Abstract
Pharmaceutical companies invest billions of dollars annually in the production of medical and promotional content. This includes e-detail aids, prescribing information, portals, and patient brochures, often translated into more than twenty languages and reviewed through rigorous medical, legal, and regulatory (MLR) processes. While these systems ensure compliance, emerging evidence suggests that content produced under this model is rarely consumed or comprehended by target audiences. Health care professionals (HCPs) face limited time and increasing digital fatigue, while patients report persistent difficulty understanding product information. In this article, we describe the structural inefficiencies of “content factories,” quantify the engagement gap, and propose that artificial intelligence (AI)–driven approaches can transform MLR-approved assets into interactive, customer-centric experiences that maintain compliance while enhancing impact.
The Content Factory Model
Over the past two decades, pharmaceutical firms have created “content factories” to standardize global medical communications. These operations rely on a complex ecosystem of agencies, medical writers, compliance reviewers, and localization partners. Their purpose is to scale content rapidly across therapeutic areas and markets.
However, evidence points to systemic inefficiencies:
Redundancy and duplication: Affiliates often recreate content for local markets, increasing costs and introducing regulatory risk [1].
Opaque impact: Once a PDF or slide deck is deployed through platforms such as Veeva, there is little visibility into whether it was opened, read, or understood [2].
Escalating costs: The combination of volume, repeated MLR review, and retranslation leads to billions in annual expenditure without evidence of proportional educational value.
The Engagement Gap
Content factories solved the challenge of supply but not the challenge of consumption.
HCPs: On average, physicians see approximately 6.4 pharmaceutical representatives per month, with a mean interaction time of 11 minutes [3]. At the same time, surveys suggest that a majority of HCPs prefer to supplement in-person detailing with self-directed digital content, yet the prevailing format remains static PDFs and linear slide decks.
Patients: Nearly 58.5% of U.S. adults reported searching online for health information in 2022 [4]. Despite this, the European Medicines Agency (EMA) has documented that only ~12% of patients fully understand medication leaflets on first read [5].
Commercial field forces: Traditional e-detailing remains largely push-based, offering little visibility into which claims or visuals resonate. This disconnect limits the ability of sales or medical affairs teams to adapt their strategies.
The net result is that the most compliance-heavy content in the world often fails at its primary purpose: educating and activating audiences.
Why The Problem Is Growing
Three converging forces make the engagement gap more urgent:
AI-driven content proliferation: Generative AI tools can produce compliant-looking text and imagery at unprecedented scale. Without a new paradigm, the flood of content risks deepening HCP fatigue.
Regulatory scrutiny: EMA and FDA increasingly emphasize clarity, accessibility, and health literacy rather than mere technical compliance [5].
Omnichannel accountability: McKinsey reports that approximately 70% of HCPs now prefer a hybrid of rep-led and self-guided digital interactions [6]. This shifts engagement metrics from marketing teams to the boardroom.
Toward An AI-Driven Engagement Model
AI-Enhanced Self-Guided Journeys
AI technologies can transform static, MLR-approved PDFs or slide decks into interactive, self-guided modules, enabling HCPs and patients to navigate data relevant to their needs—whether efficacy endpoints, safety profiles, or dosing information.
Adaptive e-Detailing
AI can support dynamic e-detail aids that respond to interaction history. For example, if an HCP repeatedly returns to safety data, subsequent interactions can prioritize related claims and visuals, all while remaining within MLR-approved frameworks.
Modular, Compliant Ecosystems
The adoption of structured modular content—approved “blocks” that can be reused and localized—can reduce redundancy, speed affiliate deployment, and maintain compliance [1]. AI can further optimize which modules are deployed to which audiences.
Engagement Analytics As A Feedback Loop
AI-driven analytics can capture granular interaction data: dwell time on safety charts, navigation of MOA videos, or frequency of patient FAQ views. These data create a scientific feedback loop between content creation and audience impact.
Discussion
The prevailing assumption that compliance requires static, text-heavy formats is increasingly untenable. Evidence suggests that interactivity, personalization, and self-guidance improve comprehension and retention in both HCP and patient education. AI-driven tools now make it possible to deliver this level of engagement at scale—without undermining the regulatory rigor of MLR processes.
Future research should quantify outcomes associated with interactive versus static formats—for example, whether self-guided modules improve prescribing confidence among HCPs or increase adherence among patients. Evidence of measurable improvements in outcomes could justify a systemic shift in pharma’s global content operations.
Conclusion
Pharma’s content factories are optimized for volume, not impact. The engagement gap between content supply and audience needs is widening under the pressure of AI proliferation, regulatory scrutiny, and omnichannel expectations.
An AI-driven approach—anchored in self-guided content journeys, adaptive e-detailing, modular design, and analytics—offers a pathway to reimagine MLR-approved content as both compliant and engaging.
If implemented effectively, such models could convert content from a cost center into a measurable driver of patient understanding, HCP education, and brand trust.
References
Pharmaceutical Manufacturer. Why the pharmaceutical industry needs a digital content factory. 2023. Available at: https://pharmaceuticalmanufacturer.media/pharmaceutical-industry-insights/latest-pharmaceutical-manufacturing-industry-insights/why-pharmaceutical-industry-needs-a-digital-content-factory/
FiercePharma. Pharma asks: What's up, doc? Industry seeks to get inside the heads of HCPs in 2024. 2023. Available at: https://www.fiercepharma.com/marketing/pharma-asks-whats-doc-industry-seeks-get-inside-heads-hcps-2024
Clarivate. How can pharma reps respect physicians’ time? We asked 20 doctors. 2024. Available at: https://clarivate.com/life-sciences-healthcare/blog/how-can-pharma-reps-respect-physicians-time-we-asked-20-doctors/
CDC. Percentage of adults who looked up health information on the Internet: United States, 2022. National Health Interview Survey Data Brief 482. 2022. Available at: https://www.cdc.gov/nchs/products/databriefs/db482.htm
European Medicines Agency (EMA). Improving information for patients: Summary of Product Characteristics (SmPC) and Package Leaflet. 2020. Available at: https://www.ema.europa.eu/en/human-regulatory/overview/public-health-initiatives/improving-information-patients
McKinsey & Company. The future of commercial in pharma: A hybrid model for HCP engagement. 2023. Available at: https://www.mckinsey.com/industries/life-sciences/our-insights/the-future-of-commercial-in-pharma-a-hybrid-model-for-hcp-engagement