2026-27 Project (Sumner & Clark & Grint)

Mathematical modelling and clinical trial simulation of TB prevention

SUPERVISORY TEAM

Supervisor

Dr Tom Sumner at LSHTM
Faculty of Epidemiology & Population Health, Department of Infectious Disease Epidemiology and Dynamics
Email: tom.sumner@lshtm.ac.uk

Co-Supervisor

Dr Rebecca Clark at LSHTM
Faculty of Epidemiology & Population Health, Department of Infectious Disease Epidemiology and Dynamics
Email: Rebecca.Clark@lshtm.ac.uk

Co-Supervisor

Dr Daniel Grint at LSHTM
Faculty of Epidemiology & Population Health, Department of Infectious Disease Epidemiology and International Health
Email: Daniel.Grint@lshtm.ac.uk

PROJECT SUMMARY

Project Summary

Tuberculosis (TB) is an infectious disease responsible for approximately 1.5 million deaths per year. New TB vaccines are seen as a key tool to reduce this burden.  Several new vaccine candidates are in various stages of development including one in multi-site phase 3 clinical trial. Vaccine development is taking place alongside the development of new TB preventive treatment (TPT) regimens and recommendations for wider use of TPT. These developments raise questions about how best to evaluate and deploy vaccines and TPT to prevent TB. This project will use data analysis, clinical trial simulation and mathematical modelling to explore the interaction between new TB vaccines and TPT and help inform the use of new tools to prevent TB.

Project Key Words

Tuberculosis, vaccines, modelling, trials, simulation

MRC LID Themes

  1. Infectious Disease
  2. Global Health
  3. Health Data Science

Skills

MRC Core Skills

  1. Quantitative skills
  2. Interdisciplinary skills

Skills we expect a student to develop/acquire whilst pursuing this project:

  • Mathematical modelling including model design, parameterisation and fitting
  • Clinical trail design, simulation and statistical analysis
  • Computer programming (in e.g. R) and use of high performance computing environments

Routes

Which route/s are available with this project?

  • 1+4 = Yes
  • +4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

  • LSHTM – MSc Epidemiology
  • LSHTM – MSc Health Data Science
  • LSHTM – MSc Medical Statistics

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Location & Travel

Students funded through MRC LID are expected to work on site at their primary institution. At a minimum, all students must meet the institutional research degree regulations and expectations about onsite working and under this scheme they may be expected to work onsite (in-person) more frequently. Students may also be required to travel for conferences (up to 3 over the duration of the studentship), and for any required training for research degree study and training. Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Day-to-day work (primary location) for the duration of this research degree project will be at: LSHTM – Bloomsbury, London

Travel requirements for this project: No essential travel. The student may potentially visit international collaborators.

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • Minimum standard institutional eligibility criteria for doctoral study at LSHTM
  • The student should have a background in epidemiology with a strong quantitative focus (e.g. an MSc in Epidemiology or Medical Statistics) or a mathematical background (e.g. mathematics, physics)
  • Some experience of mathematical modelling is desirable, but not essential.
  • Some experience of computer programming is desirable but not essential.

Other useful information

  • Potential Industrial CASE (iCASE) conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Rationale
Tuberculosis (TB) is an infectious disease responsible for approximately 1.5 million deaths per year.    Biomedical tools for the prevention of TB are limited. Bacille Calmette-Guérin (BCG), the only currently licensed vaccine against TB, is typically given at birth and protects infants and young children against severe forms of tuberculosis but it’s effectiveness against TB in adolescents and adults is very variable. Tuberculosis preventive treatment (TPT), consisting of 3-6 months of antibiotics, has been shown to be effective at reducing the risk of TB but its use is largely limited to those at highest risk, including people living with HIV and young children who are contacts of people with TB. Several new TB vaccines are in development, with a number of candidates in phase 2b and phase 3 trials. At the same time, developments in TPT regimens have led to recommendations for wider eligibility for TPT, including adult contacts of people with TB, alongside interest in long lasting injectable forms of TPT.  Changes in TPT recommendations have implications for the design of future TB vaccine trials and for the potential population level adoption and impact of any newly licensed vaccine.

Aim
This PhD studentship aims to use clinical trial simulation and mathematical modelling to explore the interaction between TPT and new TB vaccines.

Objectives
The proposed high level objectives for the project are:

How should future vaccine trials be designed to account for increased use of TPT among trial participants?

  • Wider eligibility for TPT will mean that a  greater proportion of potential vaccine trial participants will be taking TPT or should be offered it as standard of care. Clinical trial simulations will be used to quantify the effects of TPT in different vaccine trial designs.

How might wider use of TPT effect the population level impact of new TB vaccines?

  • Wider use of TPT, or the development of long acting injectables, may reduce the demand or acceptability of new TB vaccines. Mathematical modelling will be used to explore how future use of TPT may effect the population level impact of new TB vaccines.    

Techniques
The project will use a variety of data analysis and modelling methods. The project will involve the development of clinical trial simulation models and the adaptation of existing dynamic transmission models of TB.  The project will involve the use model fitting methods including approximate Bayesian computation and history matching with emulation.

Datasets and materials
The project will primarily use existing data sources that are publicly available. Additional data from ongoing clinical trials will become available during the course of the PhD.  Access to high performance computing resources will be available via LSHTM (if required).

Risks and mitigation
As the overall aim of the project will be achievable with existing data there are no significant risks to the project.

Further reading

Relevant preprints and/or open access articles:
(DOI = Digital Object Identifier)

Other pre-application materials:

Additional information from the supervisory team

The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.

Sumner & Clark & Grint Recording

MRC LID LINKS

To apply for a studentship: MRC LID How to Apply
Full list of available projects: MRC LID Projects
For more information about the DTP: MRC LID About Us

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