Combination anti-coronavirus therapies based on nonlinear mathematical models
J. A. Gonzalez, Z. Akhtar, D. Andrews, S. Jimenez, L. Maldonado, T., Oceguera, I. Rondon, O. Sotolongo-Costa
TL;DR
This paper develops nonlinear mathematical models combined with experimental data to design new combination therapies for COVID-19, aiming to improve treatment effectiveness.
Contribution
It introduces a novel approach integrating nonlinear modeling with experimental data to optimize COVID-19 combination therapies.
Findings
Proposed new combination therapy strategies.
Validated models with laboratory and clinical data.
Potential for improved COVID-19 treatment outcomes.
Abstract
Using nonlinear mathematical models and experimental data from laboratory and clinical studies, we have designed new combination therapies against COVID-19.
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