Design the trial your payer will believe. Not just your regulator.
The comparison you are allowed to make at reimbursement is decided years earlier, at trial design. Axelium builds your evidence network now — so you can see where it breaks, a missing comparator or an unanchored node, while it is still a protocol decision, not a rejection.
From a comparator you hope connects to a network you have mapped.
Same workflow, two states. Flip the switch to see what changes.
Map the network now, not at rejection.
Build the comparator network from the evidence that already exists, see where your future comparison connects, and keep it current as the field moves.
Build the comparison once
- A systematic review and a network meta-analysis
- Anchored against every relevant comparator
- Defensible from the first submission
Re-runs on a schedule
- The whole pipeline re-runs on a cadence
- Flags when a new trial moves the result
- A signed record of what changed, each cycle
No black box
- Deterministic statistics — same inputs, same result
- Every estimate traces to its source study
- Change an assumption and re-run
Methods your payer already recognises.
We reproduced a published forest plot — exactly.
In our reproduction case study, Axelium rebuilt a published meta-analysis end to end and matched its pooled estimate. Same inputs, same numbers — because the statistical engine is deterministic.
Comparisons a committee will accept
Pairwise and network meta-analysis, plus population-adjusted indirect comparisons, with certainty grading — every step inspectable.
The questions a development team actually asks.
Guided setup does the mapping. You supply the question; the platform builds the network and shows where it connects.
The cheapest time to fix a disconnected comparison is before the protocol locks — not after the committee names it.