Specialty Pharma · Pre-Launch Commercial Intelligence

Targeting the
Invisible Patient

We map evidence graded clinical journeys against public health signals to support you in proving value for maximizing market share against complex clinical pathways. SignalIQ maps where patients should be, using the clinical pathway they travel before reaching treatment.

Complementary to existing analytics

Pre-Launch Strategy Preview
Executive Targeting Dashboard showing Japan prefecture map with opportunity scoring by tier

If any of this sounds familiar
"We don't know which territories to prioritise because we have no Rx history for this molecule yet."
Pre-launch / first-in-class
"We know the patient exists somewhere in the system, but they're not getting diagnosed or referred in time."
Underdiagnosed / rare disease
"Field resources are spread evenly across territories, but the real opportunity is probably concentrated in a handful of regions."
Resource allocation / field deployment
SignalIQ addresses all three by correlating published clinical evidence with government health data to show where the patient burden is, why it's not converting, and what to do about it by territory.
How the engagement works

No IT setup, no data sharing required from you. We run the analysis and deliver the intelligence.

No infrastructure on your end
No data sharing required
No platform to deploy

How It Works

Four phase methodology.
One self contained output.

From literature to live dashboard, structured to deliver directional intelligence before launch, without IT dependency or software licences.

Step 01

Literature Baseline

Peer-reviewed literature seeds an evidence-graded clinical indicator taxonomy specific to the disease and geography.

Step 02

Data Ingestion

Government health statistics and claims data structured by geographic unit, region, state, or province.

Step 03

AI Correlation

Statistical correlations identify which signals predict treatment burden. Only significant indicators contribute to the score.

Step 04

Executive Dashboard

Standalone intelligence output: zero IT implementation, no data sharing required and immediate compatibility with existing territory planning.


Decision Signals

Six signal categories.
Each independently scored.

The model draws on observable, publicly available data across the full patient pathway, from upstream disease burden through to system infrastructure readiness.

Upstream Disease Burden

Prevalence proxies identifying at-risk patient pools before diagnosis, the leading indicator of latent demand.

👁

Symptomatic Signals

Clinical presentations recorded separately: patients symptomatic but not yet confirmed for the target disease.

💊

Treatment Proxies

Current standard-of-care volumes confirming active, treatable disease. The primary conversion-ready signal.

🏥

Specialist Access

Specialist density and co-visit patterns, representing the care pathway the patient must traverse to reach treatment.

🔗

Referral Pathways

Signals revealing where patients are lost between diagnosis, specialist referral, and treatment initiation.

📊

System Readiness

Infrastructure signals: trial sites, infusion capacity, and diagnostic throughput, revealing structurally ready regions.


Regional Priority Output

Four tiers. Clear actions
for each.

Every region emerges from the model with a tier classification and a recommended commercial response, ready to sit in your monthly review.

Confirmed Burden

High signals + high treatment volume

Active patients on current standard of care. Most direct conversion opportunity.

Latent

High upstream + low treatment signal

Burden likely present but not reaching management. Education or access gap to address.

Surgical Heavy

High surgical + low medical therapy

Patients bypassing earlier intervention. Upstream prevention story strongest here.

Divest

Low signal across all categories

Thin market. Resources better deployed elsewhere this cycle.


Engagement Model

Research firm delivery.
Not software implementation.

SignalIQ runs the full analysis on our side. The client receives the intelligence, not a system to operate. No IT infrastructure required, no data sharing required from you, no platform to deploy or maintain.

🔬We run the analysis using publicly available government data. You provide no proprietary data to receive the output.
📁You receive the intelligence as a self-contained file, compatible with existing territory planning workflows.
🔒No cloud infrastructure, no login credentials, no vendor platform to onboard. It opens like any other document.
📊Output sits alongside your existing internal analytics. SignalIQ adds the external public data layer, not a replacement.
🔄Successive cycles can incorporate aggregated field observations at territory level to calibrate the model over time.

Data Sources

All publicly available
government databases.

All analysis is built on publicly available government databases. No insurer data, no patient records, no privacy risk. Fully compliant.

PubMed / PMC

Published medical journals. Used to map the patient journey and validate every indicator against peer-reviewed clinical evidence.

NDB / MHLW

National drug dispensing and procedure data by territory. The primary source for treatment proxies and surgical signal.

E-Stat

Medical infrastructure data. Clinic and specialist density mapping across geographic units.

MHLW Patient Survey

Disease prevalence by ICD-10 code. Upstream burden signal for the target condition.

MEDIS

Pharma master data. Brand and manufacturer mapping for treatment proxy validation.

PMDA + jRCT

Regulatory, safety, and package insert data plus clinical trials registry for competitive pipeline intelligence.


Engagement Structure

Scoped in phases.
Live output from week three.

Engagements are structured to deliver a working prototype early, so you see the methodology applied to your market before committing to a full engagement.

PhaseKey ActivitiesTimeline & Output
Phase 1
Feasibility
Discovery workshop: define up to 3 correlations, agree signals & visualisation approach. Patient journey mapping for target market.
Co-developed Statement of Work
1–2 weeks
Phase 2
Build & Deliver
Data ingestion, AI correlation analysis, visualisation build, commercial alignment session, Executive Dashboard delivery.
Targeting dashboard
3–4 weeks
Phase 3
Ongoing
New correlation sets on demand: each independently scoped, built and delivered as new commercial questions emerge. Minimum annual commitment keeps the model current as your launch evolves.
Updated dashboard layers
1–2 weeks per correlation set

All analysis is based on publicly available, non-sensitive government data. Outputs are directional intelligence tools, not absolute patient counts.

Work Together

Ready to see where your
market can realistically convert?

Every engagement starts with a scoped discovery workshop, so you define the correlations that matter to your commercial team before any data is run.

Registered
Signal Liquid Pte Ltd · Singapore
Focus
Specialty Pharma · APAC Markets
The prototype shown above is a working example of what is built for your product and market. Deliverables are with no cloud infrastructure and no vendor dependency.
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