Evolutionary Antifragile Therapy Is a Treatment Strategy to Suppress Drug Resistance by Exploiting Dose–Response Convexity

A population of cells within a tumor can be described as antifragile (the opposite of fragile) if they derive a benefit from fluctuations or perturbations in environmental conditions induced by treatment. Treatment fluctuations could either promote (antifragile tumor) or inhibit (fragile tumor) the evolution of treatment resistance to targeted therapies. In this study, we showed that analysis of the convexity of dose-response curves provided a direct prediction of response to prescribed fluctuations in treatment. Convexity predicted that continuous treatment protocols (i.e., zero prescribed fluctuations in treatment) would outperform uneven protocols when dose response is convex. This theory was applied to predict in vivo response to targeted therapy, and the predictions were validated by experimentally testing high/low intermittent dosing (uneven dosing) and continuous dosing (even dosing) schedules. Convexity (and its inverse, concavity) explained 2 phenomena: Dose response is a convex (fragile) function, but the resistance onset rate is a concave (antifragile) function. Thus, design and validation of alternative treatment schedules maximized response while maintaining prolonged sensitivity to treatment. Together, these analyses provide supporting evidence that fluctuations alter the evolutionary trajectory of tumors in response to targeted therapy, even without altering the cumulative dose. By using this insight to design alternative treatment protocols to limit the evolution of resistance by careful analysis of the dose-response curvature, the study supports the potential of "evolutionary antifragile therapy" as a subtype in the broad class of evolution-based treatment strategies. SIGNIFICANCE: The mathematical method using dose response curvature to determine appropriate treatment dosing that limits the evolution of resistance could facilitate designing dose schedules that optimize tumor response. See related commentary by Pomeroy and Palmer, p. 4195.