2025 Trends: Investing in Clinical Data

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 are some trends we’ll see in clinical trials in 2025?

Das: Effective and well-designed clinical trials is essential for the commercialization stage, and particularly when it comes to making sure that the drugs and therapies, as designed and commercialized, are getting to the right patients, which means the links between the clinical stage and the commercial stage, that's becoming stronger, and the gap between those two things are becoming much less. The first area where we are going to see a lot of investment rightly, is in data strategy and in integration of data itself. First and foremost, the industry has to be prepared for increasing volumes of real-world data and real-world evidence getting integrated in a real-time process into measuring the effectiveness of trials, as well as adapting or modifying them. We're definitely going to see a lot more on data standardization. That's actually a problem. Before you can do AI (artificial intelligence), you need to get your data into order, check the quality of it, the governance of it, the updating of it, and so forth, so making sure that that organizations have enough data infrastructure to handle that sheer diversity of data sources, which, by the way, we see every day, the diversity of data sources, the unstructured nature of it, the non-standardization of it, can be a really, really huge problem. Then in 2025 I predict we're going to see a lot of investment, of course, also in patient diversity and inclusion, where you're strengthening strategies for diverse patient recruitment, looking at more decentralization so you can reach people where they're at, you want to reduce the barriers that a typical patient will face in getting to a trial and adhering to that regimen through the length of the trial. You're also going to see a lot on building relationships with underserved communities, and I think this is important in working with local health systems, with nonprofits to access the communities which might have a disease prevalence that isn't reflected. Last, but certainly not the least is regulatory preparedness. Regulations are getting more complex and more prescriptive and more demanding, but monitoring FDA guidance on novel trial designs and DCT approaches, staying current with international regulations, so that you have a very smooth commercialization process, as well as data privacy. As we use more AI to analyze data that has PHI and does not, making sure that you're able to actually align with those data privacy requirements, which is essential for trust is going to be very important. I could probably go on, but these are some of the key items that I expect to see a lot of progress being made on.