AXONOMICS-AI
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Clinical-trial imaging analytics
Earlier proof thatneuro-recovery treatments
AI analysis of routine MRI scans to generate early treatment-response signals
for stroke, traumatic brain injury, and spinal cord injury trials.
Stroke
TBI
Spinal core injury
Phase II / III trials
Pharma & biotech sponsors
6mo
Typical endpoint wait time
$ 1M+
Daily Phase II/III trial burn
0
Early response signals available today
The problem
The decision comes too late.
Patients recover at very different rates. Sponsors typically wait months for
a clinical endpoint to read out. That uncertainty translates directly into
wasted enrollment, wasted trial cost, and delayed go or no-go calls.
W0
Treatment start
Trial begins. Baseline MRI collected. Clock starts.
W4
Early window
Is it working? No answer available.
W8
Mid window
Still no signal. Trial spend continues.
M6
Primary endpoint
Answer finally arrives. Too late for early decisions.
The solution
Earlier signal. Better decisions.
Axonomics doesn't replace the trial. It improves the timing and quality of
the decision — using the same routine MRI scans the trial already collects.
Without Axonomics
✕
Decision waits for the primary clinical endpoint
✕
High uncertainty during the early window
✕
Continued spend on programs that may not be working
✕
Difficult conversations with board and investors
With Axonomics
✓
Earlier go or no-go support in the trial
✓
Better patient selection in future cohorts
✓
Stronger endpoint and trial-design confidence
✓
Clearer story for board and investors
How it works
MRI scans in. Early response report out.
No new scanners. No new protocols. Fits inside the sponsor's existing
imaging workflow. Output: an auditable report, not a research file.
01
⬡
Routine MRI collected
Standard imaging already captured during the trial. Existing scanners and protocols.
02
⬡
Secure upload & de-identification
Compliant data transfer from sponsor or imaging CRO. Audit trail on every step.
03
⬡
AI extracts recovery patterns
Models identify imaging features associated with neurological recovery.
04
⬡
Signal vs. expected recovery
Each patient scored against a model of natural recovery for that indication.
05
⬡
Sponsor report delivered
An auditable readout to support trial-decision conversations with the team.
Scientific basis
The signal is already in the scan.
Routine MRI contains biological information correlated with neurological
recovery. The data exists. What's required is the model to extract it.
1,715
SOOP dataset — stroke
MRI with linked NIHSS outcomes. Candidate training cohort for stroke trajectory modelling.
3,000
TRACK-TBI — traumatic brain injury
MRI with GOSE outcome measures. Key dataset for TBI recovery pattern extraction.
4,500
CENTER-TBI — European TBI cohort
Multi-site European dataset with detailed outcome labelling across injury severity.
The team
Built by people who know the problem.
Neuroscience expertise, machine learning depth, and clinical research credibility.
MAA
Mohammed Ali Alvi
Founder & CEO
MHJ
Muhammad Hasan Jafry
ML Lead
MF
Michael G. Fehlings
Scientific Advisor
