scholarly journals Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory

2018 ◽  
Author(s):  
Mark Gluzman ◽  
Jacob G. Scott ◽  
Alexander Vladimirsky
Keyword(s):  
Game Theory ◽  
Dynamic Programming ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Theory Model ◽  
Optimal Treatment ◽  
Tumor Evolution ◽  
Trade Offs ◽  
Adaptive Therapy

Recent clinical trials have shown that the adaptive drug therapy can be more efficient than a standard MTD-based policy in treatment of cancer patients. The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are administered based on the current state of tumor. But the adaptive treatment policies examined so far have been largely ad hoc. In this paper we propose a method for systematically optimizing the rules of 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 based on a mathematical model of tumor evolution. We compare adaptive/optimal treatment strategy with MTD-based treatment policy. We show that optimal treatment strategies can dramatically decrease the total amount of drugs prescribed as well as increase the fraction of initial tumour states from which the recovery is possible. We also examine the optimization trade-offs between the total administered drugs and recovery time. The adaptive therapy combined with optimal control theory is a promising concept in the cancer treatment and should be integrated into clinical trial design.

scholarly journals Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory

2020 ◽  
Vol 287 (1925) ◽  
pp. 20192454 ◽  
Author(s):  
Mark Gluzman ◽  
Jacob G. Scott ◽  
Alexander Vladimirsky
Keyword(s):  
Game Theory ◽  
Dynamic Programming ◽  
Cancer Treatment ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Theory Model ◽  
Adaptive Treatment ◽  
Adaptive Policies ◽  
Treatment Policies

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.

scholarly journals Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations

2014 ◽  
Vol 4 (4) ◽  
pp. 20140037 ◽  
Author(s):  
David Liao ◽  
Thea D. Tlsty
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Dynamics ◽  
Evolutionary Game ◽  
Treatment Strategies ◽  
Analysis Method ◽  
Analysis Techniques ◽  
Game Theoretic ◽  
And Control

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

Research on Opportunistic Behavior in Energy Security Cooperation of China and Japan

2011 ◽  
Vol 71-78 ◽  
pp. 2085-2088
Author(s):  
Chun Chu ◽  
De Shan Tang
Keyword(s):  
Game Theory ◽  
Behavior Analysis ◽  
Evolutionary Game Theory ◽  
Energy Security ◽  
Evolutionary Game ◽  
Theory Model ◽  
Opportunistic Behavior ◽  
Security Cooperation ◽  
Energy Cooperation ◽  
China And Japan

Analyze the opportunistic behavior between China and Japan in energy security cooperation with game theory. There are two types countries in the process of the cooperation, they are opportunistic and cooperating countries. To use of evolutionary game theory model of cooperation and energy cooperation between China and Japan in the opportunistic behavior analysis, the results show that under certain conditions, cooperation can be avoided the incidence of opportunistic behavior, if not satisfy the relevant constraints, the co-operation will inevitably.

scholarly journals Production-Use Water Pricing and Corporate Water Use in China: An Evolutionary Game Theory Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yao Xiao ◽  
Qiao Peng ◽  
Wanting Xu ◽  
Hongye Xiao
Keyword(s):  
Game Theory ◽  
Water Supply ◽  
Evolutionary Game Theory ◽  
Water Conservation ◽  
Local Governments ◽  
Evolutionary Game ◽  
Developed Countries ◽  
Policy Formulation ◽  
Theory Model ◽  
Water Pricing

Decisions related to pricing production-use water are a critical issue that local governments in China are facing. Its significance has increased in recent years, as a serious corporate water-supply shortage has surfaced with rapid economic development and urbanization. Different from developed countries, the pricing of production-use water is a complex issue in China that involves the distribution of benefits among local governments, water-supply companies, and water-consuming companies, where the overall balance is affected by every slight adjustment. Based on the evolutionary game theory, this study constructs an evolutionary game model involving water-supply companies and water-consuming companies with a systematic analysis of the interaction process between the policy formulation related to water pricing by water-supply companies and the decision making related to water consumption by water-consuming companies. The research finds that the difficulty of balancing corporate financial benefits and public water conservation benefits has led to the complexity of water pricing. Moreover, raising water prices will not necessarily cause companies to save water, but it will increase the production cost of the entire economy. This is the direct cause of low water prices, implemented by water-supply companies, in many regions of China.

scholarly journals The social evolution of genocide across time and geographic space: Perspectives from evolutionary game theory

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Charles H. Anderton
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Social Evolution ◽  
Evolutionary Game ◽  
Theory Model ◽  
Geographic Space ◽  
Policy Interventions ◽  
The Social ◽  
The Holocaust ◽  
Moore Neighborhood

A standard evolutionary game theory model is used to reveal the interpersonal and geographic characteristics of a population that make it vulnerable to accepting the genocidal aims of political leaders. Under conditions identified in the space-less version of the model, genocide architects can engineer the social metamorphosis of a peaceful people-group into one that supports, or does not resist, the architects’ atrocity goals. The model reveals policy interventions that prevent the social evolution of genocide among the population. The model is then extended into geographic space by analyzing interactions among peaceful and aggressive phenotypes in a Moore neighborhood. Key concepts of the analyses are applied to the onset and spread of genocide during the Holocaust (1938-1945) and to the prevention of genocide in Côte d'Ivoire (2011). [JEL codes: C73, D74]

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