once the optimal parameters are obtained | Through Latin Hypercube Sampling and Partial Rank Correlation Coefficient | 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 |
|---|---|---|---|
| The pharmacokinetic differential equation model represents spread of virus in a diffusive way. Other forms of spread are not taken into account because of their rare occurrence. However, for some patients, other types of virus spreads can happen. | Clinicians, health professionals and health researchers. | 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 |
|---|
| Extensive |
| Naming Conventions? | Repository? | Code Review? | |
|---|---|---|---|
| individual modeler | Yes | GITHUB | Yes |
| within the lab | N.A. | N.A. | N.A. |
| collaborators | No | GITHUB | Yes |
6. Documentation
| Current Conformance Level / Target Conformance Level | |
|---|---|
| Code commented? | Extensive: Each part of the code will be commented in detail |
| Scope and intended use described? | Extensive: Supporting material in publications |
| User’s guide? | Adequate |
| Developer’s guide? | Partial: No, there is a concept document and a software design document |
7. Dissemination
| Current Conformance Level / Target Conformance Level |
|---|
| Extensive |
| Target Audience(s): | “Inner circle” | Scientific community | Public |
|---|---|---|---|
| Simulations | Through peer-reviewed publications | ||
| Models | Through peer-reviewed publications | GITHUB | |
| Software | GITHUB | GITHUB | |
| Results | Through peer-reviewed publications | Scientific articles, news, social media, GITHUB | |
| Implications of results | Scientific articles, news, social media, GITHUB |
8. Independent reviews
| Current Conformance Level / Target Conformance Level |
|---|
| Insufficient |
| Reviewer(s) name & affiliation: | To be done |
|---|---|
| When was review performed? | To be done |
| How was review performed and outcomes of the review? | N.A. |
9. Test competing implementations
| Current Conformance Level / Target Conformance Level |
|---|
| Insufficient |
| Yes or No (briefly summarize) | |
|---|---|
| Were competing implementations tested? | To be done |
| Did this lead to model refinement or improvement? | To be done |
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? | |
| How do your modeling efforts conform? | We meet all documentation, programming and credibility standards as confirmed by independent assessment by users. |
Our model is specifically designed to analyze gene expression data from patients suffering from COVID-19.