Ascentra · A²I™ Device

Get medical devices to those who need them most

Data intelligence to inform equitable and fair access to medical devices

Three markets. One disciplined evidence narrative.

Move from rejection-pattern matching to risk rehearsal — across device reimbursement pathways in Australia, the UK, and New Zealand.

01

HTA Pattern Match

34 structured rejection patterns drawn from published MSAC, NICE, and PHARMAC guidance show which device evidence claims have historically determined funding outcomes.

Explore corpus →

02

Evidence Claim Risk

Not all evidence carries equal weight. Identify which claims in your evidence base have been challenged in similar device submissions — ranked by relevance to your device class.

View risk patterns →

03

Remediation Map

For every high-risk claim, see what evidence — including in silico device simulation where accepted — has historically closed the gap.

Equity landscape →

Device class intelligence

Explore rejection patterns and equity signals by device class.

Query 34 MSAC / NICE / PHARMAC device patterns

Filter by body, domain, device class, and in-silico mitigation path.

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