ACT: With Veeva’s 2025 Clinical Data Trend Report now available, what are some key trends in clinical data that you’re expecting to see this year?
Garty: We actually polled a very similar type of question to the industry, and had about 150 data manager and data leads come in and give us some answers, so of that fold, interesting enough, risk based everything, risk based data management, risk based monitoring is still at the top. We haven’t realized the full potential of really focusing on what matters most, i.e. risk based, right? We’re going to see more and more approaches and really that transformation. While we’ve been talking about it for well over a decade, we’re still realizing the benefits and in data management, we still hold on to perfection as king. We have to test everything, but there’s a newer generation really coming in, and as we focus on clinical data science and shift off of just traditional data management, we see now that shift is taking hold.
ACT: Why do you think so many stakeholders face challenges with the increasing complexity of clinical data? How can these concerns be addressed?
Garty: Historically, you had to think about the fact that we had humans entering data into a single system, and then we took that data and were able to do something with it, right? Traditional EDC, but now we have this proliferation of new instruments, diagnostics, personal devices, eCOA, we have nursing at home, all of these are different sources of data, and so our tools, EDC, was not prepared for that. What we instead needed to do is to actually automate that aggregation of all the data, unifying it together, cleaning it, and ultimately transforming it. It’s really the underlying tools that needed a major overhaul in the industry. The same is true when we get on to AI, for instance, if we don’t focus on the foundational tools, then we’re really adding complexity onto complexity, and in my life, that’s never led to simplicity, and simplifying, standardizing is really key for our industry going forward, so we do have to put an absolute heavy focus on underlying data foundations.