Next-Gen Research To Understand Patients

Menopause is serious—and it’s still massively undertreated

Only about 1 in 4 women are receiving any treatment for menopause symptoms. Many women with moderate to severe symptoms are simply “pushing through,” not taking steps to get care that will make a real difference in their lives.  AI research is a way for companies to understand the critical needs of patients.

For pharma teams building patient-centered communication and marketing strategies, that gap isn’t just a clinical issue—it’s a behavior + belief + barrier issue. And you can’t message your way through it unless you truly understand what’s holding patients back.

Consider “Mary R.” (name changed). In research, she described her situation as “normal.” But her story signaled moderate-to-severe impact:

• Sleep disruption

• Mood changes

• Reduced work productivity

• Serious strain in her family life

ThemeNav© Research

These are classic questions that must be addressed by patient research. Using the most recent developments in survey research, we have developed a cutting-edge methodology:

ThemeCompass© can also probe in real time—asking smart follow-ups based on what a participant just said.

This methodology permits deep dives into:

• Emotional impressions

• Feelings/Barriers

• Likelihood of discussing medication with a doctor

• Actual interactions with doctors (past visit recall)

• Likelihood of using medication to treat the condition (including new medications like Lynkuet, a nonhormonal treatment)

In Mary’s case, she shared she didn’t mention symptoms to her doctor because she felt embarrassed and expected dismissal. A targeted follow-up uncovered what mattered most: trust, self-advocacy, and fear of being minimized—key drivers that shape whether patients ever enter the treatment conversation (including newer nonhormonal options).

Traditionally, such questions could be asked by a live moderator.  However, the AI advantage is that the system can connect the dots real time (including quantitative responses) and probe deeper.  We’ll know if she talked with a doctor in the past 3 months, why and be able to predict (with a high level of probability) if she is likely to talk with a doctor in the near future.

A New Way to Capture Qualitative Depth Insights

At the start of each study, we tell each participant that they must provide very detailed responses to each question.  If they use a smart phone, they can use their microphone for their response. A response of 200-500 characters or more (at minimum a paragraph) is required before they proceed. With 200 respondents, that produces hundreds of pages of transcripts for analysis.  We then use AI to identify themes and link them to quantitative measures.

The result feels like 200 in-depth interviews inside a single study—anchored to specific metrics that support true drivers analysis. We can identify the barriers that block treatment and the triggers that move patients to act.