Clinical Research: Phase 1 - Phase 4

The 7 Most Important Steps for Success in Neurodegenerative Disease Trial Design

When it comes to clinical trials for neurodegenerative disease (NDD), it’s easy to get overwhelmed by complexity. Not only are the mechanisms that underlie NDDs like multiple sclerosis and Alzheimer’s still largely a mystery, their inherent variability is hard to account for.

The best way to combat the problem? Break trial design down into more manageable pieces. Here are seven core factors every NDD trial design should address.

1. Develop representative phenotypes

Clinical presentation and progression for NDDs are highly variable, which is one of the main factors for why NDDs are tricky to diagnosis. In fact, many proteinopathies are only found postmortem, with symptoms — if present — attributed to some other cause.

Makes sure you’re clearly defining both the disease process being treated and the proposed endpoint for targeted therapy.

2. Recruit the right patient population

While a larger sample size may yield better data in theory, oversimplifying disease groups to do so backfires in NDD research. The solution? Define novel clusters, such as specific patient profiles or disease staging. Use a stratified approach to identify the patient population that’s right for your trial.

3. Adapt to a changing landscape

Unfortunately, many past strategies aren’t as effective in today’s NDD research climate. Patients have a range of treatment options now — which is a great thing! — but it also adds more challenges for NDD researchers. It means that the treatment-naive population is shrinking, especially in the case of conditions like multiple sclerosis that indicate early management.

4. Select sites with care

Of course, each of your trial sites should be staffed with skilled personnel who are experienced with patient engagement and clinical research. Other considerations for specific site selection include:

  • Local treatment guidelines
  • Level of access to and reimbursement for existing therapies
  • Incidence of both the disease of interest and relevant comorbidities
  • Regulations, especially those that govern placebo use

5. Utilize biomarkers

Today’s NDD researchers have access to a wide array of biomarkers for screening patients and evaluating treatments: EEG, CSF, MRI, PET, and more. These tools make up an alphabet soup that can drive trial design and supply quantitative data.

6. Conduct comorbidity analyses

Patients are often excluded from clinical trials due to comorbid conditions. But that isn’t always the best plan for NDD research where many other conditions can be considered an aspect of disease progression. Determining which comorbidities are common enough to be considered normal for your patient population can yield results more relevant for real-world clinical settings.

7. Incorporate adaptive design strategies

With lengthy and variable disease progression, NDDs are especially suited for adaptive trial design. This strategy makes sure patients receive individually tailored treatment without compromising on data quality.

Of course, each of these steps is much easier said than done. For more information on just how experts are tackling NDD trial design, be sure to read more about our research here.