Artificial intelligence is changing the game for pharma marketing teams.
This article explores how AI tools can streamline the eDetail design process. We used our fictional product, Noxivision, to test a hybrid workflow that combines AI with human expertise. Can this approach cut development time, ensure MLR compliance, and help create compelling presentations that resonate with healthcare professionals?
Key Takeaways
- AI cuts eDetail concepting time
- Hybrid workflow keeps MLR compliance intact
- Designers still own branding & data accuracy
Don’t have time to read the article? Listen instead:
What is Noxivision? Noxivision is our fictional product developed as part of Iguazu’s research into AI advancements. If you would like to read more about the Noxivision project, please click here to read through the articles. Or for a shorter recap, listen to the Noxivision AI Podcast.
Why eDetails Strain Pharma Teams
Brand managers face immense pressure to deliver compelling, compliant marketing content like eDetail presentations. For brand and marketing managers, creating effective marketing materials is a high-stakes process.
What are eDetails? Find out more about eDetails for pharmaceutical marketing
Traditional eDetail Production Bottlenecks Brand Teams
The traditional workflow is riddled with bottlenecks, from creative ideation to final approval. The most common pain points include:
Regulatory Hurdles:
Gaining MLR approval for every asset is a major bottleneck that can cause significant delays.
Struggling to Visualise New Ideas:
It's difficult and slow to explore and develop new visual concepts, limiting creative options.
Ensuring Data Accuracy:
Maintaining scientific precision across a multitude of slides requires meticulous oversight.
Limited Budgets & ROI Pressure:
Teams face pressure to do more with less while proving the commercial return on every marketing dollar spent.
As a pharmaceutical digital marketing agency, we strive to give our clients the best return on investment and support them in streamlining their CLM efforts. So we wanted to know: Can AI tools now expedite asset development, enhance message clarity, and boost commercial impact?
Our AI‑Driven Experiment
Study Design & Metrics: What Did We Test and How
To assess the practical value of AI-assisted design tools in a pharmaceutical context, we ran a structured experiment using Noxivision, our fictional product created to explore how AI could support asset development within regulatory constraints. Our goal was to test whether these tools could improve layouts and reduce time.
Tools Tested (ChatGPT, Canva, MagicSlides, SlidesGPT)
We evaluated a mix of AI platforms and plugins, assessing each for its ability to contribute meaningfully to the eDetail design process, from concept generation and content structuring to layout prototyping and visual consistency. We used them to generate rough layouts, visual motifs, and content hierarchies that our designers could then refine.
Results: How AI Speeds Concept‑to‑MLR
AI cuts eDetail design time
The hybrid workflow keeps MLR compliance intact
Designers still own branding and data accuracy
AI outputs can be reused across leave-behinds, booths, and CRM assets
Design and Branding for Pharmaceutical eDetails
With a diverse set of AI-generated starting points created, we were able to repurpose these as a foundation for the eDetail design process. These early outputs served as a springboard not just for visual inspiration but as a way to rapidly advance layout and content development without compromising scientific integrity. This early acceleration enabled alignment on strategic narrative and visual direction before entering more resource-intensive phases of review, increasing speed to MLR approval and field deployment.
Here is a breakdown of how AI-assisted design impacted our workflow, from initial concepts to complex data slides:
- Homepage and Profile Slides: AI-generated strong initial layouts, requiring only minor adjustments.
- Complex Content Slides: AI provided a solid visual foundation, but these pages still required greater manual refinement.
- Reusability: The AI-generated elements proved versatile, acting as visual anchors across different pages.
AI-generated design components proved especially versatile as a foundation for our designers to build upon. These outputs, which included background shapes, graphical accents, and text containers, acted as visual anchors, reinforcing consistency across complex messaging. For brand managers, this ability to reuse and standardise design language not only improves clarity for HCP audiences but also reinforces brand credibility and message retention.
For example, the initial AI-generated layout for the eDetail homepage required only minor structural adjustments. Core layout elements remained intact, while regulatory-compliant colours, brand fonts, and custom iconography were expertly layered in by our designers. The wave-like pattern suggested by AI was adapted into a branded motif, creating both visual interest and strategic flexibility. This enabled differentiated storytelling formats that are immediately engaging for sales reps and HCPs without compromising compliance, a testament to the value of AI assistance in the hands of experienced designers.
A similar approach was taken with profile overview slides. While the structural integrity of the AI draft was preserved, imagery and content areas were optimised to highlight key patient visuals and value propositions. The expanded right-hand column allowed for more robust inclusion of clinical claims, trial snapshots, and value messaging, enabling sales reps to deliver richer, more persuasive narratives. The subtle dotted line dividers retained from AI outputs added visual clarity and structure, helping field teams navigate dense scientific content with confidence.
Slides with dense or complex content, such as clinical data tables, product attributes, or efficacy summaries, required greater manual refinement. However, AI provided a strong visual foundation, enabling faster structuring of high-stakes content without disrupting scientific precision. By embedding branded design motifs into these more technical pages, the final outputs retained clarity and cohesion across the deck. This directly supports MLR efficiency, helping brand teams approach review cycles with more polished, compliant layouts and fewer delays from format revisions.
Hybrid Workflow: Designers + AI
What Worked
A Hybrid AI-Driven Design Workflow – Amplifying Team Capabilities, Not Replacing Them
AI-assisted design tools proved highly effective when used at the start of the creative process. They allowed our team to quickly generate rough visual concepts, which sped up early thinking and freed up design resources to focus on higher-value tasks like clinical storytelling and user engagement.
Rather than replacing expert designers, AI enhanced their ability to work faster and more strategically. For example, our design team quickly explored different layout options for homepages, clinical summaries, and product overviews. These drafts weren’t final, but they provided a solid starting point, helping shorten design cycles and align stakeholders more efficiently.
For brand managers, this hybrid approach goes beyond speed. It supports faster iteration on messaging, helps teams get closer to MLR-ready content earlier, and improves overall efficiency in bringing materials to market. This is how we have used AI to deliver more responsive, strategic design support.
The most important benefits include:
Earlier progress toward MLR-ready content
Shorter design and review cycles
More efficient alignment across stakeholders
Stronger, more strategic design support
This is how we have used AI to deliver more responsive, strategic design support.
Find out how our services can improve your next marketing campaign
What Needed Manual Oversight
While AI tools provided a powerful starting point, the role of an experienced designer remained crucial for tasks that required strategic thinking and deep industry knowledge. These critical human-led functions included:
Design of Complex Graphics:
Creating and refining intricate visuals such as graphs, charts, and study designs to ensure scientific precision and clarity.
Converting AI Concepts:
Transforming the AI-generated visual ideas into editable, reusable design assets compatible with final production software (e.g., Adobe InDesign, Figma etc.).
Scientific and Data Accuracy:
Meticulously verifying all clinical data, claims, and figures to ensure they are precise, correctly cited, and compliant with regulatory standards.
Complex Storytelling:
Structuring nuanced narratives for healthcare professionals, creating a clear and compelling flow that goes beyond a basic layout.
MLR Compliance:
Ensuring every visual, from a colour palette to a specific image, is legally and medically compliant before it enters the final review process.
Brand Consistency:
Applying a deep understanding of brand guidelines to create a cohesive look and feel that builds brand credibility.
Strategic Adaptation:
Translating the marketing strategy into visuals that resonate with a target audience and align with commercial goals.
Compliance & Data Privacy Guardrails
Limitations & Risk Controls
What are the risks of AI‑generated slide layouts?
Using AI tools on their own, without expert human oversight, presents significant risks for pharmaceutical marketing teams. Key concerns include:
Legal & Regulatory Risk:
AI can produce inaccurate, non-compliant content that leads to serious legal and regulatory repercussions.
Lack of Editability:
AI-generated outputs often require a complete rebuild, making it difficult to edit, update, or reuse assets.
Inconsistent Branding:
Without an understanding of brand guidelines, AI can create fragmented visuals that erode brand credibility.
Security Issues:
Using general AI models poses a risk of data breaches and fails to meet healthcare data privacy standards.
Our design team evaluated several AI-powered plugins and platforms to understand their capabilities in creating presentation materials suitable for pharmaceutical sales.
Early experiments with base models like ChatGPT revealed notable limitations that highlighted the irreplaceable value of human oversight in pharma marketing. While these tools were effective at generating raw content, results often lacked:
Visual sophistication:
They struggled to produce the polished, on-brand aesthetics crucial for professional pharmaceutical presentations.
Consistent design
The AI tools struggled to maintain consistency across different pages, leading to design with a confusing user experience.
Regulatory awareness:
The content wasn't inherently aligned with the stringent compliance requirements of our industry.
Structural logic for complex narratives:
They failed to convey nuanced clinical stories with the necessary hierarchy and data visualisation for HCP comprehension.
These early challenges underscored a key point: while AI can help create content, it works best as part of a hybrid workflow where human oversight ensures alignment with strategy, compliance, and compelling storytelling. All of these are essential for brand managers.
Extending the Value Beyond eDetails
While our focus here has been on eDetail presentations, the efficiencies gained through this hybrid AI-assisted design workflow extend across the full spectrum of pharmaceutical marketing. From pre-launch “leave-behinds” and congress booth visuals to sales rep training decks, CRM modules, and global brand guidelines, the ability to rapidly prototype, iterate, and refine visual assets allows brand managers to maintain consistent messaging, accelerate campaign timelines, and maximise ROI across every phase of the product lifecycle.
This includes:
- Pre-launch “leave-pieces”
- Congress booth visuals
- Sales rep training decks
- CRM modules
- Global brand guidelines
Conclusion
AI speeds up design, but expert oversight ensures accuracy, compliance, and brand impact.
The key takeaways for pharmaceutical brand managers are:
Human expertise is still required for accuracy, compliance, and brand standards
AI alone cannot yet manage full-scale eDetail development
Hybrid workflows ensure agility while maintaining scientific and regulatory precision
This approach demonstrates how AI-generated design assets can serve as more than time-saving tools they are strategic accelerators for pharmaceutical brand teams striving to create accurate, compelling, and adaptive sales enablement. By incorporating AI at the front end of the design process, teams can explore multiple narrative strategies quickly, iterate earlier, and ensure final materials are optimised for message clarity and clinical accuracy.
Can AI tools pass pharma MLR review?
The short answer is no – human expertise is still required, especially in an industry as highly regulated as pharma.
While human refinement by expert designers remains essential to uphold rigorous regulatory and brand standards, AI helps reduce time spent on low-value layout tasks. However, despite rapid advancement, AI tools are still far from being able to manage the full design of complex eDetails independently. Accuracy, consistency, security, and quality, especially in the context of pharmaceutical presentations, still demand expert oversight. Additionally, once an initial design is created using AI, making subsequent edits or updates can become increasingly inefficient, as the AI may introduce unintended changes, complicating version control and refinement.
The future is AI-assisted
By embracing this intelligent, hybrid approach, we can empower pharmaceutical brand managers to accelerate the development of critical sales tools. We ensure scientific precision, brand cohesion, and message impact, ultimately contributing to a more agile and successful product lifecycle strategy. Our expertise in leveraging cutting-edge AI tools, combined with our deep understanding of the pharmaceutical industry’s regulatory landscape, positions us as a leader in digital healthcare innovation.
Ready to Improve Your Next eDetail Project?
AI-assisted design can cut production time, improve message clarity, and speed up MLR approvals—but only with expert oversight. At Iguazu, we help pharma teams use AI safely and strategically to deliver faster, compliant, and impactful sales tools.
Looking to harness AI in your next project? Or prefer a traditional workflow? We’re happy to provide a custom quote for either a hybrid or traditional approach, ensuring the best ROI for you.
Frequently Asked Questions (FAQs)
AI is used strictly at the concepting stage generating rough layouts and visual ideas. All outputs are then refined within approved design environments like Adobe InDesign, where brand fonts, colours, iconography, and regulatory elements are layered in. This hybrid workflow ensures that final materials meet both brand standards and MLR expectations, helping teams get closer to a compliant asset earlier in the process.
Want to know how we use AI? Iguazu is committed to ensuring our use of AI tools is honest, safe, and secure. Learn more by exploring our AI Policy.
Finalised eDetail presentations are delivered in standard formats compatible with common DAM and CRM platforms. While the article focuses on design workflows, all outputs are prepared for seamless integration whether that’s for Veeva, modular content libraries, or rep-triggered CRM assets ensuring downstream usability and alignment with your tech stack.
With AI accelerating early layout and concepting, teams can explore multiple visual directions upfront, making it easier to localise or tailor materials for specific markets or messaging pivots. This means faster adaptation to market shifts, competitor moves, or new data giving brand teams a real-time edge without restarting the design process from scratch.
AI-assisted design means that artificial intelligence tools work with human designers. The AI acts like a powerful co-pilot, generating ideas, layouts, or elements very quickly. It handles the initial, often repetitive, ideation or foundational work. However, the human designer then takes these AI-generated concepts, applies their creativity, strategic thinking, brand knowledge, and regulatory expertise to refine, adapt, and finalise them. This is different from a fully autonomous AI, which would attempt to create a complete design without human input (and, as the article points out, struggles with nuance and compliance in pharma).
Want to know how we use AI? Iguazu is committed to ensuring our use of AI tools is honest, safe, and secure. Learn more by exploring our AI Policy.
In the world of AI, a “base model” refers to a general-purpose artificial intelligence system, often a large language model (LLM), that has been trained on a massive amount of diverse data. These models (like the public versions of ChatGPT) are highly capable at understanding and generating text or general concepts, but they are not specifically trained or optimised for niche industries like pharmaceutical marketing, nor are they typically equipped with design capabilities out-of-the-box. This is why specialised plugins and human refinement are essential for industry-specific applications.
MLR stands for Medical, Legal, and Regulatory review. In the pharmaceutical industry, all marketing and promotional materials must undergo a strict MLR review process to ensure they are scientifically accurate, legally compliant, and adhere to all relevant regulations and ethical guidelines. It’s a crucial step to protect patient safety, maintain brand integrity, and avoid legal repercussions.
Data privacy is paramount, especially in healthcare. When we utilise AI tools for design concepting, we primarily use them with non-sensitive, aggregated, or anonymised data inputs to generate visual structures and general content ideas. No patient-specific or highly confidential product data is fed into general AI models. All sensitive content and clinical data are integrated and refined by our expert team within secure, compliant environments, adhering strictly to industry data governance standards.
Want to know how we use AI? Iguazu is committed to ensuring our use of AI tools is honest, safe, and secure. Learn more by exploring our AI Policy.
Our team continually evaluates emerging AI technologies to identify tools that best align with the specific needs of pharmaceutical marketing, prioritising those that offer robust ideation capabilities and seamless integration into our existing design workflows. We carefully assess each tool’s ability to support our hybrid approach, focusing on its capacity to generate versatile components that our designers can then refine to meet strict brand and regulatory standards.
Interested in learning how AI can transform your marketing? We also offer consulting services to share our knowledge with pharma clients, from content creation to product launch. Ask us how AI can help you with your pharma marketing.
AI Tools used: Chat GPT, Canva, MagicSlides, SlidesGPT
Ready to Improve Your Next eDetail Project?
AI-assisted design can cut production time, improve message clarity, and speed up MLR approvals—but only with expert oversight. At Iguazu, we help pharma teams use AI safely and strategically to deliver faster, compliant, and impactful sales tools.
Looking to harness AI in your next project? Or prefer a traditional workflow? We’re happy to provide a custom quote for either a hybrid or traditional approach, ensuring the best ROI for you.
Luke Horne
Graphic designer
About Iguazu: We are a digital agency specialising in delivering tactical marketing solutions to the healthcare and pharmaceutical industry.
