[Ask the Expert, EDC, clinical data, clinical data management, clinical trials]

SDC Insights: The Most Common Bottlenecks in Study Startup with EDC Database Builds


Employee Headshots (7)In this post, we talked with Todd Bonta who joined SDC in 2021 and serves as Vice President of Clinical Data Management.  Todd has over 22 years of experience in CDM spanning all phases (I-IV) of clinical research. 

We asked Todd about the most frequent bottlenecks he sees in study startups as related to EDC database builds as well as future trends he sees in clinical data management.

Todd: The biggest bottlenecks, or “barriers” to speed and delivery of an EDC database are situations where SDC engages with a study sponsor on a study but there is uncertainty about what data needs to be collected for the protocol. Our team will start discussions with the sponsor to build the appropriate case report form (CRF) but it’s not uncommon for a clinical team to request multiple amendments to a CRF before deciding on the final version. This can be an unnecessarily lengthy process if we don’t have the right people with the right expertise engaged here.Connect with Us

A second area where I see bottlenecks is when we are starting the data point definition too early before the final protocol is approved. If the protocol is still in revision, and we are trying to determine data collection points, it’s a difficult situation. Protocol complexity can vary greatly and so flexibility is always important however, if the sponsor finds themselves amending the protocol throughout the database implementation, that is troublesome.

The ideal process is that we have a final protocol, agreement on CRF design, proceed with database development, and then we share the initial version of the database with appropriate team members (SDC, sponsor, clinical teams, etc.) for a full review and feedback session.

I've also found that having an experienced lead clinical programmer, database architect, or CDM demonstrate the database and functionality to the customer is incredibly helpful to building a constructive and trusting partnership.

When the entire team can see the database and interact with it, it’s a very different experience than reading the specs in a document and trying to interject input.

🗨️  How early in the process should this happen? Can you enroll patients and collect data before your database is considered finalized?

Todd: Certainly, you can. The database really isn't a requirement to enroll a subject. Unfortunately, I have seen some sites use that as a milestone to drive their ability to begin participation, but I think that's generally a myth. Sites can enroll and treat subjects. They can administrate according to the protocol and collect information on their source documents. Their source documents are not the database, it's a rare scenario where sites are entering data directly into the EDC system as the source. They're collecting that source prior. Admittedly, it isn't ideal to not have a database ready before subject enrollment because you don't want a backlog of source records but certainly, a site can enroll a subject, begin data collection, conduct screening, and perform site visits.

The best practice is to collect data per the protocol. Sites know the protocol, their patients, visit schedules, and assessments required. If they collect data according to the protocol, they have everything they will ever need for that final database.

Then, if the database is implemented shortly thereafter, it’s unlikely to interrupt data integrity.

One of the things that make the SDC team so good is our ability to be flexible, nimble, and our responsiveness to making necessary changes. Clinical trials can be very complex, and we can't always anticipate the patient experience.

With very complex protocols such as those in rare disease or oncology studies, we expect revisions. The challenge is timeline management around those revisions and helping clients understand that, too.

We always keep a sharp eye on timelines and our objective is to get to 98% database finality allowing 2% for revisions.

 🗨️  How long does it take generally to build a database for a very complex protocol?

Todd: As an example, for an initial oncology study, getting a database into production can take up to 12 weeks including the development of the edit specifications. If we are working on a subsequent study for a client then it can take less time if we are able to pull from foundational work and because we already understand their specifications and collaborative style and reporting needs.

🗨️  What are the most important things you look for when hiring and building your data management teams?

Todd: Sponsors really like seeing the right therapeutic indication in their team’s background however from strictly a data management perspective that is less important to me than the team leader’s strength in diplomacy and consensus-building while driving the technical process. In the end, we want a database based on everyone’s feedback that is in concert with their expectations.

🗨️  What are some trends and innovations that we should be excited about?

Todd: The first thing that comes to mind is this new world of real-time data collection using wearable sensors. Think about the diabetic wearing a continuous glucose monitor that sends health information to their phone. Harnessing that data will tell us a lot about that patient’s management of their diabetes or their inability to manage it. Now consider that data is subsequently being collected in a larger clinical database. This provides researchers with an incredible amount of highly valuable information to analyze and build new scientific discoveries from. This is possible today, and I look forward to watching these innovations continue.

Another area to be optimistic about is the health-based technology market. We all know about apps monitoring users’ steps and movement. Apple watches even monitor cardiac functionality and alert users to potential heart conditions. That's valuable information to the individuals as well as the larger clinical trial arena.

Technology is expanding even to the ability to not just monitor but to deliver medicines automatically for chronic conditions.

Finally, we should be excited about remote source monitoring. Our world has changed in terms of the ability to get out and meet on-site with people directly to monitor data against the source. Now, there are electronic source data repositories and management systems that allow source records to be deidentified and uploaded so verification of the source record can happen remotely. Obviously, some site visits will still be required, but that methodology allows clinical teams to monitor data remotely and cover much of the effort before we get on site. This also translates to less time once there, fewer visits needed which can mean less cost.

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