The Use of Synthetic and/or Real-world Data within Early Economic Modelling to Guide the Adaptive Design Process of Controlled Trials at Newcastle University

Award Summary

Funding will cover tuition fees at the Home (UK) rate only, a Research Training and Support Grant (£5,000 p.a.) and an annual stipend aligned to the UKRI rate (£18,622 p.a., 2023/24 rate).

International applicants will be considered. Successful international candidates will be required to fund the difference between home and international fees.

Overview

This project will investigate the use of synthetic controls and/or real-world data within early economic modelling and whether this in turn can help the adaptive design process of controlled trials.

Early economic modelling can be used to determine whether a technology has the potential to be cost effective early in its development cycle. Furthermore, they can inform where future research would be best undertaken to reduce decision uncertainty through a value of information analysis. The adaptive design of trials is a methodology aimed at improving the efficiency and increasing patient benefit from controlled trials. Traditional evidence generation via controlled trials is an expensive and lengthy business and HTA bodies such as NICE are developing frameworks for the incorporation of real-world data into decision-making. The use of synthetic data and/or real-world data in combination with early economic modelling to develop a framework for informing adaptive trial design may offer a more efficient way of conducting research.

This project will involve reviewing the literature for related methods for early economic modelling and adaptive trial designs. It will develop methods and guidance for incorporating real-world data and/or synthetic control data into early modelling and the subsequent use of value of information analyses to inform adaptive trial designs. A possible extension will be to consider how this initial input can then be further applied to interim decision making in adaptive trials.

You will become expert in the use of synthetic and/or real-world data within economic evaluation and the use of early modelling to inform adaptive trial designs.

Number Of Awards

1

Start Date

January 2024

Award Duration

The funding covers a 3-year PhD.

Application Closing Date

23 November 2023

Sponsor

Faculty of Medical Sciences, Newcastle University.

Supervisors

Lead Supervisor: Dr Gurdeep S Sagoo

Co-Supervisor: Professor James Wason

Co-Supervisor: Mr Stephen Rice

Eligibility Criteria

You must have, or expect to achieve, at least a 2:1 honours degree or international equivalent, in an appropriate subject, including but not limited to: decision science, biostatistics, statistics. The candidate must have knowledge of or be willing to learn health economic evaluation. A further qualification such as an MSc in health economics is desirable.

Applicants whose first language is not English require an IELTS score higher than 6.5 overall with a minimum of 6.0 in each subsection. International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.

For application information and contact details please see https://www.ncl.ac.uk/postgraduate/fees-funding/search-funding/?code=ph040

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