mama health: patient intelligence for commercial teams

See what could stall adoption before it becomes a launch problem.

Your data shows what happened. The patient side shows why.

Bring us your question

60,000+ patients across 16 markets

Trusted by global life science teams

NovartisUCBTakedaAmgenIdorsiaOtsuka
60%

of drug launches miss year-1 forecasts.

The patient-side signals often appear before the performance gap does.

From reaching patients to understanding them.

One connected system. Patient reach creates the opportunity for patient intelligence, and that intelligence makes the next decision better.

You

Bring a question

A commercial question about your market.

mama health

Reach

We reach people living with the condition.

Engage

They start a conversation, not a static page.

Activate

They take a next step, like preparing for a doctor visit.

Understand

Conversations are structured and medically validated.

You

Get patient evidence

To answer your question and decide.

Improve. What patients tell you shapes the next campaign, message or support decision.

What patients reveal.

The switch is in your data. The reason isn't.

So positioning can answer what patients actually expect next.

Example USPsoriasisTreatment changes

Reasons for changing treatment

What they wanted next Fully clear skin, not just improvement.

In US psoriasis, half of patients who changed treatment said it wasn't working well enough. What they wanted next was fully clear skin.

Based on 133 US psoriasis patients who gave a reason for changing treatment. Patients could give more than one reason. Expectation theme from 38 patient conversations.

Adoption is in your data. What holds it back isn't.

So launch plans can address the doubts that stop patients before a prescription is written.

Example USDiabetesNever started

Reasons for never starting a recommended treatment

Inside "own choice" 30 patients

20declined a newer diabetes drug class
26only discussed, never prescribed
6prescribed, then not started

Most patients who chose not to start never got a prescription.

Base: 104 US diabetes patients who gave a reason, more than one allowed. Breakdown: 30 patients. Includes treatments for other conditions.

Every finding reports its patient base. Data is anonymised and aggregated, GDPR & HIPAA compliant, and medically supervised.

The patient conversation is already happening.

The question is whether your team is looking at it.

  • Continuous, direct patient conversations
  • Anonymised and aggregated data
  • Clinical oversight and validation
  • Used by leading global pharma companies

What would you ask?

Bring one of these, or your own.

Where could adoption break down? Why are patients changing treatment? Where does the journey differ from expectations? What matters most to patients?

Bring us your question.

Pick a time for a 30-minute call. We'll show you how patient intelligence could answer it.

The booking calendar loads here on the live page.