Biological Sample Workflow Routing Without Real-Time Dependencies
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Solution Overview
Problem
Current automated systems for analyzing biological samples in clinical laboratories suffer from real-time dependencies among analytical devices and single-point-of-failure vulnerabilities, leading to inefficiencies and potential system failures.
Innovation Solution
A network-based analysis system with a sample workflow manager and instrument manager that dynamically manages sample routing, aliquoting, and buffering across pre-analytical, analytical, and post-analytical devices, minimizing real-time dependencies and single-point-of-failure risks through preconfigured processing routes and conditional statements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time dependencies among analytical devices are implemented for coordinated sample processing, then processing efficiency is improved, but system reliability deteriorates due to single-point-of-failure vulnerabilities
Solution Approach 1:
The system segments the centralized workflow management into distributed components: each analytical device has local intelligence to make routing decisions independently. The workflow is divided into discrete, manageable tasks that can be executed autonomously by individual devices or transporters, eliminating the single-point-of-failure vulnerability of centralized control while maintaining coordinated processing efficiency.
Solution Approach 2:
The system implements preliminary action by pre-configuring multiple alternative processing routes and buffers before processing begins. When a device fails or becomes unavailable, the system can immediately switch to a pre-planned alternative route without requiring real-time centralized coordination, thus maintaining reliability while preserving processing efficiency.
2Productivity
If centralized workflow management is used to coordinate all analytical devices, then processing routes are optimized, but device complexity increases and single-point-of-failure risks arise
Solution Approach 1:
Each analytical device and transporter is equipped with self-service capabilities including local decision-making intelligence, autonomous routing determination, and self-monitoring. Devices can independently assess their own status and make routing decisions without constant centralized intervention, reducing overall system complexity while maintaining optimized processing routes through distributed intelligence.
3Productivity
If real-time management control is implemented across all devices, then processing coordination is improved, but adaptability to device failures deteriorates
Solution Approach 1:
The system implements dynamic adaptability through distributed decision-making where each device can independently adjust its behavior based on real-time conditions. When failures occur, the system dynamically reconfigures processing routes at the local level without requiring centralized reconfiguration, maintaining both coordination and adaptability simultaneously.
Solution Approach 2:
The system uses distributed feedback mechanisms where each device monitors its own status and communicates with neighboring devices rather than a central controller. This localized feedback enables rapid adaptation to failures while maintaining processing coordination through peer-to-peer communication, reducing the complexity and vulnerability of centralized control.
Data Source
AI summary
An analysis system for analyzing biological samples is disclosed, and which may comprise two or more analysis system components for performing an analysis. A sample workflow manager and an instrument manager coupled to the sample workflow manager may be coupled to the system components for receiving a process status from the system components, wherein the sample workflow manager provides at least one preconfigured processing route to the instrument manager in accordance with the process status. The instrument manager may comprise a memory for storing the preconfigured processing route, wherein the instrument manager is adapted for receiving a test order for analyzing the biological sample using the system components, and wherein the instrument manager is adapted for generating commands for controlling a transport device for transporting the biological sample in accordance with the test order and the at least one preconfigured processing route.