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Abstract
Recent clinical trials have shown that adaptive drug therapies can be more efficient than a standard cancer treatment based on a continuous use of maximum tolerated doses (MTD). The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are administered based on the current state of tumour. But the adaptive treatment policies examined so far have been largely ad hoc. We propose a method for systematically optimizing adaptive policies based on an evolutionary game theory model of cancer dynamics. Given a set of treatment objectives, we use the framework of dynamic programming to find the optimal treatment strategies. In particular, we optimize the total drug usage and time to recovery by solving a Hamilton-Jacobi-Bellman equation. We compare MTD-based treatment strategy with optimal adaptive treatment policies and show that the latter can significantly decrease the total amount of drugs prescribed while also increasing the fraction of initial tumour states from which the recovery is possible. We conclude that the use of optimal control theory to improve adaptive policies is a promising concept in cancer treatment and should be integrated into clinical trial design.
Highlights
Intratumoural heterogeneity is increasingly recognized as a cause of metastasis, progression and resistance to therapy [1]
In addition to the toxicity, it is known that relapse is nearly inevitable due to the emergence of therapeutic resistance: a process driven by Darwinian evolutionary dynamics in which the maximum tolerated doses (MTD)-based chemotherapy kills off the chemotherapy-sensitive cells, and chemo-refractory cells eventually dominate in the tumour
We focus on an optimal control problem summarized in box 2 and based on the example considered in the therapeutic implications section of Kaznatcheev et al [20]
Summary
Intratumoural heterogeneity is increasingly recognized as a cause of metastasis, progression and resistance to therapy [1]. In addition to the toxicity, it is known that relapse is nearly inevitable due to the emergence of therapeutic resistance: a process driven by Darwinian evolutionary dynamics in which the MTD-based chemotherapy kills off the chemotherapy-sensitive cells, and chemo-refractory cells eventually dominate in the tumour. While it is unknown whether these resistant cells are present before therapy or acquire resistance mutations during therapy, it is the process of variation and selection under standard therapy that drives the inevitable failure in the patient
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