This project will be suitable for statisticians who are interested in applying their technical skills to improve information given by clinical trials about which patients benefit from a new treatment.
There has been an urgent need for better ‘precision medicine’ clinical trial designs that efficiently provide information about which types of patient benefit from the treatment. Our group works on methods for improving the design and analysis e.g. (1,2).
As part of the newly funded Clinical Trial Methodology Partnership Stratified Medicine Working Group, the student will focus on improving methods for precision medicine trials.
This would include:
1.Developing improved basket and umbrella trial designs. These allow combining several trials in related conditions together. Bayesian methods can be applied to allow adaptive borrowing of information between the different ‘modules’ of the trial. This methodology would be applied to a funded trial testing several treatments in related vasculitis disorders; and trials under development in breast cancer, primary biliary cholangitis, and childhood nutrition. 2.Developing improved methods for utilising the increasing amount of biological information collected in clinical trials, such as genomic and biomarker variables. This would cover both methods that would allow better stratification of patients into groups that benefit from a treatment.
Training on relevant statistical methods, statistical programming and clinical trials will be provided.
1.Wason JMS, Abraham JE, Baird RD, Gournaris I, Vallier A-L, Brenton JD, et al. A Bayesian adaptive design for biomarker trials with linked treatments. Br J Cancer. 2015 113(5):699–705. 2.Lee KM, Wason J. Design of experiments for a confirmatory trial of precision medicine. J Stat Plan Inference. 2018 Jun 23
Newcastle University (https://bit.ly/2Rzc8qJ), Faculty of Medical Sciences (https://bit.ly/2MOtbnS)
Name of supervisor(s):
Professor James Wason (https://bit.ly/2MOtlvu), Institute of Health and Society (https://bit.ly/2HHKgAV)
Applicants must have at least a 2:1 degree in a discipline relevant to the study and (by the time of starting the PhD) a master’s degree in statistics or a subject with a substantial theoretical statistics component/equivalent research training/experience.
If English is not your first language, you must have an overall IELTS of more than 6.5 with no component less than 5.5, or equivalent.
The award is available to UK/EU applicants. Non-EU international applicants who are interested should contact the supervisor.
How to apply:
You must apply through the University’s online postgraduate application system. To do this please ‘Create a new account’ (https://bit.ly/2UtXpyQ).
Only mandatory fields need to be completed. However, you will need to include the following information: •insert the programme code 8300F in the programme of study section •insert the studentship code HS036 in the studentship/partnership reference field •attach a covering letter and CV no more than two pages for each. The covering letter must state the title of the studentship, quote the studentship reference code HS036 and state how your interests and experience relate to the project •attach degree transcripts and certificates and, if English is not your first language, a copy of your English language qualifications.
100% of UK/EU tuition fees paid and annual living expenses of £14,777.