Why you should stop working with multiple EDC vendors

If you are using a multi—vendor EDC strategy to handle your clinical studies, you are wasting energy. You may justify it as needing to serve different purposes or customers, if you are a CRO, or as a risk mitigation strategy. However, what you should be asking yourself is: why aren’t we using a system that fits all our studies? Let’s scrutinize why it’s so inefficient to work with multiple EDC vendors.

Investing in a relationship with your vendor(s)

Maintaining a healthy relationship with a vendor is critical to ensuring good service delivery, aiding in contract negotiations, and so on. When working with a single vendor, it’s possible to have a greater focus on these matters.

Another aspect is that by sticking to a single vendor, you are contracting more studies to them, which in turn makes you more relevant as a customer. Why is that? Because when more studies are at stake, your needs are prioritized (e.g., product enhancements or services, such as building a custom integration) and you are more likely to get volume discounts. Other advantages include: only having to perform a single system validation; reusing custom integrations; having in—depth knowledge for audits and inspections; and access to additional capabilities—when working with a platform—type of system.

Risk mitigation vs. risk reduction

Putting all your eggs in one basket might seem like a risky move; however, you should consider reducing risk rather than mitigating it. Common concerns revolve around data, specifically: hosting, security, and privacy. Spreading data across several vendors, won’t guarantee that it is in good hands, requiring additional time and effort to comprehend different policies and to manage oversight.

So how can risk be reduced? Choose a partner you trust and that has control over the data. Think about who is really controlling the data. What are the consequences of a vendor that cannot fight against a cloud provider who has the power to change the “rules of the game”? Wouldn’t it be reassuring to work with a vendor that actual owns the cloud where data is stored?

Enabling your team

Have you considered how much effort is invested to get your team(s) enabled in multiple systems? Either your whole technical team must learn all of them, or you have specialized team members. The first option translates into a large time investment, while the second means you will have product-specialized teams that are harder to replace, leaving you without cross vendor support when needed. Also, non-functional knowledge is required for audits and inspections, often requiring answers from vendors—the more vendors you work with, the more knowledge needs to be absorbed. Moreover, system enablement is not done once. Teams need to keep updating their knowledge as systems evolve.

All steps—initial enablement for new team members, keeping up to date with system evolution, and maintaining other non-functional knowledge about the system/vendor—would be easier if your team only needed to work with a single system.

Adjusting to different data outputs

The pain of constantly dealing with different data outputs is real. Whether you are a statistician, data manager or clinical programmer, you not only need to consider protocol specifications and comply to company (or customer) standards, but you also need to adapt to each system output format. This requires knowledge, resources, effort, and above all time! Additionally, quality is more at risk when so many factors need to be considered.

Here in lies the beauty of using a single EDC system: the output is always the same! That means that your team can focus on the study specifications and industry standards, on top of reducing the timelines for study closeout. Ultimately, this allows pharmaceutical companies to get drugs to market faster.

Final notes

Stop using different EDC systems that serve different needs and start looking for a vendor that can support all your studies—no matter which type, phase, or size. Choose a vendor you can trust and to whom you can trust your data with.

Remember: you should not be adapting to different systems; a system should be adaptable to you!

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