Personalized oncology with artificial intelligence: The case of temozolomide

作者：

Highlights：

• We use MTCS algorithms to optimize drug regimen in oncology.

• We show how adding Bayesian updating allows to dynamically personalize treatment.

• Optimal personalized protocols achieve very sizable decrease in tumor size.

• These better efficacy results are obtained with no toxicity increase.

摘要

•We use MTCS algorithms to optimize drug regimen in oncology.•We show how adding Bayesian updating allows to dynamically personalize treatment.•Optimal personalized protocols achieve very sizable decrease in tumor size.•These better efficacy results are obtained with no toxicity increase.

论文关键词：Pharmacokinetics,Pharmacodynamics,Optimization,Personalized oncology,Artificial intelligence

论文评审过程：Received 1 March 2018, Revised 9 July 2019, Accepted 9 July 2019, Available online 12 August 2019, Version of Record 19 August 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.07.001