Case Study:
Understand How to Impact Patient Adherence Using Artificial Intelligence.
AI Provides Previously Unseen Insights to Increase Adherence to Medication
There are so many causes of non-adherence, but these differ depending on the therapy area, beliefs, culture and more. So how can you understand the causes of non-adherence for your brand and your market – from real world data and not doing more market research? You already have social listening data, call center data, market research data and a whole lot more. All of this can be analyzed using Artificial Intelligence to help you identify nuances that you had not seen previously.
The Client Problem
The pharma company had a challenge with adherence dropping off for their brand after 3 months. They had results of the market research but implementing the recommendations had not resulted in markedly better adherence performance. The market research team wanted to see if AI could analyze their existing data alongside other real-world data.
The Solution
They had a wealth of market research data, social listening data, call center data and more. All of the data was put into a proprietary platform which uses Natural Language Processing alongside Machine Learning to combine the data sources, including the social listening data, and analyze it to uncover nuances that were previously not picked up. [Note: Find out whose proprietary platform in the Eularis membership – it was not ours!]
The Outcome
The client was able to get numerous insights into the different causes of non-adherence that had not been previously uncovered with the market research alone approach. This led them into being able to design interventions that had a positive impact on increasing adherence to their medication.
To achieve these kinds of results, join Eularis membership today.
Latest News
Read our latest blogs here.

The Thirteen AI Output Failures Only Human Judgement Catches
You reviewed something this morning that an AI wrote. Maybe it was a medical information response, a slide, or a section of a report a

Your AI Training Worked. That’s the Problem.The AI capability problem pharma hasn’t named
The moment that stayed with me has happened in nearly every programme I’ve run. Someone goes further than the material — builds their own agents,

Cutting Headcount is the Smaller Bet in Pharma AI
In recent months, I have heard versions of the same conversation repeatedly. A functional leader describes a reorganisation in which headcount is down by 10