Haiyan Zheng – firstname.lastname@example.org
Adaptive trial designs; Bayesian methods; Finite mixture distributions; Precision medicine.
Potential PhD Projects
- Seamless phase I/II trial designs in the era of precision medicine
With the growing interest in precision medicine, clinical trials are moving beyond one-size-fits-all. Patients can now be stratified into subgroups that may receive different benefits from new treatments targeting specific molecular or immune aberrations. This project will investigate seamless designs for early-phase clinical trials that involve various patient subgroups for the simultaneous evaluation of a new treatment. Such designs will address how to efficiently collect and use both toxicity and efficacy data. Bayesian methods for adaptive borrowing of information, both across the trial phases and the patient subgroups, will be developed.
- Robust designs for estimating nonlinear dose-response curves in biomarker-guided trials
Most biomarker-guided trials (involving multiple patient subgroups) in oncology investigate new treatments at a defined dose level. When translated to non-oncology disease areas, more doses are likely to be used to study a new targeted therapy. Interest would then lie in estimating the dose-response relationships. Nonlinear regression models are widely used to fit the data for more scientifically meaningful interpretation. One challenge for this context, however, is relating to data sparsity if the parameter vectors are estimated using data from a single stratum. This project will focus on the design of experiments enabling efficient estimation of a p-dimensional parameter vector that underpins a local dose-response relationship based on the entire trial data. Specifically, proper allocation of patients to different dose groups within each stratum is of interest.
- Using external information in oncology trials involving rare-disease subgroup(s)
Design and analysis of rare-disease trials are challenging, mainly because participant pools, even with worldwide recruitment efforts, can still be very small. Innovative approaches that permit the use of external information have been endorsed by regulatory agencies (EMA, 2006). A newly emerging approach is to involve rare-disease subgroup(s) in a basket trial that evaluate a new treatment targeting certain genetic mutation, immune aberration or disease trait shared by all eligible patients. This project will propose adaptive designs for externally augmented basket trials, that is, using external data to supplement, or replace entirely, a contemporary control treatment. The developed designs will be directed towards enhancing the chance of patients, particularly those of the rare-disease subgroup(s), to receive the new treatment if showing signals of efficacy compared to the control.
Additional funding opportunities
Please get in touch if you are interested. I am very keen to support enthusiastic students and create an effective plan of PhD training.
In your email, we strongly encourage you to enclose 1) your CV, and 2) a brief statement of which PhD project has interested you and how your research/experience is relevant.
Kindly note that strong quantitative background is a prerequisite.
About the supervisor
Dr Haiyan Zheng is a CRUK Research Fellow in Statistical Methodology, with considerable expertise in both theoretical and applied statistics, especially in the field of robust inference and informative prior specification for modern clinical trials. Haiyan currently leads a three-year research programme, funded by Cancer Research UK, to develop statistical methods that (1) simultaneously evaluate treatment effects in multiple subgroups, and (2) allow for mid-course adaptations in master protocol trials.
Haiyan has four years of supervisory experience. By now, one student has submitted their thesis for a PhD in Biostatistics and another two PhD students with their training ongoing. Two other mentees have also made excellent progress in research for trials with complex objectives.
The PhD project(s) listed above will be an integral part of Haiyan’s fellowship research programme. The student(s) will further benefit from the supervisor’s long-standing relationship with pharmaceutical companies worldwide, which would allow them to do an industrial placement as well as to build their own collaboration network.
Testimonials from Previous Students
‘I encountered some problem with Bayesian statistics in my research and then consulted Dr Zheng who had been known for established research in the field. Dr Zheng offered truly useful advice to get the ball rolling and kindly partnered with me in the role of my mentor since 2020. I have learned a lot from our research project in establishing novel Bayesian decision criteria for bioequivalence assessment, under Dr Zheng’s wonderful guidance. She has always been insightful about ‘where to go’ and ‘how to reach’ for realising my goals. From what I have seen, Dr Zheng is an intelligent and passionate researcher who is dedicated to high-quality, innovative research with academic rigour. I feel myself extremely lucky to have had such a great opportunity to work with Dr Zheng.’
Duo Lv, Mentee
‘I completed my PhD in Newcastle University with Dr. Haiyan Zheng as one of my PhD supervisors. Perhaps one of the best experiences being supervised by Haiyan is her dedication to ensuring the PhD (and its milestones) were completed in within our agreed timelines. That her support was guaranteed weekly or fortnightly, throughout the PhD was always inspiring as a student to put my best foot forward. Haiyan helped me greatly develop my skills as a Bayesian statistician, and challenged me to put forward ‘nothing-but-the-best’ through her constructive feedback on all my papers and presentations. Throughout the PhD, I learnt to value her great feedback which was encouraging – All the time, she made mention of the great effort that her student (myself) was putting into the project, even when things were challenging. Even more inspiring was Haiyan’s commitment in supporting me not only in successfully completing the PhD, but also work together on various projects beyond the PhD.
I highly appreciate that Haiyan developed in me this forward-thinking mentality – where we discussed and laid groundwork on potential projects ahead of time; she always introduced our work to her collaborators, and was very keen to involve me in her collaborative projects. And it wasn’t just all about the PhD – the dinners outside work, informal chats on many occasions made the PhD journey interesting. Today, I am happy that together we have some research collaborations on the way, and I’m always looking forward to working with Haiyan.’
How to apply
For details of the MRC BSU application process please see How to apply
To be considered for funding applications need to be submitted to the University of Cambridge application system by 23:59 (GMT) on January 5th 2023