Regulatory information management in life sciences

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Point of view

Published

October 16, 2025

A system is not the only solution

Facing an increasingly complex regulatory landscape, life sciences companies have tried to centralize data to be more responsive to regulatory challenges. Many have invested in regulatory information management (RIM) systems to unify data and processes.

 

However, data systems are only as good as the data that goes into them, meaning a system is not the only solution.

The RIM investment paradox

Many RIM systems still rely on incomplete, inconsistent, and poorly structured legacy data. And according to the 2024 World Class RIM Study by Gens and Associates, only 10% believe their data is of high enough quality to support those systems.1

 

So, while technology investment is high, data readiness is lagging. That gap is costing time, money, and competitive advantage.

Why RIM systems are falling short

Historically, regulatory data has lived across multiple disconnected systems, managed by siloed teams and riddled with inconsistencies. Different departments used different formats, terminologies, and processes. Manual updates and workarounds were common, and standardization was rare.

 

When it's time to migrate this data into a unified system, the cracks show:

 

  • Data misalignment: Different systems represent the same data – like products, submissions, and changes – in conflicting ways, resulting in data standardization issues

  • Missing attributes: Fields needed in the new system may not exist or are inconsistent on older platforms, requiring a plan to extract the data from another reliable source

  • Outdated content: Many records are poorly maintained, resulting in duplicate and inaccurate entries

  • Inadequate preparation: Migrations are rarely delivered on time, as teams often underestimate the complexity involved in cleaning up legacy systems

     

This creates a perfect storm: expensive systems that may not perform as promised, regulatory delays, and frustrated users. And the cost of fixing these problems after going live can be higher than addressing them proactively.

The human cost of poor data

Regulatory data challenges aren't just operational issues. They have a direct impact on many people.

 

When data is fragmented or unfit for use, skilled regulatory teams spend more time checking data and fixing problems than moving forward. This quickly erodes trust and reduces user acceptance in the new system meant to support them.

 

Beyond internal teams, delays in data readiness, a slow time to market, and limited access to patient therapies weaken confidence among regulators, partners, and healthcare providers.

Five ways industry leaders do more with their data

Successful organizations don't wait until a regulatory deadline approaches to address the problem. They're embedding data quality, governance, and stewardship into the DNA of their regulatory operations.

 

Here's how:

 

1. They begin with data governance

 

High performers start by defining clear data ownership, standardized policies, and lifecycle controls to make sure data is captured, maintained, and used consistently across markets, functions, and systems.

By considering global regulatory standards from the start, these organizations build lasting trust in their regulatory data.

 

2. They standardize data companywide

 

Rather than relying on ad hoc fixes, leaders follow companywide standards, including naming conventions, data catalogs, and reference data rules. This prevents duplication and supports interoperability across regulatory, clinical, and supply chain teams, simplifying submission processes.

 

Whether it's responding to a new marketing authorization application or a maintenance activity, the data behaves consistently.

 

3. They conduct deep data assessments

 

Instead of "lifting and shifting" data into new systems, high performers map every area – registrations, labeling, packaging, safety, and more – against future needs. They assess data completeness, identify gaps, and benchmark quality against regulatory and system requirements before migration.

 

This gives them time to plan enrichment efforts in a structured, scalable way.

 

4. They continuously review and improve

 

Once the RIM system is live, the work doesn't stop. Leaders define key performance indicators (KPIs) for data quality, monitor dashboards, and proactively resolve issues.

 

Using repeatable, often automated processes, these organizations enrich data to make it not only compliant but also business-ready. They validate content against business rules and regulatory criteria, so data is accurate, relevant, and fit for reuse.

 

This data housekeeping means data remains trustworthy over time.

 

5. They use proven AI and analytics

 

AI and analytics aren't just buzzwords – they're essential tools. From anomaly detection and automated extraction of structured data from documents to real-time risk alerts, advanced tech accelerates compliance, drives insight, and powers smarter decisions.

Regulatory information management in action

A global life sciences company needed to move 2.5 million regulatory records from 16 outdated systems to a single new platform. The data was messy – spread across spreadsheets, PDFs, and outdated software – with lots of gaps and inconsistencies.

 

Genpact led the entire process following our data compliance framework (see figure). We prioritized, organized, and cleaned the data, filling in missing information and setting clear rules to standardize everything. Tools like AI-powered data mining helped extract key details from a variety of documents.

 

The result was a smooth, on-time launch with high-quality data, ready for faster submissions, fewer compliance issues, and evolving regulatory requirements.

Genpact's data compliance framework

The ROI of getting regulatory data right

Keeping pace with regulatory changes is tough, but it's a nonnegotiable – and the benefits speak for themselves. With high-integrity data, life sciences companies can:

 

  • Accelerate regulatory submissions and reduce review cycles

  • Improve audit readiness and regulatory responsiveness

  • Lower operational costs using automation for data reuse and readiness

  • Support continuous innovation with AI, machine learning, and analytics

  • Build a data foundation for long-term compliance and growth

     

In short, world-class regulatory data isn't a dream. It's a decision.

Start the data detox, accelerate your advantage

The message is clear: in life sciences, regulatory compliance starts with data you can trust.

 

That means thinking beyond launching a new system. It means investing in data governance, enrichment, and stewardship for quality and accountability at every stage of the RIM journey.

 

Do that, and regulatory data becomes more than a compliance requirement. It becomes a competitive advantage.

 

 

1. Gens and Associates Inc., 2024 World Class Regulatory Information Management Study Whitepaper, 2024

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