David Robertson – email@example.com
Potential PhD project
Master protocols for the efficient development of oncology drugs
This project will be co-supervised by Ayon Mukherjee (IQVIA)
Master protocols expedite drug development by testing multiple drugs and/or multiple cancer subpopulations in parallel under a single protocol, without the need to develop new protocols for each of the parallel sub-studies. Recently, there has been an upsurge in the development and use of such trial designs in oncology, with interest from industry, academia, and regulatory bodies. By using a single trial infrastructure and overarching trial protocol, master protocols improve efficiency, establish uniformity and lead to accelerated drug development. However, due to the complexity of master protocols, it is vital that these trials are well designed and appropriately analysed. There is much scope from a methodological perspective to continue to improve and develop master protocols for use in a wide range of oncology settings.
This PhD project is part of a joint academic-industry collaboration between the MRC BSU and IQVIA, and offers an exciting opportunity to work on a variety of methodological challenges for master protocols using real-world data from ongoing oncology trials run by IQVIA. As part of the PhD, there will be a 9-month internship planned with IQVIA where students would be involved in handling clinical trial projects. This would give the student hands-on experience of clinical trial processes and the implementation of novel methodology as a trial biostatistician, including the areas of application for the methodology developed in the PhD. A key part of the project will also be the development of packages in R as a part of a trial designer software in collaboration with IQVIA, to help enable the proposed methodology to be more widely used in practice.
Depending on the interests of the student, specific areas of focus for the PhD include the following:
Adaptive Dose-Escalation and Expansion Designs for Basket trials
A basket trial is a type of master protocol that evaluates a single targeted treatment for patients sharing a single biomarker or genomic feature, but across multiple diseases or disease subtypes (e.g. tumours in different organs of the body). A key advantage of basket trials is that they allow the evaluation of targeted therapies for genetic mutations that would be too rare to study within a tumour-specific context. As highlighted in recent FDA guidance, individual drug sub-studies under a master protocol might incorporate an initial dose-finding phase. This is particularly the case when evaluating an investigational drug combination, with the dose-finding stage identifying safe doses of the combination before proceeding with an activity-estimating stage. One potential area of focus of the PhD would be to develop a design and analysis framework for basket trials with an initial dose-finding stage, which consider the latest methodological developments in early phase dose-finding studies. Dose escalation and expansion studies are frequently used in clinical trials and regulatory agencies have published guidance on both these stages of the exploratory clinical trials. The focus of the research would be to develop adaptive methods for dose finding basket studies for estimating the true target dose that can be further expanded to find a signal for a particular indication.
Treatment selection in platform trials
The term platform trial is used to describe a master protocol that allows the flexibility of adding new treatment arms to the trial over time. Treatment arms enter into the trial as they become available, are evaluated, and then are ‘dropped’ for futility or ‘graduated’ from the trial once demonstrated as being efficacious. One potential area of focus of the PhD would be to develop novel platform designs that use covariate-adjusted response-adaptive randomisation, where the probability of patients being randomised to the different treatment arms varies over time based on the accumulated response data as well as their individual covariate information. This would then be combined with Bayesian decision making to compare experimental treatments to the control arm and select the best subset of treatment arms for a given indication. The focus of this research would be aligned to regulatory guidance on adaptive design for clinical trials and master protocols so that the methodology developed can be implemented in real clinical trials.
Details of supervisors
David Robertson is a Senior Research Associate at the MRC Biostatistics Unit, University of Cambridge, where he has been based since 2013. His research focuses on the development of novel methodology for the design and analysis of adaptive clinical trials. David held a Biometrika Trust Research Fellowship from 2018 – 2021, which explored questions around error rate control for clinical trial designs that test multiple hypotheses simultaneously.
A testimonial from a previous internship student supervised by David Robertson can be found here.
Ayon Mukherjee is the Director and the Head of Novel Trial Design Methodology group at IQVIA, which focuses on the implementation and development of complex innovative clinical trial designs in real-world clinical studies. As the Head of the Novel Trial Design team, he provides strategic input towards development of clinical trial designs, specifically adaptive designs and master protocols. He has over 12 years of experience working with various pharmaceutical companies, including GlaxoSmithKline and Novartis.
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