Working smarter, not harder: improving treatment combinations

​ A team of 13 led by Professor Jean-Pascal Machiels and Dr Anthony Kong 

Belgium, Denmark, Germany, Ireland, Italy and UK

 Clinicians, biologists, immunologists, bioinformaticians and mathematicians

 5 years


Treatment Regimens Grand Challenge

The challenge: Define mechanistic rules for combinatorial treatments to overcome resistance and avoid toxicity.

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.

Professor Jean-Pascal Machiels, Principal Investigator


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.


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.

This is a strong team with an excellent track record both in academia and commercially. They have put together a clear, well thought through proposal with an exciting, believable and ethical plan for progress into novel clinical trials. I look forward to hearing their full proposal.

Professor David Lane, Grand Challenge Advisory Panel 

The Team


Professor Jean-Pascal Machiels

Grand Challenge Shortlisted Team Principal Investigator
Head of the Department of Medical Oncology

Country: Belgium
Organisation: Université Catholique de Louvain
Discipline: Medical oncology, clinical trials & translational research​


Dr Anthony Kong

Grand Challenge Shortlisted Team Principal Investigator
Clinical Senior Lecturer

Country: UK
Organisation: University of Birmingham
Discipline: Clinical oncology


Professor Raffaele Calogero

Associate Professor of Molecular Biology​

Country: Italy
Organisation: University of Torino
Discipline: Molecular biology 


Ciaran Clissmann

Director of Pintail Ltd

Country: Ireland
Organisation: Pintail Ltd
Discipline: Research strategist


Professor Anthony Coolen

Professor of Applied Mathematics

Country: UK
Organisation: King's College London (KCL)
Discipline: Applied mathematics


Professor Hans Jürgen Hoffmann

Professor of Basic Allergy and Lung Immunology

Country: Denmark
Organisation: Aarhus University
Discipline: Immunology


Dr Denis Lacombe

Director General of European Organisation for Research and Treatment of Cancer (EORTC)

Country: Belgium
Organisation: EORTC
Discipline: Clinician


Dr Jean-Francois Laes

Chief Technological Officer​ of OncoDNA

Country: Belgium
Organisation: OncoDNA
Discipline: Molecular biology 


Dr Bodo Lange

CEO of Alacris Theranostics

Country: Germany
Organisation: Alacris Theranostics GmbH
Discipline: Cancer research & bioinformatics


Michelle Lynch

Patient advocate


Patricia Rhodes

Patient advocate

Organisation: Patient Research Advisory Group


Professor Christian Rolfo

Director of Clinical Trials

Country: Belgium
Organisation: University Hospital Antwerp 
Discipline: Translational research & drug development


Jez Ryder

Patient Advocate

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