Axelium
For biotech clinical development

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.

See how it works
Network meta-analysis · feasibility mapping · deterministic statistics
Forest plotlive
Random-effects pool · primary outcome6 studies
Smith 20240.62 [0.41, 0.94]
Chen 20230.71 [0.55, 0.92]
Patel 20240.83 [0.62, 1.11]
Garcia 20230.74 [0.58, 0.95]
Okafor 20240.88 [0.71, 1.09]
Müller 20221.05 [0.78, 1.41]
Pooled (RE)0.78 [0.65, 0.93]
study estimatepooled (RE)
RR, log scale
The shift

From a comparator you hope connects to a network you have mapped.

Same workflow, two states. Flip the switch to see what changes.

Live · re-maps as the field fills in

Evidence network
Kept current as new trials read out
living
Comparator gaps
Flagged while still a protocol choice
at protocol
Payer view
Modelled alongside the regulator’s
early
Tracking the evidence network as it fills in
How it works

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

Build the comparison once

  • A systematic review and a network meta-analysis
  • Anchored against every relevant comparator
  • Defensible from the first submission
Keep live

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
Inspect

No black box

  • Deterministic statistics — same inputs, same result
  • Every estimate traces to its source study
  • Change an assumption and re-run
Why trust it

Methods your payer already recognises.

Validation

We reproduced a published meta-analysis: 3 of 4 endpoints within 6%.

One analyst rebuilt a peer-reviewed meta-analysis end to end in 2 days. Pooled estimates for three of four endpoints landed within 6% of the published values, and the case study explains the fourth. The statistics are deterministic: the same inputs always give the same result.

Read the case study

Comparisons a committee will accept

Pairwise and network meta-analysis, plus population-adjusted indirect comparisons, with certainty grading — every step inspectable.

  • Network meta-analysis
  • MAIC
  • STC
  • ML-NMR
  • Custom methods
  • GRADE certainty
Straight answers

The questions a development team actually asks.

“We have no HEOR team yet.”

Guided setup does the mapping. You supply the question; the platform builds the network and shows where it connects.

“Isn’t this premature?”

The cheapest time to fix a disconnected comparison is before the protocol locks — not after the committee names it.

See where your evidence network breaks — while it is still a protocol decision.

Talk to sales
Questions

The details.

As soon as you have a candidate indication and endpoints. The evidence network can be mapped from the published literature before the pivotal trial is designed.