Overcoming the Challenges of CNS Studies

February 10, 2017
Moe Alsumidaie

As pharma continues to struggle with designing studies that result in creating breakthrough medical therapies, biopharma sponsors focusing on CNS studies face similar challenges and risks.

Biopharmaceutical sponsors focusing on CNS indications continue to face challenges and high risks, as the industry struggles with designing studies that result in generating breakthrough medical therapies. In November 2016, Lilly’s Phase III Solanezumab study failed1, and overall investments in CNS programs from big biopharmaceutical companies have declined by more than 50% from a total of 267 studies in 2009 to 129 studies in 20142. In this article, we will briefly recap discussions at ExL’s 2nd CNS Clinical Trial Forum, which delineate the challenges in CNS studies, novel approaches in CNS study design, and strategies on how to tackle the challenges.

Challenges in CNS Study Design

There was discussion on the risk/reward ratio for CNS studies being relatively high because of several factors. Firstly, preclinical models exhibit poor predictability due to dissimilarities in animal models and human brains and preclinical efficacy findings cannot be replicated. Secondly, biomarker surrogates are absent, making target and population selection very challenging, and outcomes measurements demonstrate high data variability. Lastly, IMP and study procedural adherence levels in CNS studies are lower compared to other indications and are rarely factored in study design during the development phase, leading to unanticipated study expenses, prolongation and data variability.

Challenges at the Study Site

From the study site’s standpoint, investigators are observing an increasing number of endpoints and procedures, variability in rater eligibility requirements and experience, recruitment and retention challenges, smaller budgets, and additional training burden from incorporating numerous vendors and technology applications.

CNS Study Failure Culprits

There was an interesting presentation on leveraging oncology approaches towards CNS study design. In oncology study design, sponsors typically utilize genetic and proteolytic pathways in order to identify potential targets for developing biomarkers. Biomarkers are, subsequently, used to increase study predictability, identify patients who are likely to respond, and can also serve as surrogate endpoints, essentially, enhancing targeting and study success probability. Unlike oncology, CNS biomarkers are rarely obvious before study development, as brain tissue is not readily available for researchers, and researchers must rely on imaging and electrophysiology studies, which provide vague clues into the disease. Moreover, oncology diseases tend to utilize objective endpoints (overall survival, progression free survival, time to disease progression etc.), whereas CNS study endpoints focus on subjective endpoints, such as assessment scales, which introduce much more data variability.

Discussions on the Use of Biomarkers in CNS

There was another in-depth discussion on the use of biomarkers in CNS studies. Specifically, biomarker types were defined as molecular, histologic, radiographic, physiological characteristics, nonetheless, current assessments that are used in CNS studies (i.e., scales administered by raters) are not considered biomarkers. Specific examples of CNS biomarkers include using cardiovascular stress, blood pressure, and cortisol levels as predictive biomarkers for depression. However, leveraging biomarkers in CNS studies also can pose challenges. For example, selecting biomarkers that exhibit high levels of false positives, or are very sensitive to small fluctuations may adversely impact study power. Another concern with biomarkers in CNS studies is that many are not validated for CNS. Nevertheless, the potential benefits for utilizing biomarkers in CNS studies offer the promise of enhanced success in clinical development.

Overcoming the Challenges in CNS

Clear solutions towards addressing CNS study challenges include developing a better understanding of disease models by creating biomarkers, focusing efforts on personalized and targeted therapies, requiring more evidence from animal models before moving to clinical trials, generating more focused inclusion/exclusion criteria in protocol development, and adopting novel and objective study endpoints rather than relying solely on subjective endpoints.

While obtaining a human brain to develop biomarkers is a challenge, Tom Hyde, MD, PhD, from the Lieber Institute for Brain Development offers an alternative approach. “Linking the genetic markers to disease requires exploring gene expression in the organ of interest, and in neurological and psychiatric disorders, this means exploring gene expression in human brain tissue,” said Hyde. “As living biopsies of brain are not feasible, the next best avenue of approach is cadaveric tissue. This can be obtained either prospectively, through donor registries, or with consent of next of kin at time of autopsy,” added Hyde. Hyde indicated, “recent studies in our laboratories have shown that there are often brain-specific transcripts playing a causative role in neurological and psychiatric disease, and these can only be revealed through the study of human brain tissue. Advances in therapeutics will rely upon targeting brain specific proteins and signaling pathways.”

ExL’s 6th Annual CROWN Congress is occurring in Philadelphia March 7 – 9, 2017.

References

  1. https://www.nytimes.com/2016/11/23/health/eli-lillys-experimental-alzheimers-drug-failed-in-large-trial.html
  2. Choi,D.W., Armitage, R., Brady,L.S., Coetzee, T., Fisher, W., Hyman, S., et al. (2014). Perspective. Neuron, 84(3), 554–563.