The new research project, known as ‘PREpare using Simulated Trial Optimisation (PRESTO)’, will generate important insights for vaccine developers and public health officials on what vaccine clinical trial designs could help stop the spread of an emerging outbreak.
With up to US $2.4 million funding from the Coalition for Epidemic Preparedness Innovations (CEPI), researchers at the Pandemic Sciences Institute will simulate real-life scenarios of deadly disease outbreaks in order to model how possible vaccine clinical trials could run and what outcomes they could produce.
The infectious threats that will be tested are Nipah, Chikungunya, Lassa, Rift Valley fever, Ebola and related viruses, Coronaviruses and a new or as-yet-identified ‘Disease X’. These diseases are prioritised by CEPI and recognised on the WHO R&D Blueprint.
“When a new outbreak strikes, we won’t have time to get all the information we need to tell us how best to conduct pivotal clinical trials that test the efficacy or effectiveness of promising epidemic or pandemic vaccines” said Dr Richard Hatchett, CEO of the Coalition for Epidemic Preparedness Innovations (CEPI). “But mathematical modelling can give us a headstart by forecasting how a worrisome virus might spread and what we need to do to respond. Having PRESTO’s optimal study designs readily available in an outbreak will allow health officials to make quick, informed decisions on the best steps to take for more efficient vaccine testing and rapid evidence generation, thereby creating a faster outbreak response.”
Accelerating robust clinical trial design
Data from existing CEPI-funded research will be fed into the computer model alongside evidence from previous outbreaks to create hypothetical scenarios looking at how a selected virus could spread, who it could impact and its potential severity.
Findings from these scenarios will be used to produce analysis sheets that rank the suitability of different clinical trial options measuring the efficacy or real-world effectiveness of vaccines against each selected infectious disease.
For example, the modelling data could recommend that health officials conduct either a randomised controlled trial or a ring vaccination trial in response to an escalating outbreak. The analysis sheets will also suggest the optimal number of participants to enroll in the preferred trial design and the likely time needed to run the study to obtain the necessary data.
Having pre-established clinical trial frameworks in place ahead of an outbreak is key to executing the 100 Days Mission, which seeks to develop vaccines in just over three months from identification of a Disease X. This is around a third of the time it took to develop COVID-19 vaccines and could help stop a pandemic threat in its tracks.
Professor Christophe Fraser, Professor of Infectious Disease Epidemiology at the Pandemic Sciences Institute, University of Oxford, said: “Ensuring vaccines can be robustly tested at speed is critical if we are to better respond to future pandemic threats. With every day of delay potentially costing many lives, and with the recent experience from COVID-19, we now have an opportunity to develop improved vaccine clinical trial designs so we can hit the ground running in a disease outbreak.
“The PRESTO project will bring together mathematical modellers, ethicists, regulators, vaccine manufacturers and field teams to study what works with different pathogens in different settings.
“Our aim isn't to find the theoretical abstract best solution, but to develop models that allow decision-makers to explore the impact of the inevitable trade-offs that they will have to make in different settings. The aim in all trials is to test that vaccines are safe and effective, but there are many ways of finding people to recruit in a trial, and doing so well is particularly challenging given the fast-moving nature of the early stages of a pandemic.”
Rapid data sharing
PRESTO is a three-year research project. The team will first model and develop clinical trial design recommendations for Nipah, one of the deadliest diseases known to infect humans, before moving their efforts to focus on the other infectious diseases.
In the event of an outbreak of a new Disease X, the team will direct their computational modelling efforts to focus on the emerging pathogen. In such a scenario, the team will make their clinical trial modelling data rapidly available to help quickly inform public health response efforts.
The team will make its computer software available on an open-source platform. The project will be developed in a modular manner to allow external researchers to run their own tests on the model while also providing them with the opportunity to update the tool with new data as and when needed so that it remains accurate for years to come.
The trial simulation exercises form part of CEPI’s US $80m strategic partnership with the University of Oxford to accelerate development of vaccines against diseases with pandemic potential.