Automated Sample Processing System for Clinical Laboratory Oversight
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Solution Overview
Problem
The traditional laboratory testing process for blood samples is slow, prone to human error, and burdened by inefficiencies, including lengthy wait times for results and manual handling that can lead to variability and inaccuracies.
Innovation Solution
A Clinical Laboratory Improvement Amendments (CLIA)-certified automated sample processing and analysis system comprising Sample Processing Units (SPUs) and a Laboratory Automation System (LAS) that automates pre-analytic sample processing, reduces human error, and enables faster generation of lab results by leveraging secure server software for oversight and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual sample processing is used, then device complexity is reduced, but productivity decreases and human error increases
Solution Approach 1:
The system is divided into distinct modular components: Sample Processing Units (SPUs) for automated pre-analytic processing, Laboratory Automation System (LAS) for centralized control, and secure server software for data management. Each module performs specific functions independently, enabling high-throughput automation while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
A secure server software acts as an intermediary between the SPUs and the LAS, facilitating automated communication and data exchange. This intermediary layer enables seamless integration and coordination between automated processing equipment and laboratory information systems, resolving the contradiction by providing structured interfaces that manage complexity.
2Productivity
If automated processing is implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The Sample Processing Units are designed to perform multiple pre-analytic functions including sample reception, processing, and preparation for analysis within a single automated platform. This multi-functionality increases processing throughput while consolidating equipment rather than requiring multiple separate devices, thereby managing overall system complexity.
Solution Approach 2:
The system incorporates secure server software that continuously monitors and communicates between SPUs and the LAS, providing real-time feedback on processing status, sample tracking, and result verification. This automated feedback mechanism enables high-throughput processing with reduced manual intervention, resolving the complexity-productivity contradiction through intelligent system coordination.
3Measurement precision
If manual handling is used, then ease of operation is maintained, but measurement precision decreases
Solution Approach 1:
The automated Sample Processing Units perform pre-analytic processing tasks autonomously without requiring manual intervention for each sample. The system self-manages sample tracking, processing protocols, and data recording, thereby eliminating human error sources while maintaining operational simplicity through centralized control interfaces and automated workflows.
Solution Approach 2:
Manual mechanical handling of samples is replaced with automated robotic and mechanical systems within the SPUs that precisely execute processing protocols. This substitution eliminates variability in manual operations, improving measurement precision while the centralized LAS provides user-friendly control, resolving the contradiction between precision and ease of operation.
4Loss of time
If traditional processing timeline is used, then adaptability to simple workflows is maintained, but loss of time increases
Solution Approach 1:
The automated Sample Processing Units perform pre-analytic processing steps in advance and in parallel for multiple samples simultaneously. Sample reception, processing, and preparation occur concurrently rather than sequentially, dramatically reducing the time to results while the modular architecture manages infrastructure complexity through standardized interfaces and protocols.
Data Source
AI summary
In one embodiment, a method is provided comprising analyte testing on one or more types of samples.


