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In previous work, we have developed optimal-control based approaches that seek to minimize the risk of subsequent virological failure by "pre-conditioning" the viral load during therapy switches. In this paper, we use Monte-Carlo methods to evaluate the sensitivity of an open-loop implementation of these approaches to modeling errors. To account for hidden parameter dependencies, we use parameter distributions obtained from the convergence of Bayesian parameter estimation techniques applied topmid:24954972 pmcid:PMC4061758 fatcat:vmtmvxfxijfylorgedgkzdo2nu