1
78%Injection fear before first biologic dose
Emotional52 quotes · Treatment initiation anxiety
“I stared at the pen for twenty minutes. Nobody showed me what a normal injection-site reaction actually looks like.”
Built for pharma insight teams and agencies
Patient barrier intelligence you can act on
Named barriers, sized by frequency, backed by verbatim evidence.
app.indicationiq.com/dashboard
Sample dataPlaque psoriasis biologic support — H1 2026
Patient SupportReviewModerate-to-severe plaque psoriasis · 1,184 evidence items
Ranked barriers
4 barriers identified
2
71%Flare mistaken for treatment failure
Information44 quotes · Expectation setting
“My skin got worse in week three and I assumed the biologic wasn't working. I almost stopped without calling anyone.”
Interactive preview with sample data — switch Barriers and Evidence in the sidebar
Social listening tells you mood. It doesn't tell you what to fix.
Pharma teams and agencies don't need another dashboard of positive, neutral, and negative mentions. They need to know which patient barriers recur, how often, and which verbatim quotes support the recommendation — before patient support materials, engagement strategy, or launch communications are written.
Who it's for
Built for the teams who need evidence, not adjectives
Pharma insight & patient engagement teams
- Support programmes built on assumptions, not evidence
- Social listening that scores sentiment but misses specific barriers
- Weeks of manual forum reading before a report is credible
Barrier-ranked insight with quotes your medical and compliance reviewers can audit.
Medical communications & insight agencies
- Client briefs that demand indication depth, not generic dashboards
- Analyst time sunk in qualitative coding instead of strategy
- Deliverables that need proof — not paraphrased themes
Faster, evidence-backed patient support and launch insight you can put in front of clients.
How it works
From public conversation to client-ready evidence
01
Configure an indication
Define the condition, therapeutic area, keywords, data sources, and project phase — patient support, HCP launch, or combined.
02
Collect public conversation
Gather posts from compliant open sources such as Reddit, X, and Bluesky using your indication-specific keyword set.
03
Extract named barriers
AI-assisted coding surfaces recurring barriers and themes — sized by frequency, not buried in a sentiment score.
04
Review and export evidence
Human reviewers validate insights against verbatim quotes, then export report-ready evidence for programmes and client deliverables.
Two core workflows
Patient support reports and HCP launch signals — by indication
Patient support intelligence
Understand what patients and caregivers suffer with in a specific indication — symptoms, fears, access friction, treatment misunderstandings, and support gaps.
- Ranked barrier cards with frequency
- Representative verbatim quotes
- Theme and burden-type coding
- Report-ready exports
HCP launch signals
Track what clinicians are saying publicly before and during launch — education gaps, messaging opportunities, and therapy-area conversation themes from compliant open sources.
- Indication-specific HCP language patterns
- Launch-relevant commentary themes
- Structured research inputs
- Evidence linked to source and date
Why IndicationIQ
Not a social listening dashboard. An evidence extraction engine.
Indication-first, not campaign-first
The unit of work is a therapy area and patient need — not a brand mention tracker.
Barriers, not sentiment
Outputs are named obstacles patients face — with frequency and proof — not positive/neutral/negative counts.
Quote-level audit trail
Every insight links to source, date, and verbatim text for regulated review workflows.
Human review by design
AI accelerates extraction; analysts stay in control before anything reaches a client report.
FAQ
Common questions from pharma and agency teams
- Who is IndicationIQ built for?
- Regulated pharma insight, patient engagement, and medical affairs teams — and the agencies that deliver patient support and launch communications insight on their behalf.
- How is this different from social listening tools?
- Social listening summarises volume and sentiment. IndicationIQ extracts specific, named patient barriers and HCP signals by indication — each backed by verbatim evidence your team can review and export.
- What data sources do you use?
- Public conversation from compliant open sources including Reddit, X, and Bluesky — configured per indication with clinical terms, lay language, and community-specific keywords.
- Can we use this for regulated client work?
- The product is designed around evidence auditability: quote-level provenance, human review workflows, and exports structured for insight and patient support reporting.
Start making decisions with evidence
See how IndicationIQ works on your therapy area and use case.