{"id":9402,"date":"2024-12-01T19:01:17","date_gmt":"2024-12-02T00:01:17","guid":{"rendered":"https:\/\/lifescivoice.com\/?p=9402"},"modified":"2024-12-04T11:33:34","modified_gmt":"2024-12-04T16:33:34","slug":"the-now-urgent-automation-agenda-out-of-control-regulatory-workloads-necessitate-ai-adoption","status":"publish","type":"post","link":"https:\/\/lifescivoice.com\/the-now-urgent-automation-agenda-out-of-control-regulatory-workloads-necessitate-ai-adoption\/","title":{"rendered":"The now-urgent automation agenda: out-of-control regulatory workloads necessitate AI adoption"},"content":{"rendered":"

A new independent survey of senior US pharma regulatory professionals suggests that commitment to AI investment is much higher than might be expected, although some outdated perceptions could be impeding progress. ArisGlobal\u2019s Renato Rjavec reports.<\/em><\/h3>\n

That regulatory workloads are soaring across the international life sciences industry is well acknowledged. A new survey, conducted for ArisGlobal by Censuswide with senior regulatory professionals in US pharma and biopharma organizations, confirms not only that almost all have seen their regulatory obligations expand over the last five years, three in five (60%) put the increase beyond what would be expected as the result of company growth<\/em>. A trend that is not showing any signs of waning.<\/p>\n

It is why the industry is turning purposefully now toward artificial intelligence (AI), and in particular next-generation technologies such as Generative AI (GenAI) powered by large language models (LLMs), albeit with some lingering reservations about their current potential.<\/p>\n

AI\u2019s role in the regulatory function<\/h3>\n

The good news is that there is now widespread acceptance of AI\u2019s potential usefulness in solving information or process bottlenecks in a regulatory context, with 96% of survey respondents citing its current or potential value here, and almost half (45%) describing AI as \u201cvery useful\u201d.<\/p>\n

By use case, almost all<\/em><\/strong> respondents could see direct potential for AI in addressing identified pain points. The most popular proposed use cases included transforming labelling compliance and deviations maintenance; capturing, searching, filtering the latest regulatory requirements; automating the intake of Health Authority interactions; automating regulated content translations for different markets; automating the authoring of responses to Health Authority queries; suggesting improvements to submissions\/dossiers; performing regulatory impact assessments; authoring submission documents; automating document summarization; and generating entire regulatory submissions.<\/p>\n

What\u2019s more, over a third (35%) of respondents claimed to be using AI for regulatory purposes in some form already, while 42% plan to invest in the next 18 months. A further 15% are looking at a timeframe beyond that, but also have plans to roll out AI within the regulatory function.<\/p>\n

Inertia is still evident<\/h3>\n

Inertia is still evident, however, and this could be impeding companies\u2019 ambitions for process transformation. Asked what, if anything, was inhibiting<\/em> 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%).<\/p>\n

In addition, 39% of respondents felt the technology remained too immature\/unproven; similarly, that the tools do not exist today to address their particular regulatory pain points. Sixteen per cent blamed a lack of trust in AI currently. This was ahead of budget challenges: only 15% named a lack of budget as a barrier to AI investment.<\/p>\n

Drivers of change<\/h3>\n

Asked what would prompt new or additional investment in regulatory-focused AI capabilities now or in the near future, respondents indicated the discovery that their competitors are using the technology (41%); unsustainable further rises in workloads or resource pressures (40%); a maturing of the technology (36%); the availability of specific tools geared to the tasks regulatory teams find most challenging or expensive (35%); and relevant IT systems becoming easier and more affordable to deploy (33%).<\/p>\n

Beyond those drivers, 31% said updating their upgrades to existing IT set-ups (making it possible to use AI reliably) would prompt investment. Endorsement or recommendation of AI by regulators would inspire investment also for just under a third of respondents.<\/p>\n

By contrast, budgets do not appear to be a barrier to investment plans: just 18% indicated that the availability of new budget would unlock AI investment. This is encouraging, since hesitancy linked to \u201ca lack of confidence to deploy\u201d is readily addressable today. AI technology, including Generative AI (GenAI) is advancing at an accelerating pace, and specialist applications for target use cases in a life sciences regulatory context are being actively piloted today, showcasing what is possible.<\/p>\n

Looking ahead, the survey asked for respondents\u2019 expectations of AI in a regulatory environment over the longer term. Almost half (48%) of respondents agreed that, in due course, AI would transform a lot of routine regulatory work and considerably streamline processes. Over 2 in 5 (43%) felt AI would drive up accuracy and quality in the information they produce for regulators and patients. Almost 2 in 5 (39%) respondents believed AI would be critical to the regulatory function\u2019s ability to keep pace with market demands. And over a third (35%) of respondents agreed that AI would save considerable time and money.<\/p>\n

Taking action<\/h3>\n

Finding a targeted use case to test what the technology can do is a practical way forward for companies keen to move forward now and gain a process advantage. Taking an agile, incremental, use-case-by-use-case approach to GenAI deployment will be faster, and represent lower cost and lower risk, than a big-bang \u201cAI project\u201d. It is also more likely to build engagement, as specific incremental wins are demonstrated.<\/p>\n

Whether companies are exploring AI in earnest for the first time, or looking to increase the technology\u2019s usage and impact, however, they must first get their data in order and stabilize their core systems, so that they can then fully streamline and optimize their processes with targeted use of AI.<\/p>\n

The full research report is available here <\/em><\/strong>https:\/\/www.arisglobal.com\/resources\/regulatory-industry-survey\/<\/em><\/strong><\/a><\/p>\n

About the research<\/strong><\/p>\n

This report is based on an exclusive survey conducted for ArisGlobal by Censuswide between August 30 and September 06, 2024. The research was conducted among a sample of 100 US respondents with senior titles in regulatory roles within pharma\/biopharma companies.<\/p>\n","protected":false},"excerpt":{"rendered":"

A new independent survey of senior US pharma regulatory professionals suggests that commitment to AI investment is much higher than might be expected, although some outdated perceptions could be impeding progress. ArisGlobal\u2019s Renato Rjavec reports. That regulatory workloads are soaring across the international life sciences industry is well acknowledged. A new survey, conducted for ArisGlobal […]<\/p>\n","protected":false},"author":40,"featured_media":9404,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[557],"tags":[],"class_list":{"0":"post-9402","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-insights"},"_links":{"self":[{"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/posts\/9402","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/users\/40"}],"replies":[{"embeddable":true,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/comments?post=9402"}],"version-history":[{"count":3,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/posts\/9402\/revisions"}],"predecessor-version":[{"id":9411,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/posts\/9402\/revisions\/9411"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/media\/9404"}],"wp:attachment":[{"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/media?parent=9402"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/categories?post=9402"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifescivoice.com\/wp-json\/wp\/v2\/tags?post=9402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}