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The Top 6 Questions Directors of Informatics for Biologics R&D Struggle to Answer

Want to address these questions with a modern informatics platform? Check out our comprehensive eBook on What to Look for in an Informatics Platform for Biologics R&D.

The central goal of R&D informatics is to improve data integrity and accessibility to support intellectual property. This means minimizing manual data entry, eliminating data silos, and automating as many repetitive R&D processes as possible. This is particularly important in the emerging modalities of biologics R&D, where scientists work with many sources of complex data, and where even simple sequence discrepancies can kill patents. We spoke with Directors of Informatics across biologics R&D organizations to identify what’s top of mind for them, and what they’re struggling to answer with their legacy systems.

1. What’s the best way for us to go about automating R&D’s most repetitive workflows?

Automating processes is key to improving data integrity and accessibility, but figuring out how to actually go about it brings up numerous other concerns, even outside of gathering user requirements. Will our solution be too rigid to accommodate future changes in the process? How will our approach integrate with all our different software and systems of record? Should we build it in-house or rely on a vendor? When you’re dealing with legacy systems, data siloes, and biologics R&D, these questions are even harder to answer.

2. What siloed databases exist that cause scientists to do duplicative data entry?

In many ways, eliminating data siloes is part and parcel of automating workflows. A workflow surely can’t be called “automated” if scientists still have to manually enter the same data multiple times. Just tracking down which data siloes exist is a big endeavor in and of itself, especially if you’re working with an informatics infrastructure that’s been built up over the course of many years. Some data siloes might not even be immediately evident, when scientists store data locally or on a bevy of spreadsheets.

3. How should we integrate our software and hardware in the most helpful, intuitive manner?

Integrating your informatics systems with your instruments is a great way to cut down on manual data entry and improve data integrity. But if you’re dealing with data siloes and legacy systems, there are numerous additional concerns. What if your systems have prohibitively slow APIs? Are there multiple systems where an instrument should sync data, and how do you keep that data in sync across those systems?

4. What scientific questions can we not answer with our current systems?

In terms of supporting IP, empowering R&D decisions with data is a key goal for informatics. Drilling down into the questions that R&D can’t answer but wish they could isn’t straightforward, but regularly considering unsatisfied R&D insights is critical to consistently improving your informatics infrastructure. For Directors of Informatics working with legacy systems, software can often feel like it’s there just to “check a box” rather than to contribute towards a set of fundamental R&D insights.

5. How engaged are my users? Is our software actually generating value?

Let’s be clear: user adoption is not the end goal of informatics. After all, you can just make a system mandatory and see high user adoption. Instead of serving as the ultimate metric of informatics success, user adoption should be one of many indicators that an informatics system is generating value. If the system is doing its job, the usage will naturally follow. Unfortunately for Directors of Informatics, with certain systems, tracking usage rates is a tall order in and of itself.

6. How airtight are our permissions restrictions, legal structures, and security?

Ensuring regulatory compliance and enforcing security best practices is pivotal to a properly functioning informatics ecosystem. Legacy systems, point solutions, and locally-stored data confound attempts to regulate record-keeping practices. At best, R&D loses out on data, and at worst, the data itself is at risk. Without a central software platform that generates value at the scientist level, Directors of Informatics are left in the dark.

 

You can’t easily address any of these questions with scattered systems, legacy software, and tools that just weren’t built for biologics. The only way Directors of Informatics for biologics can get these answers quickly, confidently, and reliably is with an informatics platform purpose-built for large molecule R&D.

Ready to get to the heart of these questions with a modern informatics platform? Check out our comprehensive eBook on What to Look for in an Informatics Platform for Biologics R&D.

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