Our Projects

The EJS ACT-PD trial and initiative are always focused on ensuring the latest innovations are being incorporated into the trial. Our ‘Trial Innovation Program’ has been developed as an additional program of research studies to be delivered alongside the trial to continue to drive innovation. The first phase of this program includes: 1) introducing digital outcome measures to collect more nuanced and sensitive changes in PD symptoms, 2) collecting biosamples into a large repository to enable novel fluid biomarker analysis, 3) providing strategies to optimise recruitment and retention including

additional core-funded delivery staff and supporting the production of the trial registration

process via the ‘Join Parkinson’s Research’ registry. Additional sub-studies and strategies for improvement are being considered.

Digital measures

Our Digital Measures Subgroup are focused on developing a robust and sustainable selection process to review and prioritise digital measures for inclusion as exploratory measures in the EJS ACT-PD trial. This follows the successful implementation of the current digital measures sub-study, assessing the mobilise-d Digital Mobility Outcomes (DMO) algorithm via the Axivity device.

The group are further exploring potential additional measures, both active and passive, for inclusion as a new sub-study. Proposals and suggestions are welcome via our research collaboration request process.

Biosamples

The Biosamples sub-study within the EJS ACT-PD trial invites participants at selected sites to provide additional biological samples including blood and cerebrospinal fluid, to help us understand more about how the treatments being tested are working and how Parkinson’s disease progresses. These samples can be used to explore whether treatments reach the brain, identify biological markers linked to treatment response or disease progression, and support new scientific analyses that may improve future research strategies.

The sub-study is currently recruiting well and the number of samples allows us to keep the analysis strategy flexible and open. Additional analyses and proposals for future biosample collection are actively welcomed as scientific needs evolve and new research questions emerge. You can submit proposals for analysis collaborations via our research collaboration request process.

Genetic analysis

The Genetic sub‑study in the EJS ACT‑PD trial is run in collaboration with the PD Frontline research study, and invites all participants to have their genetic information analysed to identify potential gene variations. This will help us to understand how genetic differences might influence Parkinson’s disease and responses to the treatments being tested. The samples will also be shared with the Global Parkinson's Genetics Program (GP2) for full genomic analysis.

Partner sub-study

The Partner sub‑study in the EJS ACT‑PD trial invites partners of participants to participate and contribute their own insights. Partners will be asked to complete questionnaires about their wellbeing and quality of life and how this might change during the trial. This unique element will help us to capture a fuller picture of how the treatments being tested are working and what wider impact they may have.

Statistical innovations

As the trial progresses, there is the opportunity to adopt advanced statistical innovations in two ways. First, we will exploit the trial dataset and perform new statistical modelling on the trial data – this will then inform how randomisation and treatment comparisons may occur in smaller groups, or how certain groups can be enriched for patients more likely to respond. These adaptations can then be incorporated into the next stage of the trial design (adaptive trial design based on statistical modelling). Second, we will implement another statistical innovation termed ‘trial emulation’. This allows the same inclusion/exclusion criteria of our trial, to be applied to external and existing routine healthcare datasets/observational studies so that near identical participants in terms of age, gender, ethnicity, geographical location and PD characteristics can be matched to each other, only differing according to whether they have been exposed to the drug of interest. Trial emulation in existing datasets is a robust way of predicting whether a new candidate drug is likely to have a disease-modifying effect if incorporated into the EJS ACT-PD MAMS platform. Both approaches can only be implemented once the trial has commenced, and this and other statistical approaches can significantly change the efficiency of a platform trial to deliver a treatment.