Engineering Therapies that Evolve to Autonomously Control Epidemics

Abstract

The overarching aim of our seedling effort was to de-risk the idea that viruses could be engineered into therapeutics, known as Therapeutic Interfering Particles (TIPs), using the virus HIV as a model system. By engineering TIP prototypes that were shown to reduce HIV levels >10X in cell-culturewhile having no effect on the viability of healthy, uninfected cellswe directly achieved this aim (Aim I of our proposal). The secondary aim (Aim II) of the proposal was to demonstrate, via mathematical modeling, that engineered TIPs could have indefinite, population-scale impact. To achieve this aim, we developed novel multi-scale models that connected the measured within-cell TIP dynamics achieved in Aim I with the predicted population-scale impact of these TIP prototypes on HIV prevalence levels. We further calculated cellular design constraints (e.g., genomic RNA expression levels) to guide the development of TIPs with predicted population-scale efficacy. Finally, we demonstrated the evolutionary robustness of TIPs against a key route of HIV mutational escape. Our modeling results de-risking the TIP approach were published in PLoS Computational Biology this past year.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2017
Accession Number
AD1034864

Entities

People

  • Leor S Weinberger

Organizations

  • The J. David Gladstone Institutes

Tags

DTIC Thesaurus Topics

  • Computational Biology
  • Dynamics
  • Engineering
  • Epidemics
  • Models
  • Multiscale Models
  • Particles
  • Plant Structures
  • Prototypes
  • Scale Models
  • Therapy
  • Viability

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Infectious Disease/Epidemiology
  • Molecular Genetics