Deploying Personalized Content in Pharma Sales: A Practitioner’s Guide

The pharmaceutical industry has access to an impressive array of tools for generating personalized content. Leveraging Large Language Models (LLMs) trained on vast datasets, these tools can produce highly polished slides, emails, and videos tailored to individual healthcare professionals (HCPs).

However, despite the sophistication of these technologies, deploying them effectively—ensuring that personalized content reaches sales representatives and enhances their interactions with HCPs—poses significant challenges for marketing, digital, and innovation teams.

(To clarify: this post focuses on personalized content, meaning materials such as slides or emails that are customized in both message and content for each individual HCP.)

Beyond the technical and IT integration hurdles (which we will address in a forthcoming post), the key challenges fall into three critical areas:

• Relevance: How can we generate content that is genuinely engaging and valuable for a specific HCP at a given moment?
• Alignment: How do we ensure that the content aligns with overall marketing strategy and adheres to market-specific regulatory constraints?
• Compliance: How can we efficiently manage regulatory considerations, including pharmacovigilance concerns related to third-party content references?

The Role of AI in Personalized Content Deployment

Based on multiple real-world implementations and success stories, we recommend a phased approach to deploying personalized content in pharma sales. A practical starting point is to implement three fundamental use cases:

1. A recent scientific paper cited by the HCP
2. Content triggered by social media activity or engagement
3. A reference to a recent industry event

For each of these scenarios, we provide practical guidance on what works, how content can be generated, and how to integrate it into established pharma marketing strategies. To further support practitioners, we include one-page 'cheat sheets' for each use case, offering a structured approach to execution.

A key enabler of this approach is the strategic use of AI agents—specialized models that handle distinct aspects of content selection, preparation, and validation. We introduce Remy, Alina, and Coco, three AI agents designed to optimize personalized content delivery:

• Remy ensures Relevance by selecting the most pertinent content for each HCP.
• Alina guarantees Alignment with brand and market-specific regulations.
• Coco oversees Compliance, including pharmacovigilance and regulatory reporting.

Use Case: The Recent Scientific Paper

When an HCP publishes or references a scientific paper, sales reps can significantly enhance their engagement by incorporating this knowledge into their discussions. Here is how the AI-powered process works:

1. Remy (Relevance AI Agent) identifies and selects the most relevant scientific paper based on the HCP’s interests and past interactions.
2. Alina (Alignment AI Agent) ensures that the selected paper aligns with the brand’s approved communication strategy and regulatory requirements.
3. Coco (Compliance AI Agent) verifies compliance considerations, such as pharmacovigilance risks, before finalizing the content.
4. The approved content is then formatted into an AI-generated insight or a personalized slide for the sales rep.

A well-structured personalized slide should:

• Summarize the key findings of the paper
• Provide a direct link to the original publication
• Seamlessly lead into related marketing materials for the promoted brand

Use Case: Social Media Engagement

HCPs increasingly use social media to enhance their professional presence. Their posts and engagements can serve as valuable indicators for sales reps. However, manually tracking social media activity is time-consuming, and reps may not be fully trained in evaluating relevance, alignment, and compliance of online content.

An AI-powered system can monitor social media activity and deliver personalized insights in real time - but only if deployed with caution. Here is how the process unfolds:

• Remy identifies and analyzes relevant social media activity.
• Alina verifies that the engagement aligns with marketing strategy and regulatory guidelines.
• Coco assesses compliance risks before the insight is shared with the sales rep.

The final output can be integrated into tools like Veeva Insights or Next Best Platforms, summarizing the social media post, linking to the original content, and suggesting an appropriate follow-up aligned with approved marketing materials.

Use Case: A Recent Event

Though seemingly straightforward, referencing an HCP’s participation in a recent event can be a low-risk, high-impact way to personalize interactions. Typically, this involves using data from pharma-sponsored events (which is readily available within the company’s CRM). As a next step, data from platforms like Veeva Links can provide deeper insights into an HCP’s participation in industry conferences.

A successful deployment of this use case involves:

• Summarizing the event name, topic, and date
• Linking to relevant approved marketing content
• Using the event as a bridge to continue meaningful engagement

AI Agents in Action: How Remy, Alina, and Coco Work

Our experience shows that the highest-quality personalized content is delivered by an ensemble of AI agents, each specializing in a distinct task:

Remy (Relevance AI Agent)

• Identifies the most relevant content for each HCP based on predefined criteria.
• Uses an LLM-based classifier, fine-tuned for brand and market specificity.
• Applies additional source-specific relevance filters to refine content selection.

Alina (Alignment AI Agent)

• Ensures selected content aligns with the brand’s strategic messaging.
• Checks against a predefined regulatory and marketing checklist.
• Uses AI prompts to validate alignment with brand-specific guidelines.

Coco (Compliance AI Agent)

• Applies business rules and AI-based pharmacovigilance checks.
• Detects potential compliance risks in content.
• Can automate pharmacovigilance reporting where necessary.

Once Remy, Alina, and Coco validate the content, an AI-powered content generator produces the final insight, slide, or video for the sales rep.