Knowledgeable
Use case · Indirect comparison

Indirect treatment comparison

Indirect treatment comparisons your reviewer can reproduce.

Knowledgeable scaffolds anchored and unanchored matching-adjusted indirect comparisons (matching-adjusted indirect comparisons), network meta-analyses and standard indirect treatment comparisons against the competing treatments that actually matter to your HTA, with assumptions tracked, sensitivities pre-run and code your ERG or IQWiG can reproduce.

See it runTalk to an expert
Reviewer-grade
reproducibility
Days
from scope to results
100%
assumptions logged
Knowledgeable Live

Watch it run on your work.

HEOR statistician · global team
A scripted demo · click Continue below (or press Space) to send the brief and walk through the work step by step.
Grounded in 12 sources · audit-logged
HEOR statistician · global teamdraft
Click send to brief Knowledgeable…
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Background & context

Where this fits in your workflow.

Knowledgeable scaffolds anchored and unanchored matching-adjusted indirect comparisons (matching-adjusted indirect comparisons), network meta-analyses and standard indirect treatment comparisons against the competing treatments that actually matter to your HTA, with assumptions tracked, sensitivities pre-run and code your ERG or IQWiG can reproduce.

Most teams running Indirect comparison today juggle a stack of search tools, PDF readers and consultancy slides, then spend the back half of the project reconciling claims to sources. Knowledgeable collapses that into one defensible workflow: indirect treatment comparisons your reviewer can reproduce.

The work runs against your literature, trial registries, HTA precedent, label and SmPC, with every sentence pinpoint-cited so your senior reviewer opens a document that's already at QC.

Evidence sources
Published literatureTrial registriesHTA precedentLabel / SmPCConference abstractsReal-world data
How it runs
  1. 1Scope & competing treatment locked
  2. 2Evidence pulled & graded
  3. 3Draft built with citations
  4. 4QC pass against framework
What changes

The work that finally lands the way you scoped it.

Anchored, unanchored and network meta-analysis

Scaffolding that fits the evidence you actually have, not the method you wish applied.

Method-fit-for-evidence

Assumption tracker

Every clinical and methodological assumption logged with rationale and source. Sensitivities pre-run.

Audit-ready

Reviewer-reproducible

Code, inputs and data dictionary packaged so the ERG, IQWiG or HAS can re-run the analysis end-to-end.

Reproducible run

Drops into the dossier

Outputs land in the reviewer-shaped section of the AMNOG, NICE or HAS dossier with citations intact.

Dossier-ready

Defend the comparison, not the spreadsheet.

Scope your next indirect comparison
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Built for HTA scrutiny.

Methodologically defensible, fully audit-trailed and reproducible. ISPOR-grade, not vendor-grade.

Our approach to AI Security posture
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