Parkinson's Disease May Start Years Before Diagnosis. Why Are We Still Waiting to Find Patients?

According to the Global Burden of Disease Study, approximately 11.8 million people were living with Parkinson's disease globally in 2021, contributing to more than 388,000 deaths and 7.47 million disability-adjusted life years (DALYs). Researchers project that the number of people living with Parkinson's disease could more than double by 2050 as populations continue to age and life expectancy increases (Su et al., 2025; Yang et al., 2026).

In the United States, the burden is also rising. The CDC recently reported increasing Parkinson's disease mortality among adults aged 65 years and older, highlighting growing pressure on healthcare systems, caregivers, and neurology services (CDC, 2026).

At the same time, scientific innovation is accelerating. New therapies, biomarkers, digital monitoring technologies, and regenerative medicine programs are creating optimism across the Parkinson's ecosystem. Yet, one fundamental challenge remains. Despite decades of research and billions of dollars in investment, there is still no approved therapy proven to reliably slow or stop Parkinson's disease progression (Menozzi & Schapira, 2025; Koros et al., 2025).

This raises an important question. What if one of the biggest challenges in Parkinson's disease is not discovering therapies, but identifying the right patients early enough for those therapies to work?

The Innovation Boom in Parkinson's Disease

The Parkinson's pipeline is more active than it has been in years. Researchers are pursuing multiple approaches that extend beyond traditional dopamine replacement therapies and symptom management.

Recent developments include:

These advances represent meaningful progress. However, scientific breakthroughs alone do not guarantee successful outcomes. Every therapy ultimately depends on identifying the right patients, at the right stage of disease, with the right evidence to support intervention.

Parkinson Patients Are Often Identified Too Late and Needs an Earlier Evidence Strategy

Parkinson's disease is often diagnosed when motor symptoms become difficult to ignore. The biology of the disease, however, may begin years earlier.

Research increasingly shows that prodromal Parkinson's disease can involve non-motor symptoms and subtle neurological changes long before diagnosis. These may include REM sleep behavior disorder, constipation, loss of smell, depression, anxiety, autonomic dysfunction, and subtle motor abnormalities (Yamakado & Takahashi, 2024; Cattaneo et al., 2026).

For patients, this often means years of uncertainty. Symptoms may be treated individually by different healthcare providers without anyone recognizing a broader neurological pattern. A patient may see a gastroenterologist for chronic constipation, a sleep specialist for REM sleep behavior disorder, or a primary care physician for fatigue and mood changes. The underlying disease process may remain hidden.

Research suggests that by the time a Parkinson's diagnosis is made, approximately 35% to 45% of striatal dopamine may already be lost, while some studies estimate that more than 60% of dopaminergic neurons may already be damaged (Yamakado & Takahashi, 2024; Runnova et al., 2024).

This creates a critical timing problem. Many therapies entering development are designed to preserve neuronal function, slow neurodegeneration, or intervene earlier in disease biology. Yet, many patients are not identified until substantial neurological damage has already occurred.

Promising Therapies Still Face Major Evidence Gaps

Scientific innovation is advancing rapidly. Evidence infrastructure is not always keeping pace. Even the most promising Parkinson's therapies face common challenges once they enter clinical development.

This challenge becomes increasingly important as precision medicine strategies rely more heavily on early intervention, biomarker-guided recruitment, and patient stratification. The future of Parkinson's research may depend as much on evidence generation as therapeutic innovation itself.

Rubix LS Perspective: The Evidence Gap Starts Before Diagnosis

At Rubix LS, we do not view Parkinson's disease solely as a recruitment challenge. We view it as an early-evidence challenge.

Rubix LS has not conducted Parkinson's disease-specific interventional trials. However, across adjacent neurological and complex-care evidence-generation initiatives, we have observed recurring patterns that overlap directly with questions Parkinson's researchers are now trying to solve.

These include:

• Early signal detection

• Delayed specialty referral

• Fragmented non-motor symptoms

• Biomarker readiness

• Underrecognized disease progression

• Limited specialist access

To better understand these challenges, Rubix LS conducted an internal review of 229 de-identified patient profiles from adjacent neurological and complex-care contexts.

 Rubix LS Data Lens: What Early Evidence Fragmentation Can Look Like

To make this challenge more tangible, Rubix LS reviewed 229 de-identified patient profiles from adjacent neurological and complex-care contexts. These profiles were not used to diagnose Parkinson’s disease. Instead, the review was designed to examine how early neurological signals, care-pathway barriers, and biomarker-readiness indicators can appear before patients become visible through traditional neurology recruitment channels.

Viewed as a patient-visibility problem, the findings suggest that early evidence may already exist, but it is often scattered across symptoms, specialists, geography, and incomplete referral pathways.

In this review:

1. Approximately 73 of 229 profiles demonstrated three or more early neurological signal categories, including sleep disturbance, hyposmia-like sensory changes, gastrointestinal dysfunction, mood-related symptoms, autonomic manifestations, or subtle motor concerns.

   
   

2. The median estimated referral delay was 21 months, suggesting that potentially relevant clinical signals may remain unresolved for nearly two years before reaching a more appropriate specialty pathway.

   
   

3. The median distance to a relevant specialist was 61 miles, underscoring how geography and access can influence whether patients become visible to research systems.

   
   

4. Approximately 66 of 229 profiles demonstrated characteristics that could support deeper alpha-synuclein seed amplification assay consideration.

   
   

5. Approximately 59 of 229 profiles demonstrated characteristics that could support dopamine transporter imaging consideration.

   
   

6. Approximately 78 of 229 profiles showed elevated inflammatory burden.

   
   

7. Approximately 37 of 229 profiles showed neurofilament light-related signals.

These findings do not indicate that these individuals had Parkinson’s disease. They also do not represent confirmed biomarker results. Instead, they illustrate a broader evidence-generation problem: many of the signals that may matter for earlier neurological research can appear before a patient is formally diagnosed, but those signals may not be organized in a way that supports trial readiness, biomarker characterization, or representative recruitment.

For sponsors, this creates a practical question. If therapeutic innovation is moving earlier in the disease course, how will research teams find and characterize patients before traditional referral pathways identify them?

These profiles were not used to diagnose Parkinson's disease. Instead, the review examined how symptom patterns, care-pathway barriers, and biomarker-readiness indicators may emerge before patients become visible through traditional neurology recruitment pathways.

Rubix LS internal review indicator	Percent of profiles	Approximate count out of 229	What it illustrates
Three or more early neurological signal categories	31.9%	~73 profiles	Early signals may cluster before diagnosis
Alpha-synuclein SAA consideration indicators	28.8%	~66 profiles	Some profiles may warrant deeper biomarker-readiness review
Dopamine transporter imaging consideration indicators	25.8%	~59 profiles	Imaging-readiness questions may emerge before formal research identification
Elevated inflammatory burden	34.1%	~78 profiles	Adjacent biological signals may add context to evidence planning
Neurofilament light-related signals	16.2%	~37 profiles	Neurodegeneration-related signals may require structured interpretation
Median estimated referral delay	21 months	Not applicable	Time can erode early-intervention opportunity
Median distance to relevant specialist	61 miles	Not applicable	Access barriers can shape who becomes research-visible

Rubix LS internal review of 229 de-identified profiles from adjacent neurological and complex-care contexts. Findings are illustrative evidence-planning indicators only and are not Parkinson’s diagnoses, prevalence estimates, or confirmed biomarker results. Several findings stood out.

31.9% of profiles demonstrated three or more early neurological signal categories, including sleep disturbance, hyposmia-like sensory changes, gastrointestinal dysfunction, mood-related symptoms, autonomic manifestations, or subtle motor concerns. The median estimated referral delay was 21 months, and the median distance to a relevant specialist was 61 miles. Together, these findings suggest that the early evidence problem is not only biological. It is operational. Signals may exist, but they can be distributed across disconnected encounters, delayed referrals, and access barriers that prevent patients from becoming visible to research at the moment when earlier intervention may matter most.

From a biomarker-readiness perspective, 28.8% of profiles demonstrated characteristics that could support deeper alpha-synuclein seed amplification assay consideration, while 25.8% demonstrated characteristics that could support dopamine transporter imaging consideration.

Importantly, these findings do not represent Parkinson's diagnoses or biomarker results. They represent evidence-planning indicators, suggesting that opportunities for earlier biological characterization may exist before patients become visible to traditional research systems.

The review also identified elevated inflammatory burden in 34.1% of profiles and neurofilament light-related signals in 16.2% of profiles. The takeaway is not that these profiles represent undiagnosed Parkinson's disease; the takeaway is that many of the scientific ingredients necessary for earlier Parkinson's evidence generation may already be visible before diagnosis. This is where evidence generation and equity intersect. If early signals are easier to detect in patients with consistent access to specialists, stronger referral pathways, and better diagnostic resources, then the future of Parkinson’s research may unintentionally overrepresent the patients who are easiest to find. The challenge is not only how to identify prodromal or earlier-stage patients. It is about building evidence systems that make the right patients visible without reinforcing existing access gaps.

Many Parkinson Patients Never Become Visible to Research

The challenge becomes even more significant for historically underrepresented populations. Research has consistently demonstrated disparities in Parkinson's diagnosis, specialist access, treatment utilization, and research participation (Kipnis et al., 2025; Venkatraman et al., 2024).

Patients facing transportation barriers, financial constraints, limited specialist availability, fragmented care pathways, or delayed referrals may be less likely to become visible to clinical research programs.

This creates a scientific problem as well as an equity problem.

When populations remain absent from evidence-generation efforts, uncertainty increases regarding how future therapies will perform in real-world settings. The evidence gap is therefore not simply who enrolls in a clinical trial. It is who becomes visible to the trial in the first place.

The Next Challenge Is Finding the Right Patients Earlier

The Parkinson's pipeline is not empty. The challenge is proving which interventions work, in which patients, and at what stage of disease. As the field moves toward earlier intervention, biomarker-guided development, regenerative medicine, and precision neurology, the need for stronger evidence infrastructure will continue to grow.

The next generation of Parkinson's research may depend on connecting:

• Real-world evidence

• Longitudinal symptom histories

• Access-pathway mapping

• Biomarker-readiness indicators

• Representative patient populations

before patients become too advanced for the intervention being studied. Without stronger longitudinal evidence, even promising breakthroughs may struggle to translate into real-world impact.

Up next: Evidence Brief

Our upcoming evidence brief will explore the early detection gap in Parkinson’s disease, along with key barriers to diagnosis, challenges in recruitment and representation, emerging opportunities in biomarker readiness, and what these mean for sponsors, CROs, healthcare systems, and investors.

We’ll be sharing the full brief in our next post, where we’ll dive deeper into the data, literature, and strategic implications shaping this space.

If your organization is working in Parkinson’s disease research, real-world evidence, patient identification, representative recruitment strategies, or broader evidence-generation initiatives, feel free to reach out to the Rubix LS team to continue the conversation.

References

1. Centers for Disease Control and Prevention. (2025). Parkinson disease mortality among adults age 65 and older: United States, 2014-2024 (NCHS Data Brief No. 563). National Center for Health Statistics. CdcParkinson Disease Mortality Among Adults Age 65 and Older: United States, 2024

2. Food and Drug Administration. (2024). FDA approves treatment for motor fluctuations in adults with advanced Parkinson's disease. U.S. Food and Drug Administration. Fdafda.gov/drugs/news-events-human-drugs/fda-approves-treatment-motor-fluctuations-adults-advanced-parkinsons-disease

3. Kipnis, D., Dorsey, E. R., Holloway, R. G., McDermott, M. P., Willis, A. W., Schneider, R. B., & Fleisher, J. E. (2025). Identifying barriers and facilitators to accessing care for historically marginalized communities affected by Parkinson disease. Journal of Racial and Ethnic Health Disparities, 12, 1811-1823. Doidoi.org/10.1007/s40615-024-02147-z

4. Koros, C., Fiske, B., & Stefanis, L. (2025). Gaps in the Parkinson's disease therapeutic clinical pipeline: A focus on approaches targeting disease pathobiology. Journal of Parkinson's Disease, 15(1), 45-60. Iospresscontent.iospress.com/articles/journal-of-parkinsons-disease/jpd240245

5. Menozzi, E., & Schapira, A. H. V. (2025). Prospects for disease slowing in Parkinson disease. Annual Review of Pharmacology and Toxicology, 65, 237-258. Doidoi.org/10.1146/annurev-pharmtox-052423-105253

6. Pagano, G., Polychronis, S., Wilson, H., Giordano, B., Niccolini, F., Yousaf, T., Khan, N. L., & Politis, M. (2024). Trial of lixisenatide in early Parkinson's disease. New England Journal of Medicine, 390(13), 1176-1185. Doidoi.org/10.1056/NEJMoa2312323

7. Schrag, A., Horsfall, L., Walters, K., Noyce, A., & Petersen, I. (2023). Prediagnostic presentations of Parkinson's disease in primary care: A case-control study. JAMA Neurology. Jamanetworkjamanetwork.com/journals/jamaneurology/fullarticle/2799774

8. Schweitzer, J. S., Song, B., Herrington, T. M., Park, T. Y., Lee, N., Ko, S., Jeon, J., Cha, Y., Kim, K., Li, Q., & colleagues. (2025). Phase I trial of hES cell-derived dopaminergic neurons for Parkinson's disease. Nature, 639, 433-440. DoiPhase I trial of hES cell-derived dopaminergic neurons for Parkinson’s disease

9. Su, D., Zhang, W., Yang, X., Wang, Z., Wang, Z., Liu, J., & collaborators. (2025). Projections for prevalence of Parkinson's disease and its driving factors in 195 countries and territories to 2050. BMJ, 388, e080952. Doidoi.org/10.1136/bmj-2024-080952

10. Venkatraman, V., Chan, A. Y., Veeravagu, A., Ratliff, J. K., & Henderson, J. M. (2024). Disparities in the treatment of movement disorders using deep brain stimulation. Journal of Neurosurgery, 141(1), 241-251. Doidoi.org/10.3171/2023.10.JNS231191

11. Yang, R., Wang, Y., Wang, Z., Li, Y., Xu, Z., & collaborators. (2026). Global, regional and national burden of Parkinson's disease, 1990-2021. Journal of the Neurological Sciences, 480, 125703. Jns-journaljns-journal.com/article/S0022-510X(25)02325-1/fulltext

12. Yamakado, H., & Takahashi, R. (2024). Experimental animal models of prodromal Parkinson's disease. Journal of Parkinson's Disease, 14(Suppl. 2), S369-S379. Iospresscontent.iospress.com/articles/journal-of-parkinsons-disease/jpd249003

Internal Data Disclosure

Rubix LS. (2025). Internal evidence review of 229 de-identified patient profiles from adjacent neurological and complex-care contexts. Unpublished internal analysis.

Note. Findings from the Rubix LS review are exploratory and should not be interpreted as Parkinson's disease prevalence estimates, diagnostic outcomes, or clinical trial results. The review was conducted to evaluate early neurological signal patterns, care-pathway barriers, and biomarker-readiness indicators relevant to evidence-generation strategy.