Engineered cell therapy
has been missing
its computational infrastructure.

The intellectual foundation — patent-pending, architected, and ready to build.

PCT Filing Deadline · March 2027 · Strategic Window Open Now
Current Blockers

Five failures compounding at the same time

Every CAR-T program building AI infrastructure hits the same wall — in five places simultaneously. Mednos AI was the first system designed to remove all five.

01

Measurement non-comparability

The same analyte reads differently on different instruments. The failure is not in YOUR model — it is in the measurements the model receives.

Mednos AI turns inconsistent measurements into comparable, reliable data across platforms — while preserving full traceability and control.

Mednos Harmonizes™ →
02

Pre-Authorization without risk computation

As CAR-T scales, no computable standard exists to benchmark a facility's execution risk against regional peers before a payer authorizes a $400K+ therapy.

Mednos Compares™ →
03

No temporal toxicity prediction

Serious adverse events are best projected on temporal changes — not single lab values at one point in time. Delayed multi-organ toxicities across multiple organ systems are not addressed by any currently marketed clinical decision support product.

Mednos is Temporal™ →
04

The PHI de-identification blocker

True de-identification cannot be guaranteed — a legal blocker that stops multi-institutional deployment cold. What leaves each Mednos institution is a governed, de-identified summary of measurement environment characteristics. Not patient data in any form.

Mednos AI was designed so this blocker never exists.

Mednos Uses No PHI™ →
05

The Incumbent System Rabbit Hole

Your EHR vendor cannot build this. Clinical platforms govern patient workflows — not instrument-level measurement control, GMP environments, or PCCP-compatible model update controls.

The right vendor for CAR-T AI infrastructure is not your incumbent system. It has to be purpose-built.

PCCP (Predetermined Change Control Plan): The FDA framework that allows a cleared AI system to update its parameters post-market without a new regulatory submission, provided governance conditions are defined and approved in advance.

Mednos is Use-Case Integrated™ →
Market Context · June 2025
FDA eliminated REMS requirements for approved autologous CD19- and BCMA (B-Cell Maturation Antigen)-directed CAR-T therapies in June 2025 — expanding access beyond an estimated 150 or fewer certified centers to regional and community hospitals.

The safety infrastructure that REMS provided does not disappear with the requirement. Regional hospitals now have the authorization to treat — but not the AI infrastructure to do it safely and defensibly.

REMS is gone. The safety infrastructure gap it leaves at regional hospitals is not. Mednos AI fills it.

REMS (Risk Evaluation and Mitigation Strategy): An FDA-mandated safety and access control program for high-risk therapies. CAR-T therapies historically required REMS certification — mandating specific treatment centers and strict monitoring protocols. These requirements were removed in June 2025 as clinical management of toxicities matured.

Competitive landscape

Mednos AI versus the others.

Platform Capability Comparison
CAPABILITY
Current Platform
Mednos AI
CAR-T clinical decision support at point of care
PHI stays inside your network — by architecture, not policy
Cross-site lab data your AI models can actually trust
Adverse event prediction before the patient reaches infusion
Computable payer authorization with an immutable audit trail
AI control layer designed for post-clearance parameter updates
Works alongside your EHR — not instead of it
Three Capabilities · Three Patent Families
Family 01 · Clinical AI
Clinical AI · Post-Infusion Monitoring
Predicted Toxicity Risk · Current Trajectory
CRS Grade ≥2
68%
ICANS Grade ≥2
41%
Delayed CirAE · Cardiovascular 22%
AI Draft Orders · Pending Approval
Cardiac telemetry × 72hUnsigned
Tocilizumab 8 mg/kg IV — on-callUnsigned
Neurology consult — ICANSUnsigned
Clinician confirmation required
No order executes without approval

Day +7 · CRS 68% · Three orders pending signature

CRS (Cytokine Release Syndrome): Acute inflammatory toxicity triggered by CAR-T cell activation — the primary serious adverse event in the first days post-infusion.  ICANS (Immune Effector Cell-Associated Neurotoxicity Syndrome): Neurologic toxicity occurring in the acute post-infusion window.  CirAE (CAR-T-associated immune-related Adverse Event): Delayed multi-organ toxicities emerging weeks to months post-infusion — distinct from CRS and ICANS.

Family 02 · Pre-Authorization
Regional Medical Center · Anti-BCMA CAR-T
Facility
Regional AMC
Therapy
Anti-BCMA CAR-T
Region
Northeast US
AI Risk Score Computation
Facility Risk Cost
$162,400
÷
Network Reference
$141,200
=
Risk Score
1.15
Authorization Decision · Three Possible Outcomes
Approved
Score within range
ACTIVE
Review Required
Score elevated
Not Recommended
Score exceeds threshold
⚑ Current Profile
Authorization held.
ICU response: 38 min avg.
✓ With Care Agreement
Risk score improves to 0.98.
Approved. Audit-traced.

Risk score 1.15 · Care agreement unlocks approval

Family 03 · Lab Harmonization
IL-6 pg/mL · Same patient · Four platforms
Raw · Unharmonized
Each analyzer uses different calibration standards. Same patient reads differently on every platform.
Harmonized · Comparable
Mednos AI returns each value to a governed common scale — audit-traced.
Analyzer A142.3
Analyzer A128.4
Analyzer B97.8
Analyzer B131.7
Analyzer C168.1
Analyzer C129.8
Analyzer D119.4
Analyzer D130.5
Result
70 pg/mL spread.
AI prediction unreliable.
✓ Governed Output
3 pg/mL spread.
Comparable. Audit-traced.

Same patient · Four platforms · Four different answers

HIPAA
ZONE
Institution
T-CELL
Donor Collection
CAR INSERT
GENE EDITING
CAR Construction
GMP
PRODUCTION
GMP Manufacturing
CAR-T
PATIENT
CAR-T Infusion
NO PHI CROSSES BOUNDARY
← Mednos Layers →
AI Layer 1
Governance
Harmonized Data Store
1,000,000 records
versioned · audit-traced
AI Layer 2
Outcomes Intelligence
Human In The Loop
AI Models
GUI #1 Clinical Support
PATIENT · PT-2847 · CAR-T
Infusion D+14 · BCMA target
ADVERSE EVENT PREDICTION
CRS · Grade 3+ 12%
ICANS · Grade 2+ 18%
Serious AE · 30d 8%
TEMPORAL RISK TRAJECTORY
Pre-infusion D+30
✓ CDS OUTPUT EHR-ready
GUI #2 Pre-Authorization
FACILITY EXECUTION RISK
Benchmark tier Regional Peer · Tier 1
Execution risk score 0.87 · Within threshold
AUDIT RECORD
Audit reference recorded
21 CFR Part 11 · PCCP
FACILITY AUTHORIZATION STATUS
AMC 1 ✓ Recommended
Community Hosp. · NE-447 ⚠ Review Required
Regional Med. Ctr. · SW-112 ✗ Not Recommended
✓ Recommended Audit-traced
Governed Outputs
CDS OUTPUT
CLINICIAN
SAE (Serious Adverse Event) Risk Prediction
AUTH PRE-AUTH
PAYER
Pre-Auth Assessment
LAB HARMONIZED
QA SCIENTIST
Harmonized Lab Data
FDA PCCP ✓ AUDIT PCCP AUDIT
REGULATOR
PCCP Audit Trail
Metadata in  ·  Intelligence out  ·  No PHI transmitted
6
Provisional applications.
No horizontal platform covers this ground.
3
Interconnected families — no
platform covers all three
GCP · GMP · GLP
The regulatory triad no
horizontal AI system governs
PCCP
Predetermined Change Control Plan —
the FDA barrier every buyer faces.
Built in from claim one.
Ken
Harris
Founder & CEO
Mednos AI, Inc.
Boston, Massachusetts
Delaware C-Corp · 2026

Ken Harris is the Founder and CEO of Mednos AI. He brings more than three decades of experience in healthcare and seven years in healthcare AI, having led the development and deployment of more than 100 clinical and clinical research AI tools — working alongside teams of MD and PhD subject matter experts across the full healthcare enterprise.

Prior to founding Mednos AI, he held senior commercial AI leadership roles at a global cloud and AI platform and at a leading cell and gene therapy organization. Earlier in his career, he founded a cell therapy company that reached Nasdaq — and witnessed firsthand the computational and data infrastructure failures that limited the field's potential. Those failures became the founding thesis of Mednos AI.

He has direct operational experience across clinical decision support, regulated manufacturing environments, complex multi-modal precision medicine AI models, and outcomes-based reimbursement — the four domains the Mednos AI patent portfolio addresses.

Mednos AI, Inc. is incorporated in Delaware and headquartered in Boston, Massachusetts.

30+
Years in healthcare
7
Years in healthcare AI
100+
AI tools built & deployed
1
Cell therapy Nasdaq exit
Security architecture
No PHI ever leaves your institution.
That is architecture, not policy.™
FEDERATED COMPUTATION · STRUCTURAL GUARANTEE · ON-PREMISES AVAILABLE

Mednos AI operates on a federated computation model. What leaves your institution depends on which capability is in use — but in every case, it is a governed, de-identified summary, never patient data in any form.

For lab measurement harmonization: a de-identified characterization of your measurement environment. No patient data in any form — no patient identifiers, no patient measurements, no information from which a patient record could be reconstructed.

For pre-authorization governance: de-identified operational performance indicators specific to your facility. No patient records, no patient-level data in any form.

On-premises deployment is supported for payers and health systems with FedRAMP or data residency requirements.

"The privacy guarantee is an architectural property of the system. It is not a contractual commitment that depends on vendor compliance — it is a structural impossibility for PHI to leave your network perimeter."

01 · FEDERATED LEARNING

No raw data centralized, ever

Each institution processes its own data locally. Only a governed, de-identified summary transmits centrally. Raw patient data never moves.

02 · PRIVACY-PRESERVING TRANSMISSION

Measurement environment data, not patient biology

The governed summary transmitted describes your measurement environment — not patient biology. It contains no patient identifiers, no patient measurements, and no information from which a patient record could be reconstructed.

03 · ON-PREMISES DEPLOYMENT

Full network perimeter control

For payers, government contractors, and health systems with strict data residency requirements, the platform deploys entirely within your own infrastructure. No patient-derived data, model outputs, or authorization decisions are transmitted outside your network perimeter.

How it works

This is not a theoretical guarantee. It is a network already built to prove it.

Every institution. One governed network.
No PHI ever moves.

Each node transmits only a governed, de-identified summary to the governance core — never patient data in any form. The core continuously refines calibration and returns governed parameters to every participant.

Single Institution
No external transmission required
Federated Network
Every node improves every prediction
Governed. Auditable.
No data sharing required.
Teal — metadata in  ·  Gold — intelligence out
No PHI transmitted at any stage.
IP portfolio

Three patent families. One integrated stack.

Each family is independently licensable and architecturally interconnected. The Lab Harmonization family is the data foundation. Pre-Authorization and Clinical AI sit above it, sharing the same governance architecture.

Family 01 1 provisional
Clinical AI

Clinical Decision Support & Reimbursement Optimization

AI-driven prediction of CRS, ICANS, and delayed multi-organ adverse events across the full post-infusion window. EHR-integrated clinical decision support with clinician review workflow and structured reimbursement artifact generation for value-based payment programs.

Regulatory pathway
SaMD · FDA regulatory pathway under evaluation
Primary buyers
AMCs · Hospitals · Pharma · Biotech
Request portfolio overview →
Family 02 2 provisionals
Pre-Authorization

Execution Risk Modeling & Authorization Governance

Computable risk engine benchmarking facility execution against regional peers — including assessment before manufacturing is complete. Risk-weighted scoring driving authorization decisions for payers and enabling community hospital access to advanced cellular therapies.

Regulatory pathway
PCCP-compatible
Primary buyers
Payers · AMCs · Hospitals · Pharma
Request portfolio overview →
Family 03 3 provisionals
Lab Harmonization — Foundation

Measurement Harmonization, Regulatory Triad & Governance Architecture

Instrument-level measurement harmonization across platforms — with versioned governance provenance preserved for every value. Covers the full GCP · GMP · GLP regulatory triad with CDISC-formatted output for regulatory submissions.

Regulatory pathway
PCCP · 21 CFR Part 11
Primary buyers
CRO · Pharma · AMCs · Research Institutes
Request portfolio overview →
Why this IP matters

Every major healthcare AI platform was built for breadth. None was built for the regulatory and data infrastructure of engineered cell therapy. These six provisionals cover that gap — as an integrated, governed stack. Not replicable by a horizontal platform. Not on any timeline.

The ecosystem

The moat is the
network effect.

Early licensees gain a calibration advantage that compounds. The first to license does not just acquire a technology — they acquire a head start that grows.

You can build the model.
You cannot replicate the network.
The first to license shapes the standard.
Every participant after strengthens it.

That advantage is not available to a late entrant — at any price, on any timeline.

Strategic buyers

Six categories of licensees.

The portfolio serves the drug manufacturer's clinical affairs team, the hospital and provider, the clinical research statistician, and the manufacturing quality assurance department — across six distinct buyer segments. Licensing can be structured as field-of-use by segment, exclusive or non-exclusive, or as full portfolio acquisition. View the interactive buyer map →

🏥

Academic medical centers

CAR-T clinical decision support at the point of care. EHR-integrated CDS with clinician review workflow. Payer authorization artifact production for value-based payment.

Primary: Family 01 · Family 02
🧬

Pharmaceutical companies

GCP clinical trial lab harmonization with CDISC-formatted output. GLP nonclinical study harmonization for IND/BLA regulatory submissions. GMP batch-release governance.

Primary: Family 03
⚗️

Biotech companies

Pre-authorization governance for CAR-T commercial launch. Toxicity prediction for Phase 2/3 clinical programs. Full portfolio acquisition available.

Primary: Family 01 · Family 02
📋

Healthcare payers

Computable facility execution risk scoring for prior authorization — replacing subjective criteria with a benchmarked, auditable standard. Immutable audit trail per authorization decision.

Primary: Family 02
🏭

Manufacturers & CDMOs

GMP lot-release intelligence with versioned, audit-traced control per batch. Multi-site comparability packages for regulatory submissions.

Primary: Family 03
🔬

Contract research organizations

GCP central lab multi-instrument and reagent-lot normalization. CDISC-formatted harmonized datasets for sponsor eCTD submissions. A single CRO central lab is covered independently.

Primary: Family 03
Regulatory posture

Designed for FDA from the inception

Every patent family was designed for FDA's current and emerging AI guidance — and the governance framework is designed to align with the EU ATMP regulatory framework for global programs. Not adapted after the fact.

For global CAR-T programs, the governance design aligns with Regulation (EC) No 1394/2007, EMA's 2025 guideline on quality, non-clinical and clinical requirements for investigational ATMPs, and is positioned to support forthcoming EU pharmaceutical legislation reforms emphasizing digitalized regulatory processes and advanced therapy evaluation.

FDA Regulatory Strategy

Pre-authorization governance

Designed for FDA regulatory compliance from inception. Compatible with the Predetermined Change Control Plan framework — governance updates without re-submission.

21 CFR Part 11 compliant

Immutable audit trail throughout

Human-approved model updates, electronic signature workflows, and complete audit records across GCP, GMP, and GLP. Every decision is traceable to a specific governed version state — permanently and without modification.

FDA Regulatory Submission Ready

CDISC-formatted regulatory output

The lab harmonization family produces harmonized datasets with versioned governance identifiers carried directly into CDISC-formatted regulatory submission packages — no manual reformatting required.

PCCP governance architecture

Governance updates without re-submission

The system enables pre-authorized parameter improvements under a Predetermined Change Control Plan — the key FDA regulatory barrier this portfolio structurally resolves for every buyer segment.

DRAFT GUIDANCE
FDA · January 2025

AI in pharmaceutical manufacturing quality

FDA's 2025 draft guidance on the use of AI to support regulatory decision-making for drug and biological products specifically addresses AI use in the manufacturing phase for product quality decisions — including model credibility, audit traceability, and data integrity. The Mednos AI lab harmonization and GMP governance architecture was designed in direct alignment with this emerging framework. In regulated environments, draft guidance is directionally authoritative. We build to it.

Licensing & Acquisition

The portfolio is available.
The window is early.

This portfolio is available for exclusive or non-exclusive licensing, field-of-use licensing by buyer segment, and outright acquisition. Every provisional was built for regulatory compliance from the ground up — PCCP, 21 CFR Part 11, and FDA submission-ready throughout. Request the portfolio overview or contact us directly to begin.

Ken Harris · Founder & CEO, Mednos AI, Inc. · BD@mednos.ai · mednos.ai