In this early-career researcher interview, we talk to Dr Rebecca Pinto, who is a Post-Doctoral researcher and clinical trial co-ordinator at the Department of Old Age Psychiatry at King’s College London. Rebecca works on the IMI-funded PD-MIND project, which stands for Parkinson’s Disease with Mild cognitive Impairment treated with Nicotinic agonist Drug.
Could you tell us a little bit about your work on PD-MIND, and what it involves?
I am currently setting up the PD-MIND clinical trial, a multi-site trial that will be conducted in the UK, Norway, Czech Republic, Italy and Germany. As trial manager I am responsible for the set-up of the study, which has included developing trial documentation and co-ordinating the preparation of all applications for national and local approval.
Once approvals are in place, the sites will start to recruit participants for our study. My main role will be to address any problems as they arise to ensure the safety of all our participants and the ongoing progression of our study, including monitoring recruitment so that we meet our targets. Once the study has ended the real fun (for me) starts – going through the wonderful rich source of data on our hands.
How will the findings from PD-MIND benefit people who are affected by Parkinson’s and/or other neurodegenerative/brain disorders?
Parkinson’s disease – mild cognitive impairment (PD-MCI) is common, has important clinical consequences, and there is currently no treatment available. So on one level, we are addressing an unmet clinical need to treat PD-MCI. PD-MIND will test for the first time the potential of a nicotinic agonist, AZD0328, in PD-MCI, primarily evaluating its effect on cognitive symptoms of this condition.
On another level, we hope to validate new, non-invasive ways to detect and monitor the progression of PD-MCI. Monitoring treatment effects using structural and functional MRI is in its infancy, so PD-MIND will assess MRI imaging biomarkers, to potentially identify predictors of response to AZD0328, markers of target involvement and disease course. The MRI biomarkers assessed may have the potential to identify subgroups with high or low likelihood of response to nicotinic agents (i.e. “diagnostic MRI biomarker tools”). These could be further developed towards an opportunity for personalized medical interventions.
Could you describe your career path to date?
In 2006, I started my first research post at King’s College London (KCL). It involved using a unique database containing anonymized electronic medical records of over 200,000 patients, to explore ethnic differences in the primary care management of patients with psychosis. In 2009, I started a MRC-funded MSc & PhD programme in Social, Genetic and Developmental Psychiatry at KCL. My PhD was a multi-disciplinary investigation of ADHD employing quantitative, statistical and molecular genetics, and I was able to use rich sets of data from a number of twin cohorts, such as TEDS and SAIL. My first post-doctoral position, still at KCL, was using the nationally representative Swedish Twin Registers (approx. 21,000 individuals) to explore the aetiology of tic-related disorders across the lifespan. I then started managing a 5-year NIHR-funded programme on visual hallucinations in dementia, Parkinson’s and macular degeneration. After this, I moved to PD-MIND.
Although quite varied in terms of research areas, there are 2 consistent themes – KCL, and rich data that I have been privileged to work on at each stage of my research career.
What’s next? Where do you see yourself in 5-10 years’ time?
Being a Phase 2a study, PD-MIND study is an exploratory rather than confirmatory study to assess whether a reasonably strong signal of efficacy can be achieved. If successful, the findings will inform future phase III clinical trial designs. I hope to remain involved with PD-MIND, and have the continued opportunity to personally work on the data that it and any future trials may generate.
In the future, I would like to establish my own longitudinal study with a well-defined cohort producing masses of data.