Multiscale Modeling and Viral Pandemics
Modeling Individual Responses to Disease and Treatment
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Gary An, email@example.com
Tarunendu Mapder, firstname.lastname@example.org
Elissa Schwartz, email@example.com
Methods for Modeling Inter-Individual Variability and Individual Responses to Viral Infections
The emergence and impact of various viral pandemics in the past decades (SARS-COV1, MERS, H1N1, Zika, Dengue and, most recently and widely, SARS-COV2) has highlighted the importance of enhancing the efficiency of disease characterization/classification and therapy discovery/development/testing in order to more rapidly respond to these global threats. Multi-scale modeling (MSM) holds the promise of being able to facilitate the acceleration of these tasks, but one of the persistent challenges in the translational use of MSM is reconciling the complexity of these models with the range of individual responses in both experimental and clinical populations, producing heterogeneous and variable data that needs to be accounted for by those models. In fact, the variation of biological behaviors within clinical populations is a key stumbling block in the translation or basic science mechanistic knowledge (and the potential therapies thus generated) and clinical efficacy. Rather than a barrier to the use of MSMs, we suggest that there are specific properties of MSMs that, if utilized appropriately, can help unify and reconcile inter-individual variation and variability and enhance the translational development of robust diagnostics and therapeutics.
The overarching goal of the Modeling Inter-Individual Variability and Individual Responses (henceforth shorted to “Modeling Individual Reponses”) Working Subgroup is to focus on developing cross-cutting methods and approaches that the wider modeling community (including other entity-focused Working Groups) can utilize in their simulation experiments. Central to this is the ability to represent inter-individual/intra-group heterogeneity across a range of multi-scale modeling methods and enhancing the ability to simulate experimental and clinical populations with a translational goal. Moreover, this group aims to annotate and build a platform of generic (viral and/or bacterial infection) methodologies that is able to help the other WSGs in tracing the disease prognoses and therapeutic responses. It will also provide flexible frameworks towards simulating and analyzing virtual patient cohorts and in silico clinical trials. The Modeling Individual Response WSG aims to provide a reference list and potential repository for different such methods to serve as a resource for members of the MSM community. These methods include, but are not limited to: statistical methods, mixed effect modeling, quantification of inter-individual variability (e.g. parameter sensitivity analysis), parameter space exploration/characterization, machine learning/active learning/evolutionary computation.
- Identify people working in this area to include a paragraph on their work. (Target for February 28, 2021)
- Recruit members (assemble the masses)
- Assemble into a directory of researchers. (bibliography for subgroup)
- Identify other subgroups that you should coordinate with
- Prepare a white paper, approx. 5pp in length, excluding references that does the following: (Target for May 31, 2021)
- Describe the focus of the subgroup, the major problems within it, and the role modeling can play in it
- Describe what models and data are available, and the extent of our biological knowledge, available experimental systems, etc.
- Describe what is needed that does not exist yet: models, data, experimental approaches, etc.
- Outline any action items that could get us there.
- These white papers can form the basis of a collective publication on the topic of multi scale modeling and viral pandemics.
- Catalyze research projects through presentations, exchange of ideas, search for strategic opportunities. (Target for August 30, 2021)
|Guillaume Le Treut|
|Carlos F Lopez|
Group Activities and Schedule:
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