TIEDE: I've actually challenged my group to say, "As for deploying EDC, if we have a standard on-the-line data architecture, based
on what the investigator does on the screen, does it always have to be the same? Or can we meet the customer needs by customizing
the screen for them so that they can get at the information in a way that's friendly and useful for them?" In the future,
we have the potential to make this investigator-friendly. It's going to be a challenge because it puts a burden on our shoulders,
but at the end of the day, it can well increase the acceptance and the overall use in the investigator community.
The phases of clnical trials are blurring. For example, certainly at FDA, Phase II is sort of splitting into IIa and IIb.
What is it going to take to get us to the point where you can use EDC to have visibility across the entire development process?
OLSEN: I spent a lot of time in our Phase I team. I actually was leading the charge to bring EDC into that realm. At BMS, we're
using the same EDC tools across Phase I to Phase IV. It was the data visualization that was the biggest challenge. People
were used to looking at the data in a paper format, so when we came in with EDC, they didn't know what to do with it. Once
we got into it and brought the data in near real time and were able to block a database at the speed of light, they finally
said, "Wow, this really works."
Still, although we're progressing, some people are still skeptical because they still haven't seen what the results might
be at the end to become believers. But there are so many experiments, you can show the types of powers that EDC can do. That's
one of the hats I've been trying to wear in that space.
EDC is really good at stopping errors from entering the system. So why are there still delays in getting results?
OLSEN: What we have found, in some cases, it's another dataset that is now on a critical path. It's not the eCRF dataset. You've
been able to lock that, but you're still waiting for some loaded data that's coming from an analytical laboratory. You've
exposed another weakness in that activity that went on to get to data log.
CHIN: It still comes back to integrating all the relevant data, you know, at the end. It's not just the patient data.
BROWN STAFFORD: Well, because we're waiting to integrate the data at the end, that's when we're doing some of the cleanup. That's what takes
time, because we locked an eCRF database in nine days after last patient/last visits. And then we had to sit around a few
days, because we ended up having to clean up some other database and then put them together and do a merge. You find a few
errors here or there, things that didn't match. So even though you had the "wow" out of the EDC, you didn't have the overall
impact you wanted because of the other things we found.
Clearly there are still many challenges as you continue to implement EDC in your companies. There's a challenge for you as
leaders to help your team make a collaborative effort toward your end goal, and there's a challenge to tap into that enthusiasm.
Can you share some lessons with other companies to help them move these initiatives forward? That's so necessary in encouraging
VAILLANT: If history is any predictor of the future, three to five years from now we'll be very happy if we're successful in our role
for EDC. Looking idealistically and more optimistically in the future, the different integration of data sources is key. Moving
forward with that integration through data warehousing and some other mechanism is going to be important, and that will be
the next step forward.