The key precepts of precision medicine are that a) levels of response to a healthcare intervention vary between individuals, b) that this response heterogeneity is due to individual variation in underlying pathophysiological/biological processes, and c) that these processes contain measurable manifestations, termed ‘biomarkers’, which allow researchers to group together individuals with similar underlying physical responses to the healthcare intervention to form groups with common expected response rates. This allows clinicians to ‘target’ or ‘tailor’ treatments to individuals based on their biomarker profile to maximise treatment effects.
This basic framework has led to the development of specific clinical trial designs tasked with the ability to establish whether, and for whom, interventions produce differential response rates. Currently, biomarker-linked designs, such as the Bayesian adaptive design for biomarker trials with linked treatments (BAR design, Wason et al., 2015) work on the assumption that the biomarkers for differential response to interventions are known and identified.
This project intends to explore whether this assumption might be relaxed: in many disease areas, clinicians are aware of substantial individual variation in response to treatments, but there may not be an established biomarker per se. Rather than following the typical protracted and inefficient developmental process where biomarkers are characterised in studies separate to studies exploring treatment response, this project explores whether a two-stage design which initially uses latent variable approaches to loosely define class membership, is combined with Bayesian adaptive linked treatment designs into one study. The project will need to consider how the uncertainty of biomarker class membership produced by a latent variable model feeds into the adaptive randomisation process of the second stage.
The project plan is to initially conduct a systematic review of biomarker-targeted designs, and explore the literature for methods that might be best positioned to derive biomarker class membership, considering advantages and limitations of each with respect to the proposed design (e.g. mixture models, machine learning and similar). The project will then require the development of a simulation study which tests out the proposed two-stage design and explores its operating characteristics, following by a detailed discussion of the simulation study results. Part of the project work will involve establishing contact with local trust/industrial partners to ascertain whether a real-world completed trial dataset exists to supplement the project work.
Primary supervisor research page:
Professor Jamie Kirkham https://research.manchester.ac.uk/en/persons/jamie.kirkham
Co-supervisor research pages:
Matthew Parkes https://research.manchester.ac.uk/en/persons/matthew.parkes
Professor Maya Buch https://research.manchester.ac.uk/en/persons/maya.buch
Professor James Wason (external supervisor) https://www.ncl.ac.uk/nctu/staff/profile/jameswason.html
Eligibility
Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in (Quantitative) Research Methods, Mathematics, Psychology, Data Science or in a relevant discipline. Applicants with experience in Health Research Methods, Medical Statistics, and Clinical Trials are encouraged to apply.
Before you Apply
Applicants must make direct contact with the primary supervisor before applying to discuss their interest in the project. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.
How to Apply
To be considered for this project you MUST submit a formal online application form - full details on how to apply can be found on the BRC website https://www.bmh.manchester.ac.uk/study/research/funded-programmes/manchester-brc-phd-studentships/
Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team [Email Address Removed]
Equality, Diversity and 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 https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/
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