Aramintas
Aramintas uses multi-dimensional artificial intelligence algorithms to connect the right patients with the right clinical trials — faster, more accurately, and at scale.
How Matching Works
Finding the right clinical trial for a patient — or the right patient for a trial — has historically been a manual, error-prone process. Aramintas changes that by applying layered algorithmic logic across structured and unstructured healthcare data.
Our engine ingests patient profiles, EHR data, and trial eligibility criteria simultaneously, then scores and ranks matches in real time. The result: faster enrollment, better protocol adherence, and improved outcomes for sponsors and patients alike.
Eligibility Criteria Parsing.
Natural language processing converts free-text inclusion and exclusion criteria.
Multi-Factor Scoring
Each patient-trial pair is scored across dozens of weighted dimensions, producing a ranked match list.
Adaptive Learning
Match quality improves continuously.
Real-Time Data Integration
Aramintas connects to lab platforms, registries, and APIs ensuring patient profiles reflect the most current clinical data.
Privacy-Preserving Architecture
All matching computations are performed on de-identified data.
Explainable Match Rationale
Every match surfaces a plain-language rationale, ie. which criteria were met, which were borderline, and what data informed the score.
Ready to accelerate enrollment?
Talk to our team about integrating Aramintas matching into your research workflow.
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