SBIR Phase I proposal · PhenArI

Standardized immune monitoring for Alzheimer's patients on anti-amyloid therapy

CogniMune pairs a 40-color spectral flow cytometry panel with regularized optimal transport to turn a blood sample into an objective, comparable fingerprint of the peripheral immune system — tracked over the course of treatment with lecanemab (Leqembi) or donanemab (Kisunla).

Explore the science Phase I aims

colors: 39 immune markers plus a viability dye

n = 30

treated AD patients to be followed longitudinally

study cohorts, including untreated AD and controls

~O(n²)

per iteration with Sinkhorn–Knopp, down from O(n³ log n)

The challenge

New Alzheimer's therapies need new ways to monitor patients

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid plaque accumulation and neurofibrillary tangle formation. Recently approved disease-modifying therapies — lecanemab (Leqembi) and donanemab (Kisunla) — reduce amyloid deposits in the brain and have opened new possibilities for managing AD.

But these treatments may cause Amyloid-Related Imaging Abnormalities (ARIA), and the interaction between ARIA and systemic changes during therapy remains poorly understood. Monitoring solutions must efficiently and objectively guide therapy decisions while improving patient outcomes.

Figures as cited in the CogniMune Phase I proposal.

13.8 M

Americans projected to be affected by AD by 2060

~7 M

people aged 65 and older living with AD in the US in 2024

~900k

new cases of AD and related dementias diagnosed in the US each year

60–70%

of all dementia cases are caused by AD

A critical gap

What is ARIA?

Amyloid-Related Imaging Abnormalities are side effects of amyloid-targeting antibody therapy. Their precise mechanisms are not fully understood, but there is increasing evidence of a connection with the immune system.

Seen on MRI

ARIA is detectable through MRI scans, which are scheduled at fixed points during treatment.

Blood–brain barrier

ARIA is associated with compromised blood–brain barrier (BBB) integrity and immune-inflammatory responses.

APOE ε4

ARIA is more likely in patients carrying the genetic variant APOE ε4 (over 50% of all cases).

Our approach

From a blood draw to an immune fingerprint

Peripheral immune-cell phenotypes are emerging as valuable, non-invasive indicators of both disease progression and treatment efficacy. CogniMune is designed to measure them with unprecedented resolution and compare them objectively over time.

1Measure

40-color spectral panel

A few milliliters of blood are labeled with 39 immune-marker antibodies plus a viability dye and acquired on a spectral flow cytometer — T, B, NK and NKT cells, neutrophils, monocytes, basophils, dendritic cells and innate lymphoid cells in a single tube.

2Process

Automated pipeline

Automated processing applies the same quality-controlled steps at every site and every visit, turning each acquisition into population frequencies and phenotype profiles ready for standardized analysis.

3Compare

Optimal-transport fingerprints

Sinkhorn-regularized optimal transport builds a graph of each immune profile. Graph edit and spectral distances quantify how a patient's immune system shifts from baseline — and which populations drive the change.

How the technology works

Phase I

Three Specific Aims

The proposal sets out three aims to establish a comprehensive, turnkey protocol for immune monitoring in patients undergoing disease-modifying therapies for AD.

1 Aim 1 Year 1 · Q1–Q2

Design & validate the 40-color panel

A 40-color spectral panel — 39 immune markers plus a viability dye — targeting T, B, NK and NKT cells, neutrophils, monocytes, basophils, dendritic cells and innate lymphoid cells, optimized on healthy-donor blood and validated according to CLSI H62.

Success criteria

Success criteria will be based on well published outcomes for panel design and optimization and for validation of this panel based on CLSI H62 guidelines.

Aim 1 in detail

2 Aim 2 Year 1 · Q2–Q3

Find the markers that track ARIA risk

A longitudinal study of AD patients starting lecanemab or donanemab (n=30) over a 12-month treatment cycle, sampled before initiation (BL, week 0), at treatment visits through week 16 and at week 52 (T26), compared with untreated AD patients and three control cohorts.

Success criteria

The success criteria will be to determine the correlation of the immune profile with the minimum dose required and how this impacts the relevant population for future studies, specifically focusing on the immune cell populations affected by treatment.

Aim 2 in detail

3 Aim 3 Year 1 Q3 – Year 2 Q4

Automate analysis with OT fingerprints

Automated pipelines that turn cytometry readouts into graph-based immune fingerprints using Sinkhorn-regularized optimal transport, compared over time with graph edit and spectral distances.

Success criteria

Success criteria will be to establish automated functional connectivity fingerprint characterization of the immediate response of the AD patients.

Aim 3 in detail

Why it matters

Objective monitoring for everyone involved in AD care

Healthcare providers, pharmaceutical companies, and insurers will benefit from diagnostic systems that are automated, accurate, and scalable to monitor treatment efficiency in patients with AD.
CogniMune Phase I proposal, project summary

Clinicians

Dynamic treatment-response monitoring throughout therapy, instead of binary tests that merely confirm AD presence.

Longitudinal profiles that could flag ARIA risk before clinical manifestation
Graph-based views that do not require familiarity with the mathematics

Pharmaceutical companies

A standardized platform for immune monitoring across multiple clinical sites.

OT Sinkhorn distances quantify immune changes objectively, without subjective interpretation variability
Insight into how therapies act on peripheral immune cells

Insurers

An automated, scalable, blood-based monitoring pipeline that can share the blood draw of plasma-based AD tests.

For context: MRI plus CSF testing for an estimated 1.8 M tests a year costs about $16.2 billion
From episodic assessment to continuous, quantitative immune surveillance

In collaboration with

Indiana University School of MedicineBrain Health Program (BHP) · Patient access & clinical data

Our Blood InstituteOklahoma City · Healthy control samples

Purdue UniversitySubcontract · Algorithms & data science

About our partners

Looking ahead · Phase II

From a validated protocol to a cloud platform

The results of Phase I will lay the groundwork for Phase II: a cloud-based system where data processing is done automatically, based on prior established immunophenotyping panels.

Clinicians will upload cytometry files, OT-based summaries are computed automatically, and immunologic shifts are visualized without requiring familiarity with the underlying mathematics.

Amazon Web Services HIPAA compliance via BAA De-identified data in Phase I

Upload

Cytometry files from the clinic

Process

Spectral unmixing, optimal transport, graph building and matching

Review

Immune fingerprints and shifts over time

Interested in CogniMune?

We welcome inquiries from clinicians, researchers, industry and investors. Study-team members can sign in to the research portal.

Contact the team Study-team portal