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A Multi-Drug Algorithm Used to Accurately Predict Best First-Line Treatments in Patients With Newly Diagnosed Acute Myeloid Leukemia

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Manage episode 428278268 series 1021077
Content provided by Oncology Times. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Oncology Times or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

A mathematical model using data from routine diagnostic samples has been found to accurately predict individual patient responses to the main candidate first-line treatments for acute myeloid leukemia.

Findings from a validation study in independent patient cohorts led by researchers from the Barts Cancer Institute at the Queen Mary University of London were reported at a poster session of the 2024 ASCO Annual Meeting.

Oncology Times correspondent Peter Goodwin attended the session and talked with the second author of the study, Weronika E. Borek PhD, a Bioinformatics Technical Lead at Kinomica Limited in London.

  continue reading

172 episoade

Artwork
iconDistribuie
 
Manage episode 428278268 series 1021077
Content provided by Oncology Times. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Oncology Times or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.

A mathematical model using data from routine diagnostic samples has been found to accurately predict individual patient responses to the main candidate first-line treatments for acute myeloid leukemia.

Findings from a validation study in independent patient cohorts led by researchers from the Barts Cancer Institute at the Queen Mary University of London were reported at a poster session of the 2024 ASCO Annual Meeting.

Oncology Times correspondent Peter Goodwin attended the session and talked with the second author of the study, Weronika E. Borek PhD, a Bioinformatics Technical Lead at Kinomica Limited in London.

  continue reading

172 episoade

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