Rare disease drug development, which now accounts for nearly one-third of all drugs in active R&D worldwide, presents scientific and operational challenges that will accelerate the adoption of new development strategies and operating models, according to a recently completed analysis from the Tufts Center for the Study of Drug Development.
"Our research on rare disease development programs suggests that sponsor companies are encountering unprecedented operating challenges in this area,” said Ken Getz, associate professor and director of sponsored research at Tufts CSDD, who led the analysis. “Smaller market opportunities and longer development cycle times-driven in large part by difficulties identifying investigators and recruiting rare disease patients-will necessitate increased use of data and analytics and more flexible and mobile clinical trial models."
A rare disease that qualifies as an orphan disease is defined as a medical condition that affects 200,000 or fewer people in the United States, or fewer than five people per 10,000 population in the European Union.
The share of new drug approvals worldwide for rare diseases doubled from 29% of all approvals in 2010 to 58% in 2018, according to Tufts CSDD.
The analysis, summarized in the July/August Tufts CSDD Impact Report, released found that:
"Clinical trials for rare diseases have lower drop-out rates, compared to those for non-rare diseases. However, finding and enrolling study volunteers is extremely difficult," Getz said. "Benchmark data from recent clinical trials show that, in addition to long study start-up and enrollment periods, screen and randomization failure rates are much higher in studies among rare disease patients.”
To learn more go to https://csdd.tufts.edu
Driving Diversity with the Integrated Research Model
October 16th 2024Ashley Moultrie, CCRP, senior director, DEI & community engagement, Javara discusses current trends and challenges with achieving greater diversity in clinical trials, how integrated research organizations are bringing care directly to patients, and more.
AI in Clinical Trials: A Long, But Promising Road Ahead
May 29th 2024Stephen Pyke, chief clinical data and digital officer, Parexel, discusses how AI can be used in clinical trials to streamline operational processes, the importance of collaboration and data sharing in advancing the use of technology, and more.
The Rise of Predictive Engagement Tools in Clinical Trials
November 22nd 2024Patient attrition can be a significant barrier to the success of a randomized controlled trial (RCT). Today, with the help of AI-powered predictive engagement tools, clinical study managers are finding ways to proactively reduce attrition rates in RCTs, and increase the effectiveness of their trial. In this guide, we look at the role AI-powered patient engagement tools play in clinical research, from the problems they’re being used to solve to the areas and indications in which they’re being deployed.