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. 2010 Aug 12;6(8):e1000883. doi: 10.1371/journal.pcbi.1000883

Figure 4. Quantitative evaluation of treatment strategies investigated in this study.

Figure 4

Each point summarizes the average outcome of 500 simulations with default parameter values (see the Methods section). The blue curves correspond to a standard use of a single gene therapy (discussed in subsection “Emergence and Fixation of Resistant Mutants”). The red curves correspond to a combination-therapy strategy whereby the P cells are divided into two sub-populations, each protected by a distinct set of genes (discussed in subsection “Divide and Conquer – an Effective Strategy to Combat Resistance”). (A) Effects of increasingly larger genetic barriers n (x-axis) on the fraction of successful treatments (y-axis), featuring a threshold-like behavior. A treatment is considered successful if mutant fixation did not occur within four years after its initiation at day 0. (B) Effects of increasingly larger genetic barriers n (x-axis) on the average time to fixation (y-axis), which is the time required for the resistant strains to reach 50% of the viral population. Data are depicted only in cases where the success rates are below 0.9, representing at least 50 fixation events per point. (C) Effects of increasingly larger genetic barriers n (x-axis) on the average viral reduction at the time of fixation (y-axis), depicted when success rates are below 0.9. The viral reduction is the ratio between the viral loads at fixation time and at day 0. Large genetic barriers are needed in order for the therapy to reach its set point before resistance emerges. (A,B,C) Viral suppression under the two-therapy regimen is gradually prolonged throughout the entire barrier range, and displays a dramatic advantage at Inline graphic (B). Success rates and viral reduction are also improved (A,C).