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Medication recommendation in cancer treatment based on cell line similarity

Pimenta, Diogo , Teles, Mónica , Belfo, Fernando , Trigo, António

ISLA — Instituto Politécnico de Gestão e Tecnologia

Procedia Computer Science, Volume 219, 2023, pp. 1493–1500

The possibility of performing the sequencing of the human genome has revolutionized the field of biology and medicine itself, paving the way to personalized medicine. In the case of cancer, which is a disease caused by mutations in DNA, the study of genome brings some advantages, because through the study of the functioning of the human organism and the mutations caused by tumor, this makes it possible to explore the effectiveness of a significant number of treatments through medication for certain cell lines derived from various oncological problems. Bioinformatics has some powerful tools that help in the acquisition, storage, analysis, and visualization of genomic data. The research underlying this article was based on the analysis of biological data and established as its main objective the test of the premise that the most effective medications for a particular cell line are those that have been shown to be most effective in cell lines that are visually similar. A sample of 100 images of cell lines was used, and the medications used on each cell line were compared and the above premise was validated, concluding that the similarity in DNA between cell lines allows similar treatments to be recommend.

Keywords

#cancer therapy #drug recommendation #cancer cell lines #personalized medicine #drug response #genomic data analysis #Computer science #Premise #Similarity (geometry) #Visualization #Cancer #Genome #Human genome

Bibliographic Details

Publication Type Journal article

Publication Year 2023

Journal / Conference / Work Procedia Computer Science

ISSN 1877-0509

Volume / Issue Vol. 219

Pagination pp. 1493–1500

Publication Status Published

Scopus Indexing Indexed source (via SCImago)

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Medication recommendation in cancer treatment based on cell line similarity

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Bibliographic Details

ISLA Authors & Affiliations