Abstract

We use published data in order to build up a networked mathematical framework aiming at providing: (a) a predictive understanding on how distinct stressors and immunosenescence may potentially affect the natural inflammatory response mechanisms and (b) new insights to developing early interventions that seek to exploit natural immune processes. Relying on fifty fundamental assumptions on HIV immunopathogenesis, the model simulations suggested that: (a) from a translational perspective, forthcoming physiological transitions in the systemic inflammation process do exist with conditions for bifurcation between the uninfected and the infected state being seriously impacted by immunomodulation and (b) the required therapy efficacy for pre-exposure prophylaxis may be decisively affected by immunomodulation and by the drug class used. Whereas unsuitable to make quantitative predictions due to limited experimental data and the complexity in vivo, this modeling effort paves the way for assessing the impact of personalized medicine for global epidemics within complex systems thinking.

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