An Optimal Time for Treatment-Predicting Circadian Time by Machine Learning and Mathematical Modelling.

ABSTRACT: Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient's internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals,

SUBMITTER: Hesse J 

PROVIDER: S-EPMC7690897 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature