Ready for the future? How Agentic AI is reshaping Pharmaceutical business

The pharmaceutical sector is facing increasingly complex challenges, linked to the growth of available data, rising cost pressures, and the need to respond quickly to market demands. Artificial intelligence is emerging as a key solution, capable of supporting companies in making informed and rapid decisions. Specifically, Agentic AI is emerging as a crucial tool to optimize very specific processes, using data (both internal and external) from various sources, reducing repetitive tasks, and leveraging the ability to process large volumes of data.

The Contribution of Agentic AI in Pharma

Agentic AI represents a significant evolution over traditional AI agents. This organized group of intelligent agents not only performs highly focused tasks in collaboration, but works in a goal-oriented mode, which enhances the final result. In the pharmaceutical sector, Agentic AI is applied in various areas, from data management to content creation and validation, as well as sales support. By using advanced technologies, companies can optimize data analysis, predict customer behaviors, personalize communication, and improve commercial performance. This approach helps reduce response times, improve the quality of interactions, and make processes more efficient.

Practical Examples of Agentic AI Application in Pharma

Here are some practical examples developed by Hyntelo, an AI solution company of the Assist Digital group, based on Agentic AI projects in the pharmaceutical sector:

1. Agentic AI for a Data-Driven Strategy: Through the use of smart dashboards combining multiple agents, advanced segmentation (including unsupervised segmentation) can be performed, engagement indexes and channel propensity can be defined, and a 360-degree view of the target can be obtained. This optimizes the personalization of communication and improves the effectiveness of campaigns. This ability to analyze large quantities of data allows for quicker decisions based on concrete information.
2. Agentic AI for Scientific Information: AI provides crucial support for ISF (Medical Representatives), assisting them at every stage of their interaction with clinicians. By analyzing historical data in the CRM and past interactions, ISF can receive suggestions (Next Best Action) to define the best visit schedule, prepare meetings, identify the most relevant scientific material to present based on the clinician’s needs, and digitize sample distribution through image recognition. After the interaction, voice-based interactions can be used to take notes and enrich CRM insights. This helps improve the effectiveness of interactions, achieve ISF objectives, reduce administrative load, and increase coverage.
3. Agentic AI for Content Creation: Another application example is automation in creating promotional or training content. By initiating a series of specific agents working collaboratively on tasks, the best existing content can be selected, key messages defined, texts written and translated, claims verified for accuracy, proprietary taxonomy tags applied, and content pre-validated at both medical and regulatory levels. Companies can drastically reduce the time-to-market for content, also aiming for better quality.

Future Prospects for Agentic AI in Pharma

Looking to the future, the adoption of Agentic AI in the pharmaceutical sector is set to grow, bringing pharmaceutical companies' AI proof-of-concepts (POCs) to the next level.

In summary, the integration of an agentic approach is a true turning point in the pharmaceutical industry, offering tangible value through process automation, advanced data analysis, and amplifying the "human in the loop."

Companies can accelerate innovation, improve service quality, and respond more quickly to market needs. Hyntelo, with its innovative approach, is helping to define the future of the sector, making artificial intelligence an indispensable element in the evolution of pharmaceutical operations, bringing efficiency and value at every level.