RESOURCES

Blogs

Insight at the intersection of data science and real-world health

The Talking Room

Demystifying AI, LLMs and machine learning

Use Cases

How teams put the signals to work

Compliance Hub

Data integrity, ethical AI and regulatory standards

DrugVoice

Built to be defensible.

Compliance, ethics, and data integrity are part of the process.

TMLABS

About us

Where our proprietary models are trained, tested and refined

Articles & scientific publications

Peer-reviewed methodologies and validated outcomes

Latest paper

The New GLP-1 Consumer

Articles & Scientific Publications

DRUGVOICE

DrugVoice

Measure how your messaging lands and evidence what moved

SEE IT IN ACTION

Bring us a question you can’t answer.

We’ll show you what the conversation already contains, using your therapy area and your audience.

ABOUT US

About us

Where our proprietary models are trained, tested and refined

ESG

Responsible innovation and ethical data practice

WHO WE ARE

Data scientists who speak pharma.

A team built around one problem: making real-world conversation usable at scale.

Optimizing Messaging for Key Patient Personas with DrugVoice
Download

At a Glance

Challenges

  • Unable to understand if the term ‘Type II Inflammation’ was being used by Patients
  • Unable to identify if the term ‘Type II Inflammation would resonate with Patients

Benefits

  • Drives internal efficiency
  • Enhanced messaging by Patient Persona
  • Better understanding of Patient terminology being used

Customer Objective

A Healthcare Advertising Company (Customer) were working with a major Pharma Co (Client) on a strategic educational brand campaign. The Client worked in the Respiratory space and were looking to launch a campaign based on the term “Type II Inflammation”. They needed to understand whether Patients were actively using this terminology and whether it was likely to resonate with the various Patient personas that have this condition.

Brief

The Customer briefed Talking Medicines to curate their Client’s educational content, app data, website content, social sources, and survey data with DrugVoice. From this structuring and curation the Customer would then be able to understand the aggregated personas. The Customer could then use DrugVoice to ask natural language questions of each of these personas to determine whether Patients were discussing “Type II Inflammation” and if the term was understood.

Solution

Through using Talking Medicines DrugVoice, the Customer learned that only one group of patients were actively using the terminology “Type II Inflammation” and understood what it meant. Using this information the Customer was able to make more informed decisions, and subsequently adjusted their strategy and refined their messaging. The Customer measured the success of this through using DrugVoice again. The Advanced Data Science and AI-assisted approach led to an 80% improvement in efficiency, and provided longitudinal insights, decreasing manual bias.

Elevate Your Author Analysis with DrugVoice Intelligence

Contact Britt Gibson, Manager Global Customer Engagement, at britt@talkingmedicines.com.

Read More

#
$