MedTech Pharma Marketing

Top Use Cases of AI in Pharma & MedTech

Post author By Piotr Wrzosinski
Post date 06/08/2025
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What are the main forms of generative AI being leveraged in pharma marketing?

Generative AI can be categorized into three general uses:

Content Generators: These produce texts, images, and video rapidly, and can also refine content by changing tone, simplifying information, or fine-tuning messages for specific audience segments.
Answer Engines: These are new forms of ‘search’ that generate direct answers (text, images, video) rather than just providing links. They can be used to extract insights from market research reports or summarize clinical studies.
Agents (Large Action Models – LAMs): These forms of AI act to achieve specific goals without specific instructions or human oversight. For example, an AI agent could review keynote Q&As and social media reactions to assess the medical community’s response to a drug launch. These are considered the most controversial due to their autonomous nature.

What are the primary use cases for AI in pharma and MedTech marketing?

There are four broad categories of AI use cases in pharma and MedTech marketing:

Strategic Insights Generation: AI can analyze vast amounts of both structured (e.g., CRM data) and unstructured data (e.g., government policy documents, articles on HCP preferences) to generate actionable insights and trends. This can improve understanding by up to 30%. However, caution is advised as AI can produce plausible but incorrect results (“AI hallucination”).
Marketing Content Generation: AI is crucial for omnichannel strategies that require high content volume for personalization. It can rapidly generate various content formats (texts, images, video, audio) and reduce content creation costs by 30-50%.
MLR Acceleration (Medical, Legal, Regulatory Review): AI can modernize labor-intensive MLR processes, which typically take 21 to 56 days for approval. AI tools can pre-screen materials, flagging problematic content for detailed review and fast-tracking compliant assets. AI co-pilots can also assist MLR staff with referencing claims and rephrasing options, potentially accelerating content approvals two to three times.
Field Force Enablement: AI benefits customer-facing staff like sales teams and Medical Science Liaisons (MSLs) by improving training, account planning, and content delivery. AI can provide immediate access to drug information, offer coaching for specific situations, and integrate with CRM to help reps prioritize accounts and personalize HCP engagements based on “next best” message or format recommendations.

Tags AI, medical devices, MedTech Commercialization, pharma marketing

Pharma Marketing

Understanding AI in Pharma Marketing

Post author By Piotr Wrzosinski
Post date 06/08/2025
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What is Artificial Intelligence (AI) in a pharma commercial context?

In a pharma commercial context, AI primarily refers to generative AI, which differs from traditional “classical AI” or machine learning.

Classical AI / Machine Learning models perform specific tasks, like analyzing data for predictions or identifying patient groups, using very specific datasets.
Generative AI works with a foundational, large language model (LLM) trained on vast amounts of data, enabling it to be applied to many different problems. Its key characteristics include:
- Basic competences applicable to various problems.
- Ability to learn from structured and unstructured data.
- Generation of multiple outputs such as texts, images, speech, video, and designs.
- An intuitive, conversational user interface.

In pharma, generative AI is used for activities like writing marketing materials, generating webinars, building image and video libraries, spotting segmentation opportunities, and speeding up marketing processes. It is projected to grow faster in healthcare than any other industry, potentially generating between $60 billion and $110 billion a year in economic value for the pharma and MedTech industries, with most value going to commercial operations.

Tags AI, pharma marketing

MedTech Pharma Marketing

Multichannel vs Omnichannel in Pharma Marketing

Post author By Piotr Wrzosinski
Post date 06/08/2025
No Comments on Multichannel vs Omnichannel in Pharma Marketing

What is the difference between multichannel and omnichannel marketing in pharma and MedTech?

Multichannel marketing uses multiple independent channels (like television, social media, email, websites) to communicate with customers. In this approach, channels often operate as silos, repeating the same message, with the focus remaining on the product rather than the user. It lacks a connecting node between channels.

Omnichannel marketing also engages multiple channels, but they are all integrated and coordinated to provide a unified, seamless, and personalized experience for the customer, who is placed at the center of the marketing funnel. This approach ensures that information is available precisely when needed, encourages deeper content exploration, and reinforces messages across touchpoints, ultimately improving engagement and fostering trust.

According to McKinsey, correctly implemented omnichannel models can lead to 5-10% revenue growth and 10-20% marketing efficiencies and cost savings for pharma companies.