Analytical Instrument Switching Between Sample Testing and Software Validation
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Solution Overview
Problem
Diagnostic laboratories face high costs and time-consuming procedures when validating new analytical systems or software, often requiring additional instruments or shutting down operations, due to the need for separate validation processes that are not efficiently integrated with sample testing.
Innovation Solution
An analysis system that allows switching between sample testing and software validation on the same hardware, enabling simultaneous use of existing instruments for both processes, reducing the need for additional equipment and idle time, by using a system with multiple operating environments and automated validation protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If additional instruments are purchased for validation, then validation capability is improved, but device complexity and cost increase
Solution Approach 1:
The analytical instrument is designed to perform both sample testing and software validation using the same hardware platform. The system includes a validation controller that can switch between different operating environments (validated and unvalidated) on the same instrument, eliminating the need for separate validation instruments and reducing overall device complexity.
Solution Approach 2:
The patent merges the validation function with the sample testing function on a single instrument. The validation controller integrates both validation protocols and sample analysis capabilities, combining what were traditionally separate processes into one unified system that reduces cost and complexity.
2Speed
If validation is performed during operational hours, then validation speed is improved, but loss of time for sample testing increases
Solution Approach 1:
The system dynamically switches between different operating environments based on operational needs. The validation controller can transition between validated and unvalidated environments, allowing the instrument to adapt its function in real-time. This enables validation to be performed during non-operational hours while maintaining sample testing capability during operational hours.
Solution Approach 2:
The validation process is scheduled during non-operational hours (periodic action) while sample testing continues during operational hours. The system alternates between validation mode and testing mode in a periodic fashion, ensuring that validation is completed without interrupting regular sample processing operations.
3Measurement precision
If validation protocols are performed manually, then measurement precision is maintained, but loss of time increases
Solution Approach 1:
The validation controller automatically executes validation protocols without requiring manual intervention. The system self-manages the validation process by automatically switching between operating environments, executing validation sequences, and managing data collection, thereby reducing validation time while maintaining precision through automated control.
Solution Approach 2:
The validation controller incorporates feedback mechanisms to automatically monitor and verify validation results. The system receives feedback from validation measurements and automatically determines when validation is complete or fails, eliminating manual review time while ensuring measurement precision through automated verification loops.
Data Source
AI summary
An analysis system for biological samples is disclosed that includes at least one analyzer with an analytical unit for analyzing the biological samples and an analyzer controller. The analysis system further includes an analyzer data management system (ADMS) operable for receiving a selection of an operating environment chosen from multiple operating environments. In some embodiments, an analytical system is provided which offers a switch between sample testing and software validation on the same hardware, thereby offering efficiency and flexibility. For example, if sample testing is typically restricted to a particular time of the day (e.g., blood banks often get their samples in the evening and conduct the sample testing at night), the daytime hours can be used to validate new software. In such a case, additional instruments for software validation are not required and expensive idle times of analytical systems are reduced.