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A personalized cancer treatment program selects the most effective drugs for each patient. « Medicine in the Library

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A personalized cancer treatment program selects the most effective drugs for each patient.  « Medicine in the Library

A personalized cancer treatment program selects the most effective drugs for each patient.

Posted by giorgiobertin on June 22, 2023

“Precision” medicine seeks to adapt treatments to the characteristics of each patient. Genome studies are providing more and more data to achieve this goal, but this same abundance of information is hampering the task: Doctors have to interpret numerous genetic alterations and only a few will be relevant to diagnose the type and stage of each cancer and decide how treat him.
To facilitate this task, the Bioinformatics Unit of the National Cancer Research Center (CNIO) and the University of Vigo have just launched the PanDrugs2 software program, which generates reports to facilitate clinical decisions.

PanDrugs2 analyzes the genomic data of each patient in search of the so-called ‘molecular targets’, i.e. molecules on which existing drugs act. The platform calculates a scoring system for relevant genes and another for drugs that may affect them. The highest scores are obtained by drugs with the greatest scientific evidence of efficacy against the therapeutic targets detected in patients. From these scores, the tool generates a ranking of treatments

Overall, the platform manages data on 4,642 genes and 14,659 unique chemical compounds. Based on that information, it generated 74,000 drug-gene associations.

PanDrugs2 has been published in the journal “Nucleic Acids Research” and is available for free at https://www.pandrugs.org.

The new version updates semi-automatically and faster: “We went from updating in weeks to just days. This makes maintaining and releasing new versions even easier“, affirms Gómez-López.

Read the full text of the article:
PanDrugs2: prioritizing cancer therapies using integrated individual multi-omics data.
Jiménez-Santos MJ, Nogueira-Rodríguez A, Piñeiro-Yáñez E, et al.
Nucleic Acids Res. 2023:gkad412. doi: 10.1093/nar/gkad412

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Source: National Center for Oncological Research – University of Vigo, Department of Computer Science

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This entry was posted on giugno 22, 2023 a 12:08 PM and is filed under Artificial intelligence, News-search, Techno-Health, Web technology. Marked by tags: pharmacology, genetics, medical informatics, Artificial intelligence, oncology. You can follow any responses to this entry through the RSS 2.0 feed.

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