Efficacy and Mechanism Evaluation (EME) funding tips
Created on Tuesday, 13 Dec 2016.
- Funds ambitious studies evaluating interventions that have the potential to make a step-change in the promotion of health, treatment of disease and improvement of rehabilitation or long-term care.
- Includes hypotheses-driven research to improve the understanding of the mechanisms of both diseases (natural progression of disease) and treatments (interaction between treatment and disease).
- Supports translational researchinto a wide range of new or repurposed interventions.
- Funds clinical validation studies of diagnostic tests which have been developed and are known to work in the lab.
- Standalone mechanistic studies can be funded as long as they are added onto an existing NIHR funded study.
Innovative study designs involving stratification, the use of routinely collected digital data or novel methodologies are strongly encouraged.
Average cost £1 million (£150,000 - £3 million) over an average duration of 42 months
Send an A4 summary in PICO format (with intro and background) to the panel to see if in remit
- Population you are interested in
- Control treatment
- Outcome measure you are using
Tips for success:
Study should be optimised around the most important research question.
Clear rational, show what is known and unknown in the research area.
Appropriate skill mix, with a credible mix of clinicians, applied health researchers, statisticians, experts in study design, patients and project managers.
Co-investigators should be making a clear contribution without duplication to demonstrate value for money.
Evidence of good research track record provides confidence in the team.
Important to have CTU input from early in the development stage.
- Outcome measure:
Choose a primary outcome that is patient centred and reflects the study question.
It is important that you can measure the outcome in all people in the study.
- Pilot data:
It is important to provide relevant existing data about the population to be studied and your primary outcome measure to justify the study.
The panel is interested in information about the incident of the disease in the population, where possible the anticipated effect size of the intervention and likely recruitment numbers. Such data can all be used to justify the sample size.
- Sample size:
Always justify your sample size, give enough information so that the sample size can be reproduced and is easy to understand.
Make sure the effect size is sufficient to change practice and is clinically meaningful and credible.
- Recruitment plan:
Provide a detailed recruitment plan based on data.
Make sure you are looking at numbers who have the condition and fit the study eligibility criteria.
Very few trials manage to recruit more than 50% of eligible patients!
Include an allowance for loss and put in place measures to minimise losses (losses have the potential to create bias).
Involve patients in developing measures to minimise loss as they have a good insight into what’s achievable.
- Mechanistic evaluation:
Not all proposals have a mechanistic element but when they do they should be hypotheses driven and aimed at (1) advancing scientific understanding of a clinical condition or therapy action or (2) furthering advances of health outcomes for the patients.
Mechanistic evaluations need to have the same rigour in design and clear objectives to the same standards as the efficacy evaluation part of the study.
Often mechanistic evaluations fail to meet the EME remit by being far too exploratory, focusing on biomarker discovery or failing to have the correct team in place.
Show good value for money.
Provide a realistic estimation of cost - don’t over estimate staff costs and underestimate non-staff costs, placebos can be expensive!