A recent survey of 100 United States senior regulatory personnel in pharma/biopharma suggests that the industry may be inhibiting its own progress with smarter resource management and transformed process efficiency because of outdated attitudes to artificial intelligence (AI) and machine learning.
While 97% of respondents had seen their regulatory obligations expand over the last five years, and 60% said the increase was “beyond what would be expected as the result of company growth,” and a similar proportion saw AI-powered automation as the answer to the escalating cost/efficiency problem, inertia appears to be holding many companies back from realizing that potential.
When asked about barriers to initial or further investment in AI for regulatory purposes, respondents most commonly cited outdated existing IT landscapes (45%); a belief that risks currently outweigh the benefits (44%); and inadequate availability/quality/ consistency of data or content resources to derive the value from AI (42%). Over a third (39%) felt the technology was still unproven; similarly, that the tools do not exist today to address their particular pain points. Sixteen percent blamed a lack of trust in AI. This was also ahead of budget challenges: only 15% named a lack of budget as a barrier.
By use case, almost all respondents could see direct potential for AI in addressing all of their identified pain points. These include labeling compliance and deviations maintenance; capturing, searching, and filtering the latest regulatory requirements; an intake of Health Authority interactions; managing regulated content translations for different markets; authoring responses to Health Authority queries; improving the success rate of submissions; performing regulatory impact assessments; authoring submission documents; and more.
What will nudge companies to act?
When asked what would trigger investment in regulatory-focused AI capabilities now or in the near future, respondents most commonly cited the discovery that their competitors are using the technology (41%), followed by continued resource pressures (40%); the technology being proven (36%); the availability of relevant tools (35%); and associated tech becoming easier/more affordable to deploy (33%). Endorsement or recommendation of AI by regulators would further inspire investment.
The good news is that all of the conditions to overcome hesitancy among regulatory functions regarding AI adoption, as well as the factors most likely to foster investment, are either already in place or imminent. This is likely to inspire gradual usecase-by-use-case deployment, yielding rapid, visible, and targeted results, which in turn will promote confidence and engagement.
Companies must get their data in order and stabilize their core systems, though, before they are in a position to reap the benefits of optimized processes—with the help of nextgeneration AI.
