Pipeline Comparison: Company vs Company
Compare pipelines on PoS-weighted forward value, not asset counts.
A structured way to compare pharma pipelines company-by-company — phase, modality, TA distribution and PoS-weighted forward value.
"Whose pipeline is structurally stronger — by what measure, in what TA?"
Asset-count comparisons mislead. Pipeline comparison weighted by PoS, expected launch year and forecast peak revenue surfaces the real strength differential.
Pipeline comparison decoupled from PoS-weighted forward NPV is theatre. Done right, it is the most actionable BD and IC input a strategy team can produce.
What we’re seeing in the data.
Count ≠ value
50 Phase 1 assets ≠ 5 Phase 3 assets in NPV terms.
Concentration matters
TA-concentrated pipelines outperform diffuse ones in execution speed.
Modality breadth signals platform
A diverse modality footprint hints at a real platform versus opportunistic deal-making.
Forward NPV beats prior achievements
Pipelines should be valued by what’s ahead, not what already launched.
How to think about it.
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01
Build pipeline universe
All credible candidates per company.
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02
Score per asset
PoS, expected launch, peak revenue.
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03
Aggregate by TA
TA-level forward NPV.
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04
Compare across companies
Slice-and-dice by modality, phase, geography.
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05
Refresh on every readout
PoS and forecasts move materially.
What separates a good answer from a defensible one.
Not every credible asset can be manufactured at scale on time.
Combination dependencies link asset NPVs.
Patent expiry shapes effective revenue arc.
Launch sequence affects realized NPV.
Where the signal comes from.
Common questions.
Why not just use sell-side analyst forecasts?
They’re often outdated within a quarter. Build your own and update on readouts.
How granular for BD use?
Asset-level, with explicit PoS / launch / peak assumptions per asset.
Want this answered on your data?
We build decision systems on top of analyses like this — so the next question takes minutes, not weeks.
Talk to a strategist