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  • Research home > Beat Cancer Project search > Cancer Treatment Big Data: Predicting and understanding patient-specific treatment benefits, harms and prognosis

    Cancer Treatment Big Data: Predicting and understanding patient-specific treatment benefits, harms and prognosis

    Professor Michael Sorich
    • Donor Funding: $596,009
    • Cancer Type: All Cancers
    • Cancer Stage: Treatment
    • Funded in: 2020
    • Professor Michael Sorich
      Flinders University

    The research will develop online tools that will help patients to work through difficult decisions about how and when to use an anti-cancer medicine for the treatment of cancer. It will do so by utilising innovative methods to comprehensively analyse a very large amount of data that has recently become available from both clinical studies of medicines and routine use of the medicines by patients. This analysis will allow high-quality predictions to be made regarding a patient's specific likelihood of benefits and harms from using an anti-cancer medicine.

    This research will help overcome barriers to the communication of key information and empower patients by providing doctors with a toolkit to present the treatment options and their key outcomes to the patient in a manner that is personalised to their specific circumstances and characteristics. By having this personalised information, patients can feel more confident and empowered to make the most appropriate decision for them specifically regarding their treatment and will be better prepared by having more accurate expectations for their treatment outcomes.

    Additionally, the research will provide insight into the patient and disease characteristics influencing benefit and harms from treatment. These insights provide opportunities to better understand why medicines sometimes don't work well for certain individuals and how this may be overcome.



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