Bring generative AI to regulatory compliance for a competitive edge

In every industry, competitive intelligence is a must-have. By analyzing the latest trends, technologies, and competitor activities, organizations can make better decisions about everything from product development and operations to marketing strategy.

However, compiling and reporting this information is a colossal task.

In the consumer healthcare industry, R&D teams must spend countless hours searching through hundreds of online sources for information on new patents, drug launches, drug approvals, warnings, guidelines, claim innovations, and press releases – anything the company would need to better formulate and take products to market.

Once research teams have gathered relevant information, they can spend weeks piecing together reports for in-house regulatory affairs analysts, R&D specialists, and senior leaders.

What's more, healthcare regulators across the globe continuously revise and update their guidelines. As a result, drug development teams need real-time regulatory intelligence to guide their governance process. Failure to comply with the latest policies could delay projects, leading to significant penalties, customer dissatisfaction, and reputational harm.

In short, the healthcare company needed a more agile process to make fast, informed decisions.

As the company's long-time technology partner, we knew that gen AI could transform its regulatory process. We launched a six-week pilot project, building an AI solution that automates data searches, gathers insights, and reports on drug developments and other key industry information.

First, we engaged with the regulatory affairs and R&D teams to understand which drug types or drug combinations required intelligence reports. We then defined rules and criteria to specify the type of content AI should include or exclude from searches. We also created a detailed keyword dictionary of medical conditions, symptoms, drug combinations, formulations, and delivery systems mapped to the company's products. Then, we used machine learning to tag and categorize content.

Next, we implemented LLMs – deep learning models that analyze vast volumes of data and identify underlying patterns to generate detailed, human-like content.

Our AI experts customized the LLMs to handle various data types. For instance, many LLMs can analyze text but struggle with images. So, we added optical character recognition tools to extract drug development insights from graphs and images.

But technology alone is not enough. We worked with the company's subject matter experts to fine-tune the AI prompts that tell the technology what to search for and its outputs at every stage. Putting human expertise at the heart of the process was essential to ensure optimal results. This human validation led to increased accuracy in AI output results.

We created an innovative gen-AI solution with three key components:

1. Data structure agnostic data scraping: Our solution searches and extracts structured, semistructured, and unstructured data from a variety of sources, such as the US Food and Drug Administration (FDA), Consumer Healthcare Products Association (CHPA), DailyMed, and others
2. Global adaptability: Although data comes into the system in multiple languages, our solution was configured to understand what articles are relevant and translates that information into English
3. Insight delivery: The company didn't want a text-heavy newsletter, so we created a visual summary with alerts readers could set up through a user-friendly portal. Regulatory affairs analysts, R&D experts, and leadership teams can filter searches by region, therapeutic areas, and specific periods for quick access to the insights they need. Plus, all reports live in one system

Today, this healthcare giant enjoys access to fast, and comprehensive regulatory and competitor research and reporting. We delivered:

• Consolidated insights: Our dashboards and newsletters present critical information in a visually appealing, concise format, making competitive intelligence accessible and approachable
• Enhanced productivity: Teams can now generate reports in hours instead of weeks. Without time-consuming research, employees can focus on higher-value tasks such as accelerating product development and ensuring regulatory compliance
• Improved decision-making: Empowered with the information they need, enterprise leaders make faster, smarter decisions. They know where to prioritize R&D investments, how to stay compliant with the latest regulations, which product lines to discontinue, where and how to launch new products, and much more

The consumer healthcare company now employs generative AI to access relevant regulatory and competitor information quickly, helping employees streamline their work and make strategic choices. With newfound agility and intelligence, they use data-driven insights to foster innovation and excellence in the competitive consumer healthcare industry.