Using Artificial Intelligence for Precision Medicine

• Research type

  Research Study

• Full title

  Personalised Preoperative (Neoadjuvant) Chemotherapy (NACT) to Optimize Curative Treatment in Breast Cancer

• IRAS ID

  293230

• Contact name

  Stephen Y.T. Chan

• Contact email

  steve.chan@nuh.nhs.uk

• Sponsor organisation

  Nottingham University Hospitals, NUH, NHS Trust

• Clinicaltrials.gov Identifier

  AI_AWARD01884, NIHR AI Project

• Duration of Study in the UK

  3 years, 0 months, 1 days

• Research summary

  Aim: To enable an accurate prediction of the treatment response for each BC patient, with the aid of tumour imaging before and during pre-operative chemotherapy, which leads to the optimal personalised treatment to minimise chemotherapy dosage and side-effects.

  Method: Recently magnetic resonance imaging (MRI) has been routinely used to assess the tumour size before and after chemotherapy, for decisions regarding the effectiveness of therapy and the extent of surgery after chemotherapy. In addition to an accurate 3 dimension measurement of the tumour, the MRI provides useful
  biological information regarding the tumour. We will identify a set of features from these serial MRI scans in combination with routine clinical assessment data to predict the effectiveness of chemotherapy.

  Patient/public involvement: We have regular six monthly meetings to update our projects with the local patients
  support group. The member of the Patient/Public Advisory Group and the Nottingham BC Patient Support Group will be part of the management team for this project.

  Outcome: To develop an accurate procedure to help guiding routine treatments options, enabling better and timelier decisions for each patient's management. This will lead to the optimisation of chemotherapy, delivering cost-effective treatment, improved patient experience, and a reduction in healthcare costs burdens.

• REC name

  N/A

• REC reference

  N/A