Oncology/NSCLC/Disease Landscape

AXLRx · Disease Landscape Brief

The NSCLC patient population, defined.

How the NSCLC population segments by histology, stage, and biomarker — and where each segment is actually treated — before you size a single opportunity.

NSCLC · US MarketDisease Landscape72-Hour Delivery30 Pages · 3 Outputs100% Live-Sourced

NSCLC is not one disease. It is a stack of biomarker-defined segments, each with its own standard of care and its own addressable size.

Non-small cell lung cancer accounts for roughly 85% of lung cancer. But "NSCLC" is a label over a dozen actionable molecular segments — EGFR, ALK, KRAS G12C, ROS1, PD-L1 tiers — each with a different dominant therapy and a different patient volume. Sizing the wrong segment is the most common pre-launch error.

Testing penetration determines how many of those biomarker-defined patients are actually identified and treatable. The gap between the epidemiological population and the tested, eligible population is where most addressable-market estimates break.

Below, we segment the population the way your commercial model has to — and show where the data is solid and where it is assumption.

~85%
of lung cancer is non-small cell histology
~226k
estimated new US lung cancer cases per year (all types)
5+
actionable molecular segments that each demand separate sizing
~57%
of NSCLC diagnosed at distant/metastatic stage

Five questions. Each section is built to answer one of them.

Structured by decision, not by topic — every section feeds a specific commercial call.

01

How does NSCLC segment by histology, stage, and actionable biomarker?

DeliversSegmentation map · histology split · biomarker prevalence with testing-rate caveats
02

How many patients sit in each segment — and how many are actually identified?

DeliversPopulation by segment · diagnosed vs. tested gap · five-year trend
03

What is the standard of care in each segment today?

DeliversTreatment pattern by line and segment · guideline-anchored · real-world adoption
04

Where is the unmet need current therapy has not addressed?

DeliversProgression and non-response cohorts · segment-level gap analysis
05

How is the landscape shifting — pipeline, testing, and guideline change?

DeliversPipeline by segment · testing-rate trajectory · guideline-change watch
Scoped to your asset's target segment — not the disease in aggregate.
Scope Your Work

Eight sections. Every section structured around a named commercial question.

What your team receives. Section scope is built around your asset and proposed label — not pulled from a generic template.

AXLRx™ · Intelligence Brief · Disease Landscape
Non-Small Cell Lung Cancer — Disease Landscape, US
Prepared for [Client]  ·  Q2 2026  ·  30 pages  ·  Confidential
Contents
  • 01The Segmentation Framepp. 1–3
    • Why histology + biomarker, not stage alone, defines the commercial map
    • The segments your asset actually competes in
    • What secondary data resolves vs. what needs primary work
  • 02Epidemiology Basepp. 4–7
    • Incidence and prevalence, US
    • Stage distribution at diagnosis
    • Demographic and risk-factor skew
  • 03Molecular Segmentationpp. 8–13
    • Biomarker prevalence — EGFR, ALK, KRAS G12C, ROS1, PD-L1 tiers
    • Testing penetration and the identification gap
    • Co-mutation and overlap considerations
  • 04Treatment Patternspp. 14–18
    • Standard of care by segment and line
    • Guideline anchors and real-world divergence
    • Where adoption lags the label
  • 05Unmet Need Mappp. 19–22
    • Progression-after-IO and non-responder cohorts
    • Segment-level gaps your mechanism might address
    • Sequencing pressure points
  • 06The Shifting Landscapepp. 23–25
    • Pipeline entrants by segment
    • Testing-rate trajectory
    • Guideline-change watch
  • 07The Assumption Registerpp. 26–28
    • Which population figures are solid and which are modelled
    • The inputs that drive estimate variance
    • Sensitivity on testing penetration
  • 08Client Alignment Questionspp. 29–30
    • Evidence gaps secondary research cannot close
    • Where your segment definition needs primary validation
    • Decisions contingent on label scope
  • Source Annex — all PMIDs, ClinicalTrials.gov IDs, and live URLs pp. A1–A6

At a glance

30pages across 8 structured sections
5commercial questions answered
72hfrom scope confirmation to delivery
100%of figures cited to live source

Readout call included

All deliveries include a 30-minute call with your analyst — to walk through findings and identify what your team needs to resolve next.

Three outputs delivered within 72 hours. Each built for a different role in your commercial team.

The intelligence analysis, the working model, and the board summary — delivered together.

Core Deliverable
PDF
PDF · ~30 pages
Intelligence Brief

Structured for sequential reading by your launch lead, medical affairs director, and market access team. Every exhibit sourced.

  • Executive summary — 3 pages, decision-level
  • Full analysis by section
  • Every exhibit cited to a live source
  • Source annex — all PMIDs and live URLs
XLS
Excel Workbook
Segmentation Model

A live, editable model that splits the NSCLC population by histology, stage, and biomarker — with labelled, sourced assumptions your analyst can adjust.

  • Population by segment with prevalence inputs
  • Testing-rate adjustment layer
  • Diagnosed vs. identified gap
  • Five-year projection
  • Sensitivity on the top assumptions
PPT
PowerPoint · Optional Add-on
Executive Deck

Five slides your leadership team can act on — structured around decisions, not descriptions.

  • Market opportunity — cohort-level
  • Competitive position and key threats
  • Payer readiness gap
  • Patient capture scenarios
  • Priority decisions and open questions

Exhibit 2 — NSCLC molecular segmentation, US.

Illustrative segmentation. Prevalence ranges are segment-typical and shown to demonstrate the depth and sourcing standard your team receives — every figure on a commissioned brief is cited at the exhibit foot.

Molecular Segmentation — NSCLC, US · Q2 2026 Sample · Illustrative
SegmentApprox. share of NSCLCDominant 1L approachIdentification depends onCommercial note
EGFR-mutantAdenocarcinoma-skewed ~15% (US) EGFR TKI (osimertinib) NGS / EGFR testing at dx Crowded; resistance-setting opportunity
ALK-positiveYounger, never-smoker skew ~4% ALK TKI FISH / NGS Small but high-value, durable
KRAS G12CSmoking-associated ~13% Chemo-IO; emerging G12C inhibitors NGS Active pipeline battleground
PD-L1 high (≥50%), no driverSee CI brief ~25–30% of non-driver IO monotherapy PD-L1 IHC IO incumbent-dominated
[YOUR SEGMENT][Client] · Confidential Defined at intake Scope-dependent Per proposed biomarker Sized to your asset
Sources: Segment prevalence ranges are segment-typical and illustrative for this sample page. On a commissioned brief, each figure is cited to a live SEER, NCCN, FDA, or peer-reviewed source at the exhibit foot and verified at point of writing.

Every figure is live-sourced before delivery. If a number cannot be verified, it does not appear.

This is a field where AI confidently reproduces outdated epidemiology, superseded payer policy, and retracted analyses. AXLRx uses none of its own memory as a source. Every figure your team receives is verified against a live document at the time of writing.

A wrong number in front of your payer or your leadership team is not recoverable in the same meeting.

  • Every claim cited to a live PMID, ClinicalTrials.gov ID, or URL at point of writing — uncited claims are dropped, not estimated
  • PubMed metadata fetched live during authoring — model memory produces incorrect author and journal data even on correct PMIDs
  • Numeric cross-check: the specific figure must appear in the cited source, not merely be consistent with its topic
  • Independent audit pass after generation — broken links, unsourced claims, and numeric inconsistencies flagged before delivery
  • Drop gate: any figure that cannot clear the above is removed. No confidence tiers. No exceptions.

What commercial teams ask before commissioning.

Scope
Is this a generic NSCLC overview?
No. The landscape is segmented to the part of NSCLC your asset competes in, with the population and treatment data your model actually needs — not a textbook summary.
Sourcing
Where do the population figures come from?
Every figure is cited to a live SEER, NCCN, FDA, or peer-reviewed source at the point of writing, and cross-checked to appear in that source. Unverifiable figures are dropped.
Delivery
How fast?
72 hours from scope confirmation, with a 30-minute readout call included. A 48-hour track is available for board deadlines.
Format
Do we get an editable model?
Yes — the Excel segmentation model is fully editable with labelled assumptions, so your analyst can run sensitivities without rebuilding it.
Process
Can we commission just the segmentation?
Yes. Scoped standalone sections are available and priced by scope. Tell us at intake which questions your team needs answered.

Tell us your asset. Your team has the intelligence in 72 hours.

We build from your asset's clinical profile — mechanism, biomarker strategy, proposed label, and target cohort. Scope confirmation takes one call.

Start Your Request

Or see a sample output to review the depth before committing.

01

Submit your asset profile

Drug, mechanism, proposed indication, target cohort, geography. Five minutes via the intake form.

02

Scope confirmed in 24 hours

We confirm scope with your team, clarify ambiguities, and lock delivery timing.

03

Your disease landscape, delivered in 72 hours

PDF intelligence document, Excel model, and optional executive deck — with a 30-minute readout call included.