# Automated molecular diagnosis on fine needle aspirates (FNA)

> **NIH NIH R43** · AIKILI BIOSYSTEMS INC. · 2021 · $400,000

## Abstract

Molecular analyses of cancer cells are essential in establishing diagnoses and guiding available
treatments. Conventional tissue biopsies, while providing key information on tissue architecture, are associated
with morbidity and high cost and therefore are not performed as frequently as would be clinically desirable. An
alternative to cutting core biopsy guns are fine needle aspirations (FNAs), which can be performed with
minimal intervention and allow for less invasive and/or repeated sampling from small lesions. However,
workup of FNA specimens remains challenging using conventional cytology and immunohistochemistry. To
address these barriers, Aikili Biosystems seeks to enable same-day diagnostic workup of FNA samples
using a proprietary “FAST” assay and automated image cytometer. A key component of Aikili's technology
is our proprietary cell cycling method (FAST), which builds upon and expands previous assay capabilities (4-
channel multiplexing) to over 20-40 biomarkers; it is coupled with our image cytometer, a stand-alone
diagnostic platform capable of automated cancer cell classification in <2 hours. Building upon initial
development and pre-clinical validation, in Aim 1, we will validate FAST antibody probes in >15 cancer
markers, integrate sample processing with Aikili's cytometry system and analyze associated images using the
device. In Aim 2, we will evaluate the benefit of the integrated technology for rapid, same-day analysis of
clinical samples, specifically lymphoma FNA samples (n = 40) stained with FAST-linker modified antibody
probes. Phase I will be deemed successful when Aikili's system reliably detects and classifies lymphoma
cells compared to gold standards. Successful completion of Phase I will lay the foundation for a Phase II
application for clinical testing and manufacture of cytometry systems and commercial cartridges for
multiple cancers. This platform has potential to transform cellular diagnostics and pathology workflows
through rapid, same-day analyses of minimally invasive FNAs; its robust analyses of pharmacodynamic
markers has potential to enable development of new, clinically meaningful biomarkers that can be used to
advance drug development.

## Key facts

- **NIH application ID:** 10323396
- **Project number:** 1R43CA265442-01
- **Recipient organization:** AIKILI BIOSYSTEMS INC.
- **Principal Investigator:** Laura E Kelley
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $400,000
- **Award type:** 1
- **Project period:** 2021-08-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10323396

## Citation

> US National Institutes of Health, RePORTER application 10323396, Automated molecular diagnosis on fine needle aspirates (FNA) (1R43CA265442-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10323396. Licensed CC0.

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