Rethinking How Real-World Data Can Help Parkinson’s Disease Clinical Trials
RESEARCHER: Dr. Priti Gros
INSTITUTE: University of Toronto
PROJECT GRANT: Clinical Research Fellowship (2022 - 2024), $150,000, co-funded by Parkinson Society British Columbia through the Parkinson Canada Research Program.
Dr. Priti Gros from the University of Toronto, alongside her co-supervisors Dr. Connie Marras and Dr. Susan Bronskill, studies how real-world data can be used to improve clinical trials for disease-modifying therapies in Parkinson’s disease (PD). Real-world data (i.e. information routinely collected during everyday healthcare encounters) can help researchers design future trials and understand how treatments perform outside of controlled research settings.
Over the past two decades, numerous clinical trials for PD have tested promising therapies to delay disease progression, but none have demonstrated definitive long-term benefit. This raises a critical question: are these experimental drugs truly ineffective, or are we failing to study them in ways that reflect their impact on Parkinson’s disease unfolds in the real world? Their research addresses this question by showing how real-world data can help to rethink PD clinical trials through a series of studies: from who is recruited, to how progression is measured, to which potential therapies to test, and informing how clinical trials could be designed in the future.
Who participates in Parkinson’s disease-modifying therapy trials?
Most Parkinson’s disease-modifying therapy trials recruit participants from teaching hospitals and academic centers. Until recently, little was known about whether individuals seen in teaching hospitals early in their disease—the group most likely to be recruited into disease-modifying therapy trials—are representative of the overall Parkinson’s population. Dr. Gros’ research team used population-based data to compare nearly 20,000 individuals with Parkinson’s across Ontario (Canada). They examined those seen early by neurologists in teaching hospitals as a proxy for trial-eligible participants and compared them with individuals receiving early care in other settings, such as community neurology or primary care. Because the data capture nearly all healthcare interactions in a single-payer health system, this approach allowed for a province-wide real-world comparison.
They found that individuals seen in teaching hospitals were younger, had fewer comorbidities, and lived in more socioeconomically advantaged neighborhoods. In the long-term, they were less likely to develop dementia, require long-term care, or die, compared with individuals seen in other settings. Moreover, they were also more likely to receive additional Parkinson’s medications and surgical therapies, reflecting greater access to specialized interventions.
These results suggest that Parkinson’s disease trials may underrepresent individuals with faster complications and those from more disadvantaged communities. This has important implications for trial generalizability and health equity.
This work reveals potential blind spots in traditional clinical trials and suggests the need for more intentional recruitment strategies that better include all populations, including those historically underrepresented.
Beyond who is recruited: how progression is measured
The team’s current research focuses on how Parkinson’s disease progression is measured in clinical trials and how to assesses whether these measures align with the long-term health system trajectory of the disease. Many trials rely on short-term changes in clinical rating scales, particularly the motor component of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS Part III). Yet Parkinson’s unfolds over many years, sometimes decades.
By linking clinical assessments to long-term health service outcomes, they aim to evaluate whether short-term changes in commonly used scales are correlated with long-term milestones such as falls, dementia, institutionalization, or death. This study will test whether outcomes in clinical trials predict long-term disease burden.
Using real-world data to inform future trials: which therapies to test?
Their research uses real-world data not just to explore limitations in existing clinical trials, but also to help design future studies. By using large population-based health data and advanced methods, they can study treatments in ways that closely resemble clinical trials, but over much longer periods of time. The research will focus on drug repurposing (i.e. medications that are already approved and widely used for other conditions and may also help slow PD). They study how exposure to these drugs relates to outcomes that matter to people living with Parkinson’s disease and to the health system, such as independence, need for care, and survival. This approach helps identify potential therapies that are suited to be formally tested in clinical trials. It also offers a practical way to study long-term treatment effects at a large scale.
Using real-world data to design clinical trials
They are currently reviewing the literature and examining how randomized clinical trials have incorporated real-world data in their design not only within the field of neurology but also other medical fields. This involved reviewing trials that incorporated data such as health records, disease registries or health administrative data to support trial planning, follow-up, or outcome measurement. This work helps outline how real-world data can be thoughtfully integrated into clinical trials and potentially reduce cost, improve length of follow-up and capture meaningful outcomes.
What this means for people living with Parkinson’s disease
Parkinson’s disease clinical trials do not always reflect the experiences of everyone living with the disease. People who are most likely to be recruited into trials may differ from many individuals in the broader community, including those who are older, have additional health conditions, or live in more disadvantaged settings. At the same time, many trials rely on short-term measures that may or may not necessarily capture how Parkinson’s or the experimental drugs affect people over the long term. Real-world data, which follow individuals over many years in everyday care, may offer an opportunity to better understand disease progression outside of trial settings. Integrating this type of data into trial design may help future studies become more inclusive, cost-effective and more relevant to the lives of people living with chronic conditions, such as Parkinson’s disease.
Dr Priti Gros is a movement disorders neurologist and clinical associate at Toronto Western Hospital. She is currently a PhD student in Clinical Epidemiology and Healthcare Research, supervised by Dr. Connie Marras and Dr. Susan Bronskill. She is passionate about how real-world data can support clinical trials for disease-modifying therapies in Parkinson’s. Beyond her PhD, she is passionate about non-pharmacological therapies in Parkinson’s and is involved in the Dancing with Parkinson’s Boards of Directors.
This content was published in the Summer 2026 edition of our quarterly magazine, Viewpoints. The content was accurate as of this publication date.