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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
Indhold leveret af Oncology Times. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Oncology Times eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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

179 episoder

Artwork
iconDel
 
Manage episode 428278268 series 1021077
Indhold leveret af Oncology Times. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Oncology Times eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.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

179 episoder

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