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Unlocking multidimensional cancer therapeutics using geometric data science
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Parashar, Deepak (2023) Unlocking multidimensional cancer therapeutics using geometric data science. Scientific Reports, 13 (1). 8255. doi:10.1038/s41598-023-34853-x ISSN 2045-2322.
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WRAP-unlocking-multidimensional-cancer-therapeutics-using-geometric-data-science-Parashar-2023.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1784Kb) | Preview |
Official URL: https://doi.org/10.1038/s41598-023-34853-x
Abstract
Personalised approaches to cancer therapeutics primarily involve identification of patient sub-populations most likely to benefit from targeted drugs. Such a stratification has led to plethora of designs of clinical trials that are often too complex due to the need for incorporating biomarkers and tissue types. Many statistical methods have been developed to address these issues; however, by the time such methodology is available research in cancer has moved on to new challenges and therefore in order to avoid playing catch-up it is necessary to develop new analytic tools alongside. One of the challenges facing cancer therapy is to effectively and appropriately target multiple therapies for sensitive patient population based on a panel of biomarkers across multiple cancer types, and matched future trial designs. We present novel geometric methods (mathematical theory of hypersurfaces) to visualise complex cancer therapeutics data as multidimensional, as well as geometric representation of oncology trial design space in higher dimensions. The hypersurfaces are used to describe master protocols, with application to a specific example of a basket trial design for melanoma, and thus setup a framework for further incorporating multi-omics data as multidimensional therapeutics.
Item Type: | Journal Article | ||||||
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Subjects: | R Medicine > RC Internal medicine | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Cancer Research Unit Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
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SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | Cancer -- Treatment , Cancer -- Diagnosis, Geometric analysis | ||||||
Journal or Publication Title: | Scientific Reports | ||||||
Publisher: | Nature Publishing Group UK | ||||||
ISSN: | 2045-2322 | ||||||
Official Date: | 22 May 2023 | ||||||
Dates: |
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Volume: | 13 | ||||||
Number: | 1 | ||||||
Article Number: | 8255 | ||||||
DOI: | 10.1038/s41598-023-34853-x | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 27 June 2023 | ||||||
Date of first compliant Open Access: | 27 June 2023 |
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