• One in Two - Clinical trials with Professor Corinne Faivre-Finn: How RAPID RT could improve survival rates for lung cancer patients

  • Sep 11 2023
  • Duración: 56 m
  • Podcast

One in Two - Clinical trials with Professor Corinne Faivre-Finn: How RAPID RT could improve survival rates for lung cancer patients

  • Resumen

  • In this episode, we speak to Corinne Faivre-Finn, a Professor of Thoracic Radiation Oncology about lung cancer clinical trials, focussing on:

    · Radiotherapy: what it is and how it’s used to treat lung cancers

    · Clinical trials: what are they, who are they for and how are they set up

    · The RAPID-RT clinical trial that launched at The Christie in early 2023, and how it could improve survival rates for lung cancer patients

    · The involvement of AI and rapid learning in this trial, and the benefits this has for data collection

    · Integrating patient voices into the trial

    Speaker profile:

    Corinne Faivre-Finn, FRCR, MD, PhD, is a Professor of Thoracic Radiation Oncology at the Division of Molecular and Cancer Sciences (University of Manchester) and Honorary Consultant Clinical Oncologist (The Christie NHS Foundation Trust, Manchester) with a specialist interest in lung cancer. Prof Faivre-Finn trained in Paris until 1998 and accepted a consultant post at The Christie in 2001. She has numerous professional roles including: Radiotherapy Research Lead and Radiotherapy Big Data Lead for Manchester Cancer Research Centre, Radiotherapy Research Lead for the CRUK Lung Cancer Centre of Excellence and Early NSCLC Chair of EORTC Lung Group. She is the Co-lead of the Christie/Manchester Cancer Research Centre Patient Reported Outcome Group.

    Show notes:

    Professor Corinne Faivre-Finn's research profile

    The Telegraph: AI utilised to help prevent lung cancer patients getting heart disease

    CRUK clinical trial research website

    RAPID RT, The University of Manchester

    Dr Gareth Price research profile

    We are Vocal home page

    Using real world data and rapid learning to drive improvements in lung cancer survival

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