Technology’s Role in Trial Design Optimization

In a recent video interview with Applied Clinical Trials, Dipanwita Das, CEO & co-founder at Sorcero, discussed advancements and future trends in clinical trials. Key challenges include high costs, long timelines, lack of diversity, and rigid protocols. Das highlighted technological advancements such as AI, real-time monitoring, and historical data analysis, which are all expected to optimize trial design and patient recruitment in 2025 and beyond.

ACT: What types of technology do you think clinical research experts can benefit from the most in their goal of improving patient outcomes?

Das: Technology, of course, is a huge role in transforming all of this, artificial intelligence (AI) certainly, but I think in the next one or two years, trial design optimization is where I'm excited to see the use of more historical data at scale, particularly to optimize inclusion/exclusion criteria, use of AI, and better data science and EHR analysis for patient recruitment, making sure they're actually covering all of the patient populations that need to be represented. Better real-time monitoring: real-time monitoring is just really, really difficult right now, so making sure that there is a certain degree of automated detection of data quality issues, etc., and of course, using AI for literature review protocol writing, as well as automating documentation. In the medium to long term, there are lots of other spaces in which AI and technology overall will play a huge role, from synthetic control arms to adaptive trial designs as well as digital biomarker developments, or even the idea of in silico trials, so there's a lot of exciting things coming up, but I think in the next one to two years, optimizing design, recruiting patients, and real-time monitoring is going to go a long way.