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The Promising Connection Between Data Science and Evolutionary Theory in Oncology.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Goodman, Jonathan R 
Ashrafian, Hutan 

Abstract

Theoretical and empirical work over the past several decades suggests that oncogenesis and disease progression represents an evolutionary story. Despite this knowledge, current anti-resistance strategies to drugs are often managed through treating cancers as independent biological agents divorced from human activity. Yet once drug resistance to cancer treatment is understood as a product of artificial or anthropogenic rather than unconscious selection, oncologists could improve outcomes for their patients by consulting evolutionary studies of oncology prior to clinical trial and treatment plan design. In the setting of multiple cancer types, for example, a machine learning algorithm can predict the genetic changes known to be related to drug resistance. In this way, a unity between technology and theory might have practical clinical implications-and may pave the way for a new paradigm shift in medicine.

Description

Keywords

artificial intelligence, cancer control, cancer evolution, data science, evolutionary biology

Journal Title

Front Oncol

Conference Name

Journal ISSN

2234-943X
2234-943X

Volume Title

9

Publisher

Frontiers Media SA