Example where low-dose strategy best prevents the emergence of resistance.

<p>(a) The dose-response curves for the wild type in blue (<i>r</i>(<i>c</i>) = 0.6(1−tanh(15(<i>c</i>−0.3)))) and the resistant strain in red (<i>r</i>_<i>m</i>(<i>c</i>) = 0.59(1−tanh(15(<i>c</i>−0.6)))) as well as the therapeutic window in green. Red dots indicate the probability of resistance emergence. Probability of resistance emergence is defined as the fraction of 5000 simulations for which resistance reached a density of at least 100 (and thus caused disease).(b) and (c) wild type density (blue), resistant density (red), and immune molecule density (black) during infection for 1000 representative realizations of a stochastic implementation of the model. (b) treatment at the smallest effective dose <i>c</i>_<i>L</i>, (c) treatment at the maximum tolerable dose <i>c</i>_<i>U</i>. (d) The probability that a resistant strain appears by mutation is indicated by grey bars for low and high dose. The probability of resistance emergence is indicated by the height of the red bars for these cases. The probability of resistance emergence, given a resistant strain appeared by mutation, can be interpreted as the ratio of the red to grey bars. Parameter values are <i>P</i>(0) = 10, <i>P</i>_<i>m</i>(0) = 0, <i>I</i>(0) = 2, <i>α</i> = 0.05, <i>δ</i> = 0.05, <i>κ</i> = 0.075, <i>μ</i> = 10⁻², and <i>γ</i> = 0.01.