Quality Assurance of lung cancer diagnostic test
Led and managed all Design Control elements of the serum test for advanced non-small cell lung cancer patients quality assurance process
Software Verification and Validation of diagnostic test
Led and managed all Design Control elements of the serum test for advanced non-small cell lung cancer patients quality assurance process by focusing on precision, accuracy, reportable range, reference range, analytic sensitivity, analytic specificity, specimen stability, linearity, and carryover metrics.
Patients need tests to guide treatment decisions
- Managed all QA/RA required for the test deliverables, as well as, supported the remainder of the team in developing a quality product that meets FDA and CLIA regulatory requirements
- Ensured test development activities related to verification and validation to be fully compliant to the quality system procedures
- Facilitated and completed root cause analysis investigations when design challenges were encountered
- Worked with the project leader, systems engineers, and design engineers to plan and hold robust design reviews
- Assisted teams with developing the Risk Management File, including Risk Assessments, SFMEA, DFMEA/PFMEA, FTA
- Participated on various continuous improvement/process improvement initiatives with focus on improving Laboratory Information Management System workflows
- Designed and executed protocols for evaluation of test, and
verification / validation manual test cases
- Developed requirements traceability process SOP and produced the matrix for the project
Diagnostic Test Verification and Validation Process
Considerations when determining the utility of tests should be placed on Protocols for Evaluation of Tests, Reference Tests, Resolution of Discordant Results, and Metrics / Indicators of diagnostic test performance.
Designing Protocols for Evaluation of Tests
When designing protocols for evaluation of diagnostic tests, the following needs to be included:
- Set guidelines
- Follow exactly
- Outline all characteristics of samples and procedures
- Describe detailed algorithm to follow for discordant results
- Include QA/QC section
Reference tests should characterize samples, must be careful about “pre-selected samples” to evaluate false positives, and should be tests that are recognized by the scientific community.
Resolution of Discordant Results
If discordant results from diagnostic test received, do the following:
- Check sample integrity, labeling, paperwork, and procedures
- Repeat by same laboratory technician
- Repeat blindly by another laboratory technician
- Repeat reference test blindly
- Repeat at different laboratory
Metrics / Indicators of Diagnostic Test Performance
Metrics we used were: Sensitivity, Specificity, Test efficiency, Delta values, and Predictive values.
In order to ensure quality test results we followed the following practices:
Maintained accurate Record Keeping, including kit lot numbers (expiration and open dates), clearly labeling reagents with date opened or prepared (include open and expiration date) on each label, daily temperature monitoring and recording, performance of controls and action taken when out-of-range, photograph or clear photocopies, Ratios of in-house controls to cut-off values.
Followed Quality Controls, including kit controls (use as directed by the manufacturer), three levels to monitor variability (low, high, negative), storage of in-house control sera.
Adopted Quality Assurance best practices, by designing SOP with total compliance, supervising review of all paperwork, developing checklists for monitoring all activities, complete documentation of all results, and no deviation from procedures.