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  Computation modelling of biological response to radiation at tissue level for Proton Therapy

   Faculty of Biology, Medicine and Health

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  Dr M Merchant, Prof K Kirkby, Dr John Warmenhoven, Dr Nicholas Henthorn, Dr A Chadwick, Dr Elham Santina  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Proton Beam Therapy (PBT) is a radically new type of radiotherapy that has the potential to improve the precision and targeting of radiotherapy leading to fewer side effects, faster recovery and better outcomes for patients. It also has the potential to target radio-resistant hypoxic tumours and tumours that are difficult to treat by more conventional means.

 NHS England has invested £250M in two new PBT treatment centres (London, Manchester), the first of which (at the Christie) opened in 2018. The Christie Clinical PBT Centre has three state of the art gantry rooms for clinical treatment and the fourth room, for research. The infrastructure and equipment in the PBT research room is funded by The Christie Charity.

 This project is aimed at using this new research capability in combination with developing computational models to answer a key challenge for proton therapy: what is the relative biological effect (RBE) of protons and how can this information be used clinically?

 Most clinical treatments with protons world-wide are given assuming that the same physical dose of protons delivers 1.1 times the biological effect of X-rays irrespective of depth, tissue type and oxygenation. Over several decades, evidence has accumulated for an increase in RBE at the end of proton range, but due to large experimental uncertainty, direct quantification of RBE has been challenging. RBE evidence is largely based on in vitro survival studies or in vivo pre-clinical studies, and evidence for detectable RBE effects which lead to normal tissue toxicity in patients has been elusive.

 Many phenomenological RBE models exist based on cell survival, as do tissue complication models based on empirical photon data, but this project addresses the conceptual gap that exists in computational modelling between the nanodosimetry of protons at a DNA level that cause treatment complications at a tissue level.

Entry Requirements

Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area/subject.  Candidates with experience in Monte Carlo simulation, radiation or medical physics or with an interest in radiobiology are encouraged to apply. 

For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website ( Informal enquiries may be made directly to the primary supervisor. On the online application form select the PhD Cancer Sciences.

For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit

Equality, Diversity & Inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website

Biological Sciences (4) Computer Science (8) Mathematics (25) Medicine (26) Physics (29)

Funding Notes

Applications are invited from self-funded students. This project has a Band 2 fee. Details of our different fee bands can be found on our website


Ingram SP, Henthorn NT, Warmenhoven JW, Kirkby NF, Mackay RI, Kirkby KJ, Merchant MJ. Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage. PLOS Computational Biology. 2020;16(12
Warmenhoven JW, Henthorn NT, Ingram SP, Chadwick AL, Sotiropoulos M, Korabel N, Fedotov S, Mackay RI, Kirkby KJ, Merchant MJ. Insights into the non-homologous end joining pathway and double strand break end mobility provided by mechanistic in silico modelling. DNA Repair (Amst). 2020;85(February 2019):102743.
Ingram SP, Warmenhoven JW, Henthorn NT, Smith EAK, Chadwick AL, Burnet NG, Mackay RI, Kirkby NF, Kirkby KJ, Merchant MJ. Mechanistic modelling supports entwined rather than exclusively competitive DNA double-strand break repair pathway. Sci Rep. 2019;9(1):6359.
Henthorn NT, Warmenhoven JW, Sotiropoulos M, Aitkenhead AH, Smith EAK, Ingram SP, Kirkby NF, Chadwick AL, Burnet NG, Mackay RI, Kirkby KJ, Merchant MJ. Clinically relevant nanodosimetric simulation of DNA damage complexity from photons and protons. RSC Advances. 2019;9(12):6845-58.
Henthorn NT, Warmenhoven JW, Sotiropoulos M, Mackay RI, Kirkby NF, Kirkby KJ, Merchant MJ. In Silico Non-Homologous End Joining Following Ion Induced DNA Double Strand Breaks Predicts That Repair Fidelity Depends on Break Density. Sci Rep. 2018;8(1):2654.
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