AI-driven precision and personalization for commercial pharma

Authors:
Tory Smithe, Head, Digital Strategy - Healthcare & Life Sciences, Adobe
Jonas Sjoquist, Life Sciences Strategy Lead, Adobe
Tyler Jorgensen, Principal, Customer Transformation, PwC US
Tyler Mansfield, Principal, Customer Transformation, PwC US

The challenge and the opportunity

The stakes have never been higher for pharmaceutical companies to be able to efficiently personalize omnichannel experiences, reach relevant patients faster, and provide healthcare professionals (HCPs) and patients with the information they need to enhance the treatment journey.

As access to HCPs becomes increasingly constrained and vying for their attention highly competitive, pharmaceutical companies are under significant pressure to provide content that is not only timely but also highly relevant and tailored to customers’ needs. Traditional methods of content creation in the industry can be highly manual and inefficient. They also fail to extract meaningful insights due to incomplete customer datasets and limited understanding of historical performance, which can lead to disjointed communication with target HCPs and patients.

Imagine a model where you could go from brief to deployment in less than 24 hours, with intelligent, automated content reviews driving compliance with pre-defined MLR standards from the start. Imagine market-ready content on Day One of launch that helps deliver a highly personalized experience for customers across every channel and touchpoint. With the right approach, this can be achievable. It’s all powered by a consolidated technology stack, streamlined workflows, and the latest AI models applied across the end-to-end (E2E) content lifecycle. This new way of working allows teams to focus on what matters most: deliver impact on a scale faster than ever before.

Why now?

The present conditions are fertile ground for technology adoption. These trends are reshaping how pharma should adapt to meet evolving expectations:

• Greater demand for speed and agility. The rise of the “healthcare consumer” has driven increased demand for information, while pandemic-era expectations for agility and real-time interaction have become the norm. With content output projected to increase five-fold over the next two years, GenAI will play a significant role in meeting this demand.
• Intensifying competition and hyper-accelerated time-to-market. Significant AI investment in R&D is expected to drive a surge in scientific breakthroughs and further condense go-to-market timelines in the mid- and long-term. With more brands and more players, the pace of business will only accelerate.
• Reimagining value creation. In the near-term, many companies are facing patent cliffs for large revenue drivers, and these pipeline gaps have prompted many major players to shift into “launch mode” for the foreseeable future. To drive continuous value creation, we are seeing a shift toward preventive and specialized therapies targeted at increasingly narrow patient populations.
• Increasing focus on operational efficiency. With pharma and life sciences returning a paltry 13.9% (compared to 28.7% for the S&P), R&D investment is not translating into market value—forcing a focus on cost efficiency and operational agility. As content spend remains a top expense—in our experience, up to $1B for the largest players—the new mandate is to do more with less to maximize return on investment (ROI).

Considerations unique to commercial pharma

Pharmaceutical companies operate in a highly technical, highly regulated environment, where safety and precision are integral to content management, and even minor inaccuracies can lead to compliance risks, regulatory scrutiny or even patient harm.

Technology solutions should accelerate and orchestrate workflows across the end-to-end lifecycle and maintain the depth, accuracy, and regulatory alignment required in a complex space. To achieve this, some unique additional capabilities are required:

1. Medical claim creation, content libraries and tactic assembly

• Product claims must be supported by evidence (e.g., scientific publications, trial results), with regulatory requirements that establish prescriptive guidelines on the framing. These claims are housed within a library of reusable, compliant content blocks, which serves as the source of truth.
• While many global claims can be applicable at the local level, differences in trial design and regulatory guidance may require adjustments. A claim family structure links global, regional and local messaging, and, therefore, allows flexibility in messaging while enabling consistency with global strategy.
• Additionally, fair balance requirements place guidelines on relative sizing, placement and color of a product’s benefits relative to its risks. Templates enable the compliant assembly of claims within the library.

 2. Automated MLR readiness and review

• Given the highly prescriptive nature of content requirements, medical, legal and regulatory (MLR) reviewers conduct a series of context-specific, specialized checks to drive compliance, which are ripe for automation.
• Risk-based content tiering and tagging based on the complexity of checks allows for more efficient resource allocation and reduces burden on review teams by modularizing content for review.
• Low-risk checks can be conducted by an MLR AI agent while medium- and high-risk checks can be assigned to reviewers based on subject matter expertise. Automated checks should continue to have human oversight and sign-off.

3. Integrated regulatory submission

• Different regulatory bodies (e.g., the FDA, MHLW) require content submissions in different formats and structures and varying metadata fields, adding another layer of complexity. Non-standardized submission processes across regions create additional challenges.
• Integrating regulatory submission into the broader content management system streamlines workflows and expedites approvals by allowing for compliance with country-specific requirements while maintaining global consistency.

A pharma-tailored E2E content management system — powered by Adobe GenStudio, enabled by a new way of working

Adobe GenStudio is a first-of-its-kind offering: a single, fully consolidated platform that spans the end-to-end content lifecycle. It harnesses the power of GenAI to streamline content creation, allowing brands to produce diverse, on-brand marketing materials quickly and efficiently. Its AI-driven capabilities enable marketers to generate and remix content in various formats for personalized and high-performance campaigns across channels and tactics.

PwC leverages deep pharma industry experience to help streamline content management and offer tailored solutions, flexible enough to handle future challenges. Using large language models (LLMs), our accelerators generate relevant and compelling product claims and support "glocalization" or "local-to-local" content strategies. These tools help drive MLR readiness with an intelligent pre-screen, covering requirements for tactic assembly and integrating regulatory submissions into a seamless, end-to-end solution.

Pharma-tailored capabilities integrated with Adobe Stack

Pharmaceutical companies are at different stages in their content management journey—some building on existing systems, others undergoing vast transformation. Regardless of where they stand, the goal remains the same: to streamline workflows, enable modular content, and leverage GenAI for greater efficiency and speed. The path to a future-ready content model isn’t one-size-fits-all; it’s a strategic decision to gain a competitive edge through agility and innovation.

This transformation goes beyond technology—it’s a fundamental shift in how pharma organizations collaborate and operate. To realize the benefits, companies should embrace an agile, tech-empowered ecosystem that fosters collaboration across marketing, medical, legal, and regulatory teams, ultimately:

• Breaking down silos between teams, moving from process-driven checkpoints to a partnership mindset.
• Empowering local teams to adapt global strategy to market-specific needs, balancing execution speed with regulatory control.
• Investing in digital fluency and change management to build trust and adoption of AI-powered tools.

Now is the time to replace bottlenecks and inefficiencies with intelligence, precision, and speed. AI can handle manual reviews and content pre-screens, freeing marketers to focus on high-impact messaging and MLR teams to take on a role of strategic oversight.

Ultimately, the pharma industry’s ability to unlock the full potential of AI-powered end-to-end content management will depend not just on technology adoption, but on its willingness to rethink how teams collaborate, how decisions are made, and how innovation is embraced to step into the future.