On the value of randomisation in designing small population clinical trials


   MRC Biostatistics Unit

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Dr Haiyan Zheng  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Phase II trial designs, conventionally in a homogeneous patient population, can be subdivided into two distinct types: i) single-arm (non-randomised) designs comparing the efficacy against historical controls, ii) randomised designs with a contemporary control arm. The latter may involve one or multiple experimental treatment arms for comparison to the common control. Whilst the highest form of evidence is generated by randomised clinical trials, the single-arm designs have been the most frequently implemented approach to efficacy assessment in oncologic drug development. Recent proposals include combination of the single-arm and randomised controlled designs [1]. This raises a few interesting questions, such as when to transit from the single arm to a randomised controlled setting and how to randomise. On the other hand, the pronounced data sparsity problem ignites the debate around if randomisation is needed for rare-disease trials [2]. Similar argument applies to precision medicine trials where patients are stratified into small subgroups that may receive different benefits from new treatments [3].

This project seeks to develop statistical methodology for improving the efficiency of phase II trials, especially those involving small populations. It will begin by quantifying gains in the trial efficiency from the use of a randomisation procedure since the start or midway through. A review of rare-disease or biomarker-driven trials that randomise patients between an experimental treatment against the control will be conducted. Simulations will be performed to understand i) when to best induce a randomisation scheme, if feasible, and ii) how to utilise data from all modules (i.e., subgroups and stages) of the trial for informed decision making. Bayesian adaptive methods will be developed to optimise the trial designs in situations of both homogeneous and heterogeneous populations. This project will further benefit from internal and external collaborations (see the section of ‘Planned secondments, research visit and internship’ for details).

The project will be undertaken under the joint supervision of Dr Haiyan Zheng and Prof Thomas Jaki. The student will be based in the MRC Biostatistics Unit (BSU), University of Cambridge. Founded in 1913, the BSU is one of the largest group of biostatisticians in Europe, and a major centre for research, training and knowledge transfer. The group, and the supervisors particularly, have long-standing relationship with clinical trial units in the UK and pharmaceutical companies around the world that will benefit the student and will allow them to build their own collaboration network.

The supervisors:

·       Dr Haiyan Zheng, CRUK Research Fellow in Statistical Methodology, has expertise in developing Bayesian methods, especially for informative prior specification and robust inference, into modern clinical trials.

·       Prof Thomas Jaki, Professor of Statistics and MRC Investigator, specialises in the design, conduct and analysis of clinical trials in all phases of drug development.

The BSU is best placed to deliver this research, as it will complement the flagship projects in response adaptive randomisation led by Dr Sofía Villar, an MRC Investigator. The student will meet Dr Villar periodically for collaboration.

This project will offer the opportunity of a two-month secondment with Prof Thomas Jaki at the University of Regensburg, Germany. The student will then work closely with members of Prof Jaki’s group on a small associated research project.

This project will also build collaboration with Prof Christina Yap (The Institute of Cancer Research, UK), a leading statistician who specialises in both developing and implementing novel statistical designs in oncology trials, and Oliver Schoenborn-Kellenberger (Cogitars GmbH, Germany), the founder of Cogitars GmbH and an expert with extensive experience in Bayesian adaptive designs of clinical trials. Both Prof Yap and Mr Schoenborn-Kellenberger will advise on the practical implementation of the methods developed from this studentship. A short research visit to Prof Yap and an internship in Cogitars GmbH will be planned. Intramural travel grants will be sought to support the secondment and research visits.

In June 2021, Dr Zheng spoke to two cancer patients about randomised basket trials (a typical kind of precision medicine trials). The patients appreciated the revolutionary shift from the conventional one-size-fits-all approach to finding best-suited treatments for the respective subpopulations. They also expressed willingness to take part if there is a trial using the standard of care treatment for the control group, but concerns were retained for the use of a placebo. In this project, optimal designs will be developed for maximising the gain of patients who are in the target populations. 

HOW TO APPLY

You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:

http://www.methodologyhubs.mrc.ac.uk/about/tmrp-doctoral-training-partnership/

Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.

Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.

Before making an application, applicants should contact the project supervisor to find out more about the project and to discuss their interests in the research before 09 January 2023.

The deadline for applications is 4pm (GMT) 16 January 2023. Late applications will not be considered.

Completed application forms must be returned to: [Email Address Removed]

Informal enquiries may be made to Dr Haiyan Zheng - [Email Address Removed]

Mathematics (25)

Funding Notes

Studentships are funded by the Medical Research Council (MRC) for 3 years. Funding will cover tuition fees at the UK rate only, a Research Training and Support Grant (RTSG) and stipend. We aim to support the most outstanding applicants from outside the UK and are able to offer a limited number of bursaries that will enable full studentships to be awarded to international applicants. These full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.

References

[1] Grayling MJ, Mander AP. Do single-arm trials have a role in drug development plans incorporating randomised trials? Pharm Stat. 2016; 15:143–151.
[2] Prasad V, Oseran A. Do we need randomised trials for rare cancers? Eur J Cancer. 2015; 51:1355–1357.
[3] Saad E, Paoletti X, Burzykowski T. et al. Precision medicine needs randomized clinical trials. Nat Rev Clin Oncol 2017; 14:317–323.