Skip to content
Axelium
Existing users
For pharma market access & HEOR

Know the day the evidence turns against your drug. Before the committee does.

Your value story is judged against the whole treatment landscape — not the single comparator in your trial. Axelium builds the network meta-analysis behind that story and keeps it live: when a new competitor trial lands, it re-runs and shows you the shift, while there is still time to answer it.

See how living reviews work
Network meta-analysis · living reviews · deterministic statistics
Network meta-analysislive
Your position in the network
Your drug
pooled
Comparator A
0.86
Comparator B
↑ shifted
Comparator C
1.14
your drugcomparators
re-runs weekly
The shift

From a one-off comparison to a standing early-warning system.

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

Last comparison: 6 months ago · run by hand Live · re-runs weekly · signed each cycle
CadenceRebuilt by hand each submission cycleRe-runs automatically on a schedulemanualautomatic
Competitor readoutsNoticed months after they move your positionFlagged the day the trial is indexed~monthssame day
Assessor critiqueA surprise at the committeeStress-tested against the same methods firstreactivepre-empted
Every marketEach country's submission rebuilt from scratchOne evidence spine, re-projected per country×5 rebuilds×1 spine
Static — nothing is watchingMonitoring 4 comparators · 1 indication
How it works

Build the comparison once. Keep it live. Inspect everything.

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 that stand up to the same scrutiny.

Validation

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.

Network meta-analysisMAICSTCML-NMRGRADE certainty
Living reviews for competitors

Turn a completed submission into a standing watch.

A

Pick your battleground

Choose a drug, an indication, and a country. We scope the evidence network that decides its value.

B

Map the network

Your position against the whole field, today — anchored where the evidence connects, flagged where it doesn't.

C

Keep it live

When a competitor's trial changes the picture, the review re-runs and shows you the shift — in time to respond.

Straight answers

The questions access teams actually ask.

"AI in a submission?"

The statistics are deterministic and reproducible. AI assists data extraction; it never touches the numbers a committee sees.

"Just another tracker?"

Trackers tell you a decision happened. Axelium rebuilds the comparison that drives yours — and keeps it current.

"Our data is confidential."

Your data stays in your workspace. Every estimate is inspectable and traceable to its source.

✦

See your drug's position in the network — and what would move it.

Talk to sales
Questions

The details.

A completed systematic review or network meta-analysis that re-runs on a schedule and flags when the pooled result changes — so a finished submission becomes a standing early-warning system.