Biomarkers for medical devices are subjected to complex verification and validation studies. Inconsistence within the data as well as subjective evaluations of the data can result in data analyses that are inconclusive or non-reproducible, which in turn result in rework and waste.
In this project we have implemented standard work for data evaluation and analysis through the use of “best practices” and JMP scripts for all major verification and validation studies. The developed JMP scripts include:
- Logging of input parameters
- Built-in an IQ-OQ function to ensure that only validated scripts are employed
- Consistency check of the data
- Data analysis
- Reporting
The JMP scripts can be controlled centrally enabling version control. The user interface is simple and allows for a large user group.
The implementation of standard work has had a remarkable effect on the quality of the results produced. The data quality has improved, and the need for repeating the studies as a result of errors decreased. The need for cleaning up of the data is dramatically decreased. The data analyses are fast and reproducible using advanced SAS JMP scripts saving time.
The results are:
Change of practice in data collection and analysis
Implementation of standard work for data management and analysis
Result of 40% reduction in hours spent
