Q&A: Nick Cernese, EY Global Health Sciences & Wellness Consulting Partner

Nick Cernese is a Health Sciences and Wellness partner at EY. He has spent the last 20 years as a management consultant, leading interdisciplinary teams across the globe and working with large and complex pharmaceutical, medical device, and health technology companies worldwide as they navigate through disruption, innovation and transformation.

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

Pharm Exec: What are the challenges that life sciences companies face today when it comes to putting content out in a timely manner?

Nick Cernese: With the digital technology explosion, there are so many more tools, channels, and formats that life sciences companies can use to communicate in a more effective and efficient manner to the patients and clinicians they serve. The pandemic further underscored both the need and appetite for quick, accurate, multi-channel information sharing.

But what life sciences companies say, directly or indirectly, about their therapies and medical devices, is considered promotional and therefore closely regulated. In a world of rapid, omnichannel communication, the review processes they use to ensure their materials are relevant, accurate, and compliant are no longer fit for purpose. They are inefficient, unreliable, and costly.

This isn’t just hugely frustrating for everyone involved in the review process. It makes it far harder for organizations supporting their existing brands to also launch new ones. In the worst case, new drugs and devices can’t be released with full marketing support because promotional materials haven’t been approved, or marketing around existing products must be dialed down because materials haven’t been updated fast enough.

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

What are the hurdles or bottlenecks slowing down the approval process for biopharma marketing materials?

The typical Medical Legal Regulatory (MLR) review process is lengthy, labor-intensive and prone to errors. It requires significant manual review time for documents, leading to bottlenecks, lost time and added expense. With an ADTA (Average Days To Approval) of 24 days, it costs industry tens of millions of dollars per year.

Part of the problem is that the process isn’t built for scale, and teams struggle to manage all the moving parts and maintain review cycle speed during a material influx. What’s more, subject experts who should be focused on reviewing complex messages needing their deeper knowledge often spend time checking basic grammar errors in straightforward materials.

When a process isn’t fit for purpose, people disengage. They find workarounds and take shortcuts. Review criteria become inconsistent. Decisions aren’t fully documented. The quality of the review falls. Errors increase and accountability is diluted. Everything slows down, bottlenecks emerge, and costs go up.

How can technology – particularly artificial intelligence and machine learning – help streamline and speed the MLR review process while ensuring compliance?

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

At EY, we’ve been working on an approach to life sciences companies’ promotional materials review process that is more efficient, reliable and intelligent. And it’s been very well received to date by those involved in the MLR process – from pharma and medical device marketing teams to their agency partners and medical, regulatory and legal affairs.

In a nutshell, following content creation and preceding MLR review, the platform uses AI to automate sets of MLR review activities, checking everything from spelling and grammar to message consistency and compliance. This creates capacity for companies to support an ever-increasing volume of content, because they are focusing on more complex parts of the review, where their judgment and professional expertise are better spent. And the AI engine learns and improves with experience, building on its original data set, 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 marketing agency rep who attended the rollout of a new MLR review system for a division of a pharmaceutical company. The meeting handout was a trifold comprised of three 8.5 x 11-inch. sheets outlining the steps to the new system. Imagine her surprise when she counted 34 steps and a total of 62 bullets! On average, her agency charged 30 percent more for each piece of content they created 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 could focus on what they do best, and companies could create and share compliant content faster and with more confidence,while reducing risks and cutting unnecessary costs.

Are there any other applications of AI technology to other areas of life sciences marketing?

Absolutely. AI 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 physicians and patients at the right time.

Over the last five years, AI has also redefined how scientists develop new drugs, tackle difficult diseases, monitor patients for symptoms and drug adherence, find the right patients for clinical trials, and more.