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Data enablement and digital business models

Get your regulatory data ducks in a row

With Christopher Lucas, Consulting Director US Research & Development, NNIT Inc.

Global cooperation between health authorities and increased focus on structured data reporting are just two of the regulatory trends impacting pharma companies. Christopher Lucas, Consulting Director US Research & Development, explains how digital solutions can enhance regulatory data.

Regulatory submissions are a critical and often resource-intensive part of any life sciences business. While digital data processing and international standards for codifying and structuring information have eased the burden to some extent in recent years, there is still plenty of room for improvement when it comes to reducing manual processes and streamlining cooperation with health authorities.

– Getting products approved faster is a top priority for most pharma companies. And faster time-to-market often boils down to being able to efficiently compile and interpret regulatory data and present them to the relevant authorities in the correct format, says Christopher Lucas, Consulting Director US Research & Development at NNIT Inc.

The challenge is that regulatory staff are still spending excessive amounts of time on manual data entry, compiling data sets and keeping track of the shifting requirements of global health authorities.

A regulatory perspective on data enablement  

The regulatory tasks in a pharma company are usually divided into these areas:

  • Regulatory Operations: Gathering and formatting regulatory information for submission to authorities like the FDA and the EMA, answering requests for clarifications, etc. This includes post-market surveillance and safety activities, such as annual labeling reviews and updates.
  • Regulatory Intelligence: Keeping your sponsor organization updated on the latest requirements from health authorities, based on the review and interpretation of commitment letters, meetings and open-for-comment periods.
  • Regulatory Strategy: Identifying which markets to target first for product approval and which pathways to follow, based on your regulatory intelligence and product portfolio.

To successfully get products approved, your organization has to master all three areas. According to Brooke Casselberry, digitalization and data enablement hold significant potential to enhance each area.

Structured content authoring is gaining momentum

For regulatory operations, one of the most promising trends is structured content authoring, which will enable more regulatory data to be codified according to detailed standards and submitted electronically. This is not a new technology, but recently the FDA and other authorities have invested heavily in being able to receive and process structured data.

– Today, much of the data from clinical studies and post-marketing activities are still compiled into Word and PDF documents and sent to the relevant authorities. From both sides, there have been significant efforts to enable compliant and well-structured transmission and reception of that data in raw form, says Christopher Lucas.

Initiatives focused on structured content authoring include ISO’s Identification of Medical Products (IDMP), the EMA’s Digital Application Dataset Integration Project (DADI) and the FDA’s Structured Product Labeling. Despite these efforts, there is still not one universally accepted standard for regulatory information. This means that pharma companies have to stay alert and up to date regarding the data requirements.

– There are several advanced solutions which support structured content authoring available to pharma companies today. But since the various health authorities deviate a little from the large standards in their requirements for data submissions, you need different data modules in order to comply with each authority, says Christopher Lucas.

AI-assisted regulatory intelligence

Technologies such as artificial intelligence (AI) and natural language processing (NLP) can be extremely useful for regulatory intelligence. For example, regulatory staff can use NLP to process the vast amount of information from health authorities faster and more efficiently.

– Some info from the FDA and other authorities is extremely critical, but a lot is non-essential. For example, in a product negotiation for approval, you might discuss how a clinical site being shut down and people having to work from home affects the trial. Being able to identify and flag critical points and evaluate their impact is very valuable, Christopher Lucas explains.

Concurrent global reviews

Structured digital distribution of regulatory data, global standards and cloud-based review tools are also impacting how international health authorities cooperate on product submissions. Until now, pharma companies have been used to applying for approval from market to market. But we are now seeing examples such as the FDA-initiated Project Orbis, which provides a framework for concurrent submission and review of oncology products among international partners.

This increased cooperation means that a product could potentially be approved for multiple markets at the same time, which impacts the sponsor organizations’ production, distribution, marketing and supply chain.

– If you get a product approved for several markets at the same time, you have to keep track of all the relevant variants, such as labeling requirements, restrictions on additives and packaging variations. To do this, you need a robust and well-integrated regulatory information system. If you have to manage all this using a spreadsheet, then you’re in trouble, says Christopher Lucas.

Want to know more about how your organization can work with data enablement, digital business models and processes, and new agendas?

Read the other articles where NNIT experts share their concrete experience and advice for different aspects of the life sciences industry.

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