How regulatory intelligence leads to real-time strategic decision making

by Jared Kimble

Data is all around us. It’s created with everything we do. For the life sciences industry, this means data is being collected faster and at a greater rate than ever before. Data takes the form of structured content — from clinical trials, regulatory filings, manufacturing and marketing, drug interactions and real-world evidence — with regard to how drugs are used in healthcare settings. It also is found in unstructured content from the internet of things (IoT), such as social media forums, blogs and so on.

But having massive quantities of data is useless without the regulatory intelligence to make sense of it. Let’s define what we mean by regulatory intelligence. This is about taking multiple data sources and feeding those into a regulatory system that can look at the data, analyze it, make use of it, collect information from it, then take that information to distribute it where it needs to go. This might be to the regulatory agencies requesting updates or information about the drug portfolio to satisfy compliance mandates, it might be to partners that you’re working with, such as trading partners, or it might be consumed internally.

Although referred to as regulatory intelligence, it encompasses many other areas of the product life cycle, including clinical research and development for detailed analysis and safety and pharmacovigilance for signal detection.

Life sciences companies can leverage these different types of data for real-time decision making to protect public safety, respond to supply shortages, protect the brand, advance the brand — for example, into new indications or new markets — and for many other purposes. In this blog, I’ll explore some of these uses of regulatory intelligence in greater depth.

Know your target

Since data is consumed across the life sciences in different ways by different people and different functions, getting to the point of intelligence first requires knowing the target and objective. If there is real-world data indicating adverse events that weren’t detected in clinical trials, having that intelligence early on allows companies to act accordingly — both to protect public safety and to safeguard brand reputation. What action the company takes will depend on what the data shows, as well as what the agencies require. For example, it might simply be to reinforce a message about avoiding other medications or foods while undergoing a specific treatment or it might require a broader response.

Another way data can be leveraged for real-time strategic decision making is to advance the brand. For example, IoT data or data held by the authorities might show weakness in a competitor’s product or weakness in the market — perhaps a gap in a region the company has begun targeting. By leveraging that intelligence, companies can take advantage of those gaps or competitor weaknesses and promote their brand as a better alternative or prepare a new market launch.

Regulatory intelligence might also shine light on other potential indications for your product. These insights might be gathered from IoT sources, such as physician blogs, or from positive side effects observed in clinical trials. The most famous example is Viagra, which initially was studied as a drug to lower blood pressure. As was the case here, not all side effects are negative, and during clinical studies an unexpected side effect led to the drug’s being studied and ultimately approved for erectile dysfunction. Having that regulatory intelligence available gives you the leverage to make the case for expanding clinical studies into new indications and extending therapeutic use.

From data to intelligence

Now that we have explored the definition of and some purposes for regulatory intelligence, we should also look at how you get from that point of data to intelligence. An important first step is to deploy the right analytical tool to sift through that data and pull out relevant information. It’s equally important to know how to make use of that data, and that requires knowing your end goal and narrowing the scope of your data search to eliminate extraneous data.

Time and resources can also be saved by leveraging automation to collect data for analysis. Since data is continuously being created, updated and pushed out, automated robotic processes make it possible to keep up to date with the latest findings and pull relevant data into your regulatory operational environment.

Regulatory intelligence is the key to real-time strategic decision making across all areas of research and development. Its importance to the organization can’t be overstated.


Jared Kimble has over 14 years of experience in the life sciences industry. His expertise ranges from software design and development to solution architecture where he is currently the offering lead for Life Sciences Regulatory Transformation Services. He leads the management and development effort for many key projects and was involved in several on-site engagements. Before joining DXC, Jared worked as a software engineer developing applications dedicated to providing financial exchange services for banks and financial institutions.

 

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