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Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs

Journal

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/1742-4682-11-41

Keywords

Antiviral therapy; Mathematical modeling; Drug combination theory; Virus dynamics

Funding

  1. Japan Society for the Promotion of Science (JSPS) [B25800092]
  2. Kyushu University Interdisciplinary Programs in Education and Projects in Research Development
  3. Aihara Innovative Mathematical Modeling Project, JSPS through the Funding Program for World-Leading Innovative R & D on Science and Technology (FIRST program)
  4. Council for Science and Technology Policy
  5. Grants-in-Aid for Scientific Research [26287025] Funding Source: KAKEN

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In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

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