Duration: 30 minutes
Date: 2/24 10am ET, 4pm CET
Speakers: Chiara Rodgers, Radha Mawrie
The lack of demographic representation in clinical trials in the US and beyond is long felt and a well-known challenge for the research community. Most clinical trials struggle to track and find the relevant data.
For some examples specific to the US:
- African Americans make up 13.4% of the U.S. population and 5% of study participants
- Latinos comprise 18.1% of U.S. residents yet make up less than 1% of clinical trial participants.
- Women are nearly twice as likely as men to experience adverse drug effects, a problem linked to the fact that not enough women are participating in clinical trials, leading to a lack of insights into how therapies will uniquely affect women.
Advanced data-mining approaches and using technology to ease the patient experience can help break down these obstacles to truly representative enrollment. By employing data science in some key ways, we can improve awareness and access for under-represented groups.
Key Learning Points:
- Knowing Your Patients –While personal data remains unseen, demographic information and insights into patients can be used to form effective strategies which are more likely to reach a diverse patient population.
- Planning for diversity: Thinking about the demographic needs of a study earlier on and employing bespoke strategies from the beginning of the recruitment push can help maximize representation and probable eligibility.
- Think Early About Patient Experience: Keeping things focused on the patient and their communities can help simplify the experience which is an incentive for participation and a great way to maintain retention.