# Consortium for Viral Systems Biology Modeling Core

> **NIH NIH U19** · SCRIPPS RESEARCH INSTITUTE, THE · 2020 · $299,700

## Abstract

Project Summary/Abstract
The Modeling Core targets the development, validation and reﬁnement of models to predict pathogen genetic
and host immune response and physiological features affecting viral hemorrhagic fever survival and long-term
sequelae of Lassa virus (LASV) and Ebola virus (EBOV) infection. Our multidisciplinary team carries expertise
across statistical thinking, mathematical modeling, evolutionary biology and computing to leverage sequenc-
ing, immunological proﬁling, mobile sensor and clinical data. We provide to the Consortium for Viral Systems
Biology Cores and Projects guidance in phylogenetic reconstruction to deﬁne evolutionary trajectories and
cataloguing LASV and EBOV intra-host variants, genetic association studies mapping host determinants and,
importantly, consultation on all statistical aspects of experimental design in the Projects. Our chief innova-
tions are three-fold. First, we incorporate viral sequence evolution into predictive survival models through
the development of phylogenetic survival analysis to uncover the viral and host genetic determinants of host
time-to-event health outcomes while appropriately controlling for shared evolutionary history and incorporat-
ing adaptive immunity repertoire development. We integrate large-scale non-omics data into these survival
models using advancing computing technology to include time-dependent immunological and physiological
features arising from wireless patient monitors and clinical tests. Third, we exploit systems-level prediction
evaluation and reﬁnement for iterative model building with internal validation, biological experimentation and
network analysis. The Core will deliver effective analysis tools enabled for real-time and scriptable use in open-
source, reproducible research and will marshall both hands-on short-courses and a regular virtual quantitative
clinic to catalyze the interactions between modeling and experimentation.

## Key facts

- **NIH application ID:** 9851805
- **Project number:** 5U19AI135995-03
- **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE
- **Principal Investigator:** Marc A. Suchard
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $299,700
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9851805

## Citation

> US National Institutes of Health, RePORTER application 9851805, Consortium for Viral Systems Biology Modeling Core (5U19AI135995-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9851805. Licensed CC0.

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