Nick Sirnes, Global Health and Wellness Science Advisory Partner at EY

Nick Sirnes, Global Health and Wellness Science Advisory Partner at EY

Nick Sirnes is a partner in health sciences and wellness at EY. He has spent the past 20 years as a management consultant, leading multidisciplinary teams around the world and working with large and complex pharmaceutical, medical device and health technology companies around the world as they navigate through disruption, innovation, and transformation.

He and his team are passionately focused on helping these organizations define their role in creating platforms that effectively share trusted health-related information. In this way, they help individuals make strong choices about their care.

Pharm Exec: What challenges do life sciences companies face today when it comes to delivering content in a timely manner?

Nick Sirenese: With the explosion of digital technology, there are many tools, channels, and formats that life sciences companies can use to communicate in a more effective and efficient manner with the patients and physicians they serve. The pandemic has also emphasized the need and appetite for rapid, accurate, and multi-channel information exchange.

But what life sciences companies say, directly or indirectly, about their medical treatments and devices is promotional and therefore closely regulated. In a world of rapid, multichannel communication, the audit processes they use to ensure that their materials are fit, accurate, and compliant are no longer fit for purpose. They are ineffective, unreliable and expensive.

This is not only very frustrating for everyone involved in the review process. It makes it more difficult for organizations that support their existing brands to launch new ones as well. In the worst case, new drugs and devices cannot be launched with full marketing support because promotional materials have not been approved, or marketing about existing products must be stopped because materials have not been updated quickly enough.

But if companies produce materials that are found to be non-compliant, this can lead to reputational and regulatory risks as well as unnecessary fines.

What obstacles or bottlenecks are slowing down the approval process for biopharmaceutical marketing materials?

The MLR review process is lengthy, labor-intensive and error-prone. It requires significant time to manually review documents, which leads to bottlenecks, wasted time and additional expenses. With an ADTA (Average Days of Approval) of 24 days, it costs the industry tens of millions of dollars annually.

Part of the problem is that the process isn’t built to scale, and teams struggle to manage all the moving parts and maintain a fast review cycle as materials flow. Furthermore, subject matter experts who must focus on reviewing complex letters that need deeper knowledge often spend time checking for basic grammatical errors in direct material.

When the process is not fit for purpose, people break up. They find solutions and take shortcuts. Review standards have become inconsistent. The decisions are not fully documented. The quality of the review rests. Increase errors and reduce accountability. Everything is slowing down, bottlenecks appear, and costs are rising.

How can technology – especially artificial intelligence and machine learning – help simplify and speed up the MLR review process while ensuring compliance?

The good news is that the need for greater content volume and speed intersects with technological advances in artificial intelligence. Artificial intelligence, including machine learning (ML) and natural language processing (NLP), has reached a level of maturity, allowing the automation of a number of MLR functions.

At EY, we’ve been working on an approach to a review process for life sciences companies’ promotional materials that is more efficient, reliable, and smarter. It has been well received thus far by those involved in the MLR process – from the pharmaceutical and medical device marketing teams to their agency, medical, regulatory and legal partners.

In short, after content creation and previous MLR review, the platform uses AI to automate batches of MLR review activities, checking everything from spelling and grammar to message consistency and compliance. This creates an ability for companies to support an ever-increasing volume of content, as they focus on more complex parts of the review, where their professional judgment and expertise is better spent. The AI ​​engine learns and improves through experience, based on the original dataset, reference library, and success criteria.

How does this kind of technology create efficiencies for life sciences companies?

In conversations with those in the industry, I heard about a representative of a marketing agency who attended the rollout of a new MLR review system for a division of a pharmaceutical company. The meeting flyer was a trio of three 8.5 x 11 inches. Sheets explaining the steps of the new system. Imagine her surprise when I counted 34 steps and a total of 62 bullets! On average, her agency charges an additional 30 percent for every piece of content you create to account for the MLR review process.

Now imagine if 54 percent of content errors could be managed automatically, saving 51 percent of reviewer time overall. Content creators and reviewers can focus on what they do best, and companies can create and share compliant content faster and with greater confidence, while reducing risk and reducing unnecessary costs.

Are there any other applications of AI technology in other areas of life sciences commercialization?

definitely. Artificial intelligence is a powerful driving force behind marketing automation. It can help with social listening, identifying the right target audiences and influencers, and generating informed copy. In short, AI can facilitate the right conversations with the right doctors and patients at the right time.

Over the past five years, AI has also redefined how scientists develop new drugs, treat challenging diseases, monitor patients for symptoms and adherence to drugs, find the right patients for clinical trials, and more.

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