Webinar Recap: Applying Advanced Analytics to Overcome CNS Trial Challenges

If you missed Signant’s webinar on applying analytics to CNS clinical trials, you’re in luck – we’ve summarized the key takeaways for you.

Metis Cognition’s Principal Consultant, Dr. John Harrison kicked things off by discussing the continued use of the MMSE for testing a potential study participant’s memory for the following inclusion criteria: the individual has a rescuable deficit, can complete selected measures, and potentially show treatment response. Harrison argues that this test alone does not include all the cognitive facets needed for a comprehensive understanding of a CNS condition like Alzheimer’s disease.

Karuna Therapeutics’ Clinical Scientist, Dr. Colin Sauder, followed by discussing the growing problem of placebo response and corresponding decrease in treatment effect. By looking at endpoint data and quality indicators, teams can identify problematic sites and act to protect endpoints.

Dr. Alan Kott, Signant Health’s Data Analyst Practice Leader, closed the webinar by discussing how 27% of visits are affected by data quality issues. In regards to data analytics, Dr. Kott reflects that the industry has made great strides with the adoption of electronic data collection methods, but credits machine learning capabilities for the industry-wide paradigm shift in conceptual thinking when it comes to analytics. Clinical researchers, who were once limited to reactive actions, are now able to identify future data issues and intervene before the data is even collected.

In summary, CNS clinical researchers need to:

• Assess all relevant cognitive domains
• Employ reliable, sensitive, and valid measures
• Select measures according to expected effects, not habit
• Mitigate placebo response by identifying problematic sites early via a Blinded Data Analytics solution

You can watch the recorded webinar.