Automated Digital Pathology Device for High-Throughput Demand

Description:

Abstract:

Computer and imaging technologies led to the development of digital pathology and the capture and storage of pathological specimens as digitally formatted images. The use of artificial intelligence (AI) in digital pathology, such as in three-dimensional (3D) reconstruction, requires analyses of high volumes of data. This resulted in increased demands for processing and acquisition of digital images of pathology samples. Increased usage cannot be met by the time-consuming, manual, and laborious methods currently used. Therefore, there is a need for automation of the techniques used in processing of pathology samples and acquisition of digital images to make them amenable with high-throughput approaches like AI analysis.

National Cancer Institute inventors are developing an automated device with integrated tissue sectioning, staining, scanning, and high-throughput capability. This device integrates pathology sample processing (e.g., sectioning, fixing, and staining) with optical scanning and digital image acquisition. This streamlines the entire process enabling high-throughput preparation of large volumes of samples and data for subsequent AI analysis. As a result of automation, the device saves time, minimizes errors, and reduces wasting reagents and supplies.

The NCI is seeking licensees to develop an automated digital pathology device compatible with high-throughput data analysis.

Competitive Advantages:

Facilitates processing and imaging of large volumes of pathology samples
Automation saves time, increases reproducibility, and minimizes errors
Compatible with high-throughput processes, e.g., AI analysis of digital pathology images and 3D reconstruction

Commercial Applications:

Biopsy sample processing in pathology labs, hospitals, research labs
Applicable to diagnoses of various disease indications, including cancer and infectious diseases

Patent Information:
For Information, Contact:
Michael Pollack
Supervisory Technology Transfer Manager
NIH Technology Transfer
240-276-5519
michael.pollack@nih.gov
Inventors:
Zhengping (Ping) Zhuang
Young-Wan Moon
Anthony Cappadona
Keywords:
AI
Artificial Intelligence
AUTOMATION
Digital Pathology
High-throughput
Histology
IMAGING
Zhuang
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