Clinical-trial imaging analytics

Earlier proof that
neuro-recovery treatments
are working.

AI analysis of routine MRI scans to generate early treatment-response signals for stroke, traumatic brain injury, and spinal cord injury trials.

Request a pilot See the science

Stroke TBI Phase II / III trials Pharma & biotech sponsors

Axonomics AI: MRI-based neuro-recovery treatment-response analysis

Illustrative, not clinical data

The problem

The decision comes too late.

Patients recover at very different rates. Sponsors typically wait months for a clinical endpoint to read out — months of uncertainty that translate directly into wasted enrollment, wasted trial cost, and delayed go or no-go calls.

Timeline showing patients wait months for a clinical endpoint while trial cost accumulates

Treatment start

Trial begins. Baseline MRI collected. Clock starts.

Early window

Is it working? No answer available.

Mid window

Still no signal. Trial spend continues.

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.

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Routine MRI collected

Standard imaging already captured during the trial. Existing scanners and protocols.

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Secure upload & de-identification

Compliant data transfer from sponsor or imaging CRO. Audit trail on every step.

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AI extracts recovery patterns

Models identify imaging features associated with neurological recovery.

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Signal vs. expected recovery

Each patient scored against a model of natural recovery for that indication.

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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.

Sample output

What a sponsor receives.

A synthetic case, shown to illustrate the report format. Real reports are generated from de-identified patient imaging under a sponsor data-use agreement.

Axonomics response report

Recovery-trajectory tracking

Synthetic case — for illustration

Case ID

SYN-0417

Indication

Ischemic stroke

Imaging timepoint

Week 4 post-baseline

Expected recovery (age-matched, standard of care) Tracked signal — this patient

ON TRACK

Tracking above expected recovery trajectory at Week 4.

Model in development. Not for clinical use. Not FDA cleared. Report format shown for illustration; case data is synthetic.

Validation & traction

Building clinical proof points, one site at a time.

Multi-site validation strategy plus compute infrastructure already secured.

Active

University of Louisville

Dr. Saad Hassan, Stroke Medical Director, UofL Health, Jewish Hospital

Pilot test site identified. IRB submission underway with the Stroke Medical Director.

NVIDIA Inception · accepted 2026

NVIDIA Inception Program

Provides GPU cloud credits and technical resources for model training, reducing near-term compute cost as a constraint on our development timeline. Membership also reflects independent technical validation from a leading AI infrastructure provider.

The team

Built by people who know the problem.

Neuroscience expertise, machine learning depth, and clinical research credibility.

Mohammed Ali Alvi, MD, MS

Founder & CEO

10 Yrs Clinical AI Endpoint Design Expert Neuroimaging AI Pipeline

Built Axonomics to solve the problem he spent 10 years inside: pharma can’t measure neurorecovery outcomes fast enough to de-risk trials.
Clinical endpoint expert: deep fluency in NIHSS, ASIA motor, mRS and MRI biomarker qualification for regulatory submissions.
Established institutional access to rare neurorecovery imaging cohorts via formal research agreements.

Dr. Shams Syed

CTO & Co-Founder

15+ Yrs AI & ML 40+ Publications 2 US Patents

Built and deployed 30+ major AI systems; 15+ years AI/ML implementation, 20+ years software engineering in C/C++ and contemporary platforms.
2 US patents on generative AI and hybrid LLMs; 40+ publications spanning deep learning, computer vision, and multi-modal systems.
Deep expertise in multi-modal LLMs, GANs, CNNs, and 3D synthesis, principal engineer on enterprise-scale AI deployments across multiple industries.

Earlier proof that neuro-recovery treatments are working.