July 1, 2024
by Catherine Finley

Artificial intelligence-enabled solutions and regulatory strategy

Introduction

For life sciences, the strategic integration of artificial intelligence (AI) offers an unprecedented opportunity to streamline processes and expedite time-to-market.

From a regulatory perspective, AI is positioned to potentially accelerate drug approval. This benefits both the companies developing new therapies and the patients whose lives can be transformed as a result. Currently, the average journey from discovery to market takes 12 years; even a marginal improvement can have a profound effect on patients’ lives.

To be effective, however, AI must be applied precisely to purpose and guided by human expertise. In this article, we’ll discuss how life sciences companies and the patients they serve can benefit from this transformative technology.

The big-picture promise of AI

Regulatory approval runs on data and lots of it. As life sciences companies craft regulatory strategies, they must interrogate countless documents, many of which are incredibly dense, to understand how similar or in-class drugs gained approval or failed to get approval.

For example, teams launching products in the US and EU need to query key documents from the US Food and Drug Administration (FDA) and European Medicines Agency (EMA), labels, clinical trial data and published literature. Of course, those sources are disconnected from one another, and relevant new documents are constantly being introduced.

AI-enabled platforms promise to streamline this process, helping companies gain efficiencies and make optimal use of limited resources. Research has shown that digitizing and automating regulatory processes could accelerate time-to-market by nearly 10%, according to ZS, a management consulting and technology firm.

Pain points AI addresses

Generating landscape intelligence has been an ongoing challenge for regulatory teams, whether they are launching a new product, expanding an indication or seeking to better understand the competitive landscape. The varied format, length and density of document sets, as well as differences among health authority approaches globally, make the process incredibly time- and labor-intensive.

When AI is leveraged as part of a domain-specific, fit-for-purpose platform, generating landscape intelligence can shift from a manual process taking days or even weeks to an automated process taking minutes. Tools that fit into existing workflows offer even more dramatic efficiency gains.

Key application and use cases

AI-enabled domain-specific solutions promise to generate dramatic efficiencies in regulatory approval by streamlining the generation of relevant market intelligence for competitive or similar in-class drugs – this is a key application.

Before introducing new therapies or indications, life sciences companies need to conduct robust landscape analysis. Depending on the lifecycle phase of the product, market intelligence needs vary.

For example, as Lyn Hopkinson from CoRA Consulting, LLC, indicates, early in development, users will be casting a wide net to understand the optimal product profile, seeking insights at the therapeutic area level for similar or in-class drugs to identify questions they will need to answer throughout the entire development program (e.g., appropriate dosage and administration and Phase 2 and Phase 3 endpoints). In later stages or if a product is approved, then questions will be more specific to competitive drugs, relating to post-marketing safety concerns, other indications or other dosing regimens to pursue.

AI-enabled tools can take on routine, time-consuming tasks, enabling users to focus on higher-level strategy. That’s true whether the use case is supporting the development of regulatory strategy documents, informing original or supplemental submission strategies, preparing for health authority meetings, answering ad hoc questions from health authorities or colleagues, or engaging with clinical development colleagues on the development program.

‘Augmented intelligence:’ The intersection of AI and human expertise

Although this article has talked a lot about artificial intelligence, a more appropriate term (and the one Dr.Evidence uses) is augmented intelligence, which means using artificial intelligence to complement, not replace, human intelligence. “We don’t treat AI as an autonomous, indiscriminate force,” said Rose Higgins, CEO, Dr.Evidence. “Instead, we wield AI as a precision tool, carefully selected and expertly applied based on our deep domain knowledge.”

Deep knowledge and extensive experience in evidence-based scientific research and guideline development is a powerful foundation for applying augmented intelligence to regulatory projects and tasks. That combination empowers users to replace labor-intensive processes with efficient, effective workflows, enabling them to operate at peak capacity and make the maximum strategic impact.

In the augmented intelligence realm, AI operates behind the scenes to enhance efficiency and precision and in the user interface to enable clients to directly access scientific content and receive rapid, accurate answers. Generative AI embedded in a solution requires a collaborative approach, educating clients and guiding them with the tools to narrow their search to a specific set of documents. Then, AI’s power is unleashed on that refined document set, creating a true partnership between humans and AI.

“We firmly believe that human expertise remains a vital component in the quest for the most relevant results,” said Higgins. “Whether through generative AI or machine-learning models, AI is a collaborator, requiring expert human guidance and amplifying human knowledge with accurate scientific answers.”

Conclusion

Like countless other labor-saving innovations, AI-enabled solutions have the potential to free humans from repetitive, time-consuming, resource-intensive tasks so they can focus on higher-level strategic work that only humans can deliver. Learn more about how Dr.Evidence empowers regulatory teams with fit-for-purpose technology to generate the landscape intelligence needed to help them get vital therapies into the hands of physicians and patients in the most efficient manner possible.

Catherine Finley is Senior Vice President at Dr.Evidence
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