Key takeaways
- 5 conversion steps from incidence to your eligible cohort
- ~57% of NSCLC presents at advanced/metastatic stage
- 3 assumptions that drive the majority of estimate variance
- Y1·Y3·Y5 horizons modelled with testing-rate sensitivity
Your addressable market is a chain of conversion assumptions. If one step is wrong, the launch forecast is wrong — and it is usually the testing step.
Every NSCLC opportunity estimate is a funnel: incidence → advanced/metastatic → biomarker-tested → eligible → treated in your line. Each step is an assumption that has to be sourced, not guessed.
The biggest single driver of variance is biomarker testing penetration — the gap between patients who are eligible and those who are identified as eligible. A forecast that assumes full testing overstates the near-term addressable pool every time.
Below, we build the funnel the way your commercial analyst will have to defend it in the first forecast review.
Exhibit 4 — NSCLC patient funnel, US (illustrative).
Sources: Funnel percentages are typical-range and illustrative for this sample page. On a commissioned model, each conversion step is cited to a live SEER, NCCN, FDA, or peer-reviewed source and verified at point of writing; testing-penetration inputs are sourced and editable.
Five questions. Each section is built to answer one of them.
Every section answers a named commercial question your team is asking, scoped to your asset.
- How many patients enter the funnel, and at what stage? • Incidence base · stage distribution · advanced/metastatic entry pool
- How many are biomarker-tested and identified as eligible? • Testing penetration by biomarker · identification gap · trajectory
- How many reach your line of therapy? • Line-of-therapy attrition · treated-share assumptions · sourcing
- Which assumptions drive the variance? • Ranked driver list · sensitivity table · break-points
- What does the funnel look like at Y1, Y3, Y5? • Three-horizon projection · testing-rate scenarios · cohort splits
What's inside
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01 · The Funnel Frame pp. 1–3
- The five conversion steps and why each is an assumption
- Where your cohort enters the funnel
- What is sourced vs. modelled
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02 · Incidence Base pp. 4–6
- Incidence and stage distribution
- Advanced/metastatic entry pool
- Demographic skew that moves the base
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03 · The Testing Step pp. 7–11
- Biomarker testing penetration — the variance driver
- Diagnosed vs. identified gap
- Testing-rate trajectory and its forecast impact
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04 · Eligibility & Line pp. 12–16
- Eligibility funnel by cohort
- Line-of-therapy attrition
- Treated-share assumptions and their sources
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05 · Scenario Build pp. 17–21
- Conservative, base, aggressive funnels
- Testing-rate and staging-mix sensitivity
- Where the model breaks
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06 · Driver Ranking pp. 22–25
- The assumptions that drive 80% of variance
- Sensitivity table by driver
- Decision levers your team controls
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07 · Y1·Y3·Y5 Output pp. 26–28
- Patient volume by horizon and cohort
- Revenue translation inputs
- Confidence bands
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08 · Client Alignment Questions pp. 29–30
- Which conversion steps need primary validation
- Assumptions that will be challenged in forecast review
- Decisions contingent on testing-rate evolution
Appendix and source ledger included · 45-minute analyst readout included with delivery
Scoped to your cohort and line of therapy — not the market in aggregate.
Assess this reportIncluded with every brief
Get Started
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.
- 01. Submit your asset profileDrug, mechanism, proposed indication, target cohort, geography. Five minutes via the intake form.
- 02. Scope confirmed in 24 hoursWe confirm scope with your team, clarify ambiguities, and lock delivery timing.
- 03. Your patient flow model, delivered in 72 hoursPDF intelligence document, Excel model, and optional executive deck — with a 30-minute readout call included.
Every figure is live-sourced before delivery. If a number cannot be verified, it does not appear.
Prepared by MoatRx analysts on the AXLRx commercial consulting engine.
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.
Frequently asked questions
Scope Is the model editable?
Yes — the Excel funnel is fully editable with labelled, sourced assumptions, so your analyst can run sensitivities and re-scope without rebuilding it.
Sourcing Are the conversion rates sourced?
Every conversion step cites a live source at the point of writing and is cross-checked against it. The testing-penetration step, the biggest variance driver, is sourced and shown as a sensitivity, not a point estimate.
Delivery How fast?
72 hours from scope confirmation, with a 30-minute readout call. A 48-hour track is available.
Format What do we receive?
The editable Excel model is the core deliverable, plus a PDF brief walking through the funnel logic and an optional executive deck.
Process Can you model a specific cohort only?
Yes. Tell us the biomarker, line, and geography at intake and we scope the funnel to exactly that cohort.