Model-driven and data-driven solutions for regulatory and HTA decision-making to address emerging challenges in drug development in cancer

   Department of Population Health Sciences

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  Dr S Bujkiewicz, Dr Sam Khan  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Additional Supervisors: Prof Richard Riley, University of Birmingham; Dr Daniel Jackson, AstraZeneca; Dr Janharpreet Singh, University of Leicester

When new cancer therapies are developed, they are evaluated in clinical trials assessing treatment’s impact on patients’ outcomes. Long-term survival is an outcome typically of interest to decision-makers, who recommend which new treatments should be available on NHS. However, modern cancer therapies are often targeted to small subsets of patients who harbour a particular biomarker. Therefore, data from clinical trials evaluating the effectiveness of therapies in a cancer subtype may be limited. Other sources of data; based on alternative outcomes, study types or other cancers, may need to be synthesised efficiently for reliable policy decisions. You will apply a range of modern tools from biostatistics (including Bayesian statistics, meta-analysis and survival analysis), epidemiology and data science and develop novel approaches for evaluation of cancer therapies.

This project is part of an exciting collaboration with University of Birmingham and AstraZeneca. You will benefit from an experienced supervisory team with expertise in statistics and oncology and an industry partner. This PhD in Biostatistics will provide you with an opportunity to develop advanced analytical skills, gain insight into drug development and decision-making processes and influence important decisions in healthcare. A suitable candidate will have MSc in Statistics, Medical Statistics or a related discipline.


Project Enquiries to [Email Address Removed]

Programme enquiries to [Email Address Removed]

To apply please refer to

Biological Sciences (4) Mathematics (25) Medicine (26)

Funding Notes

The competition funding provides students with:
4 years of stipend at UKRI rates
4 years of tuition fees at UK fee rates (Plus one award of a full overseas fee waiver to an international applicant)*
Budget to help with the cost of purchasing a laptop
The University of Leicester will provide full overseas fee waivers for the duration of their study to all international students accepted at Leicester. The funder, UKRI, allows us to appoint up to 30% overseas students.


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6. Papanikos T, Thompson JT, Abrams KR, Städler N, Ciani O, Taylor RS, Bujkiewicz S, A Bayesian hierarchical meta-analytic method for modelling surrogate relationships that vary across treatment classes. Statistics in Medicine 2020;39:1103–1124.
7. Poad H, Khan S, Wheaton L, Thomas AL, Sweeting M, Bujkiewicz S, The validity of surrogate endpoints in subgroups of metastatic colorectal cancer patients defined by treatment class and KRAS Status, Cancers 2022.
8. Schmitz S, Adams R, Walsh C. Incorporating data from various trial designs into a mixed treatment comparison model. Statistics in medicine. 2013 Jul 30;32(17):2935-49.
9. Jenkins D, Hussein H, Martina R, Dequen-O’Byrne P, Abrams KR, Bujkiewicz S, Methods for the inclusion of real world evidence in network meta-analysis, BMC Medical Research Methodology 21, 207 (2021)
10. S Bujkiewicz, J Singh, L Wheaton, D Jenkins, R Martina, K Hyrich, KR Abrams, Bridging disconnected networks of first and second lines of biologic therapies in rheumatoid arthritis with registry data: Bayesian evidence synthesis with target trial emulation, Journal of Clinical Epidemiology 2022; 150: 171-178
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