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A Multi-Drug Algorithm Used to Accurately Predict Best First-Line Treatments in Patients With Newly Diagnosed Acute Myeloid Leukemia
Manage episode 428278268 series 1021077
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.
184 つのエピソード
Manage episode 428278268 series 1021077
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.
184 つのエピソード
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