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SPHENE team is shortlisted for CANCER RESEARCH UK'S GRAND CHALLENGE

February 9th, 2018

OncoDNA is proud to be partner of the SPHENE project, which is carefully selected for the shortlist of Cancer Research UK's Grand Challenge.

Professor Jean-Pascal Machiels, Principal Investigator: “We are extremely honoured and excited to be shortlisted for Cancer Research UK’s Grand Challenge award. If awarded, this project will change the landscape of the management of head and neck cancers, a high unmet need. We will apply a systems biology approach to predict the response of an individual patient to specific cancer therapies. The ultimate goal is to improve cancer outcomes by making precision medicine a reality”.

 

Background

Treatments like chemotherapy and radiotherapy are very good at killing cancer cells. But due to the variability of cells in a tumour, some cancer cells can resist treatment. Resistant cells can survive and continue to grow, forming a tumour once again. To target a cancer from all angles, doctors often give patients a combination of treatments. This approach is extremely complex, as many factors influence the best treatment option for each individual patient. It’s not always clear which combination is best, how much of each treatment to give, or when the different treatments should be given.

This Grand Challenge project will be tackled by an expert team consisting of clinicians, molecular researchers, data scientists and computer scientists. The aim of this multidisciplinary team is to use artificial intelligence (AI) and computer modelling to determine the optimum treatment combination for each individual patient, transforming outcomes on a global scale.

The Research

Professor Machiels and Dr Kong’s team is an international team of experts from Belgium, Germany, Denmark, Italy, Ireland and the UK, whose approach will combine clinical data and laboratory research with computational modelling and AI. The team will assess samples from patients with squamous cell carcinomas of the head and neck (SCCHN) who have been treated with defined therapies. They will analyse:
– tumour samples from patients receiving the standard treatment for SCCHN
– tumour samples and blood biopsies from Europe’s largest umbrella study of SCCHN
– SCCHN cancer cells grown in the lab

Firstly, a wealth of biological information will be extracted from tumour samples and biopsies including biomarkers – a way of identifying disease status, treatment response and resistance. They’ll use this information to understand the biological mechanisms of exactly how tumours respond (or not) to drugs and how treatment resistance occurs.

This huge amount of data will then be used to build, train and improve a mechanistic model and computer programme, supported by AI, to work as a simulation tool. Like a virtual crash test or flight simulator, all available biological information for each new cancer case will be added, and the model will run a virtual treatment simulation and clinical trial. In doing so, the model will identify the outcome of different treatment combinations for an individual patient’s cancer, which could be vital in aiding clinical decision making and reduce unnecessary treatment toxicities.

Impact

By combining the power of AI and mechanistic modelling with data from the clinic, Professor Machiels and Kong’s team hope to gain an in-depth understanding of how cancers become resistant to treatment and ways to overcome this resistance. The end output will be a computer model capable of determining the best possible treatment combinations for each individual patient – creating a truly personalised plan with maximum chance of success.

More info here: http://bit.ly/2EeeaXl