Validation and verification are foundational processes in clinical laboratories to ensure the accuracy, reliability, and compliance of diagnostic methods. Understanding the distinctions and applications of these processes is essential for laboratory professionals. This short guide provides a detailed, technical, and scientific framework for implementing validation and verification based on the Clinical and Laboratory Standards Institute (CLSI) guidelines.

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1. Introduction to Validation and Verification

Validation and verification serve distinct purposes in laboratory diagnostics:

• Validation: A comprehensive evaluation of a method to establish its performance characteristics in a specific laboratory setting. It is required for laboratory-developed tests (LDTs), modified methods, and methods used in new contexts.
• Verification: A streamlined assessment to confirm that a method performs as expected under the laboratory’s operating conditions, typically for FDA-approved or manufacturer-developed methods.

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Important Distinctions

Aspect	Validation	Verification
When Required	New methods, significant modifications, or LDTs.	Standard methods approved by manufacturers.
Focus	Establishing performance characteristics.	Confirming performance matches predefined claims.
Scope	Comprehensive evaluation of precision, accuracy, sensitivity, specificity, etc.	Limited to verifying claims like precision and accuracy.
Examples	Developing a new immunoassay or modifying an existing one.	Verifying a commercially available cholesterol assay.

2. Validation: Definition and Application

Validation is necessary when introducing new diagnostic methods or significantly modifying existing ones. It aims to define performance characteristics, such as precision, accuracy, sensitivity, and specificity, under laboratory-specific conditions.

2.1 Key Performance Characteristics for Validation

1. Accuracy (Systematic Error):
   • Assesses the closeness of measured values to true values.
   • Methods: Perform method comparison studies using patient samples or control materials.
     • Test at least 40 patient samples across the reportable range.
     • Evaluate systematic errors using regression analysis and calculate bias.
2. Precision (Random Error):
   • Evaluates consistency of results under repeated testing.
   • Methods:
     • Conduct replication studies using at least 20 replicates of control materials.
     • Assess within-run, between-run, and between-day variability.
     • Calculate standard deviation (SD) and coefficient of variation (CV).
3. Linearity (Reportable Range):
   • Ensures that results are proportional to analyte concentrations across the range.
   • Methods:
     • Test at least five concentration levels spanning the entire reportable range.
     • Plot measured vs. assigned values and verify linear regression.
     • Check that total error (systematic + random) does not exceed allowable total error (TEa).
4. Analytical Sensitivity (LoB, LoD, LoQ):
   • Limit of Blank (LoB): Highest value likely observed in blank samples.
   • Limit of Detection (LoD): Lowest analyte concentration reliably detected.
   • Limit of Quantification (LoQ): Lowest analyte concentration measured with acceptable precision.
   • Methods:
     • For LoB: Test 20 blank replicates; calculate mean + 1.65SD.
     • For LoD: Test 20 low-level replicates; LoD = LoB + 1.65SD.
     • For LoQ: Test 30 replicates at a low concentration; ensure acceptable bias and precision.
5. Interference Testing:
   • Evaluates robustness by introducing interferents (e.g., hemolysis, lipemia, icterus).
   • Methods:
     • Spike patient samples with interferents at clinically significant concentrations.
     • Assess bias introduced by each interferent.
6. Reference Range Establishment:
   • Defines normal values for the target population.
   • Methods:
     • Collect data from at least 120 healthy individuals.
     • Statistically analyze results to establish the reference interval.

2.2 Validation Process Workflow

1. Define analytical goals (e.g., allowable total error, medical decision levels).
2. Plan validation experiments based on method type and clinical application.
3. Conduct experiments and collect data.
4. Analyze results and compare against predefined acceptance criteria.
5. Document findings and implement validated methods.

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3. Verification: Definition and Application

Verification confirms that a manufacturer-approved method performs according to predefined specifications in a specific laboratory setting.

3.1 Key Steps in Verification

1. Accuracy Check:
   • Test at least 20 patient samples and compare results to reference methods.
   • Use regression analysis to calculate bias and ensure it meets allowable limits.
2. Precision Evaluation:
   • Conduct replication studies with control materials.
   • Verify that CV% aligns with manufacturer claims.
3. Reportable Range Verification:
   • Confirm that the method provides accurate results across the manufacturer’s specified range.
   • Test samples at low, mid, and high levels.
4. Reference Range Verification:
   • Collect 20 samples from healthy individuals.
   • Verify that no more than two samples fall outside the manufacturer’s reference range.
5. Analytical Sensitivity Check:
   • For critical tests (e.g., PSA, hsTnT), verify LoD and LoQ claims using 20 replicates.

3.2 Verification Process Workflow

1. Review manufacturer’s specifications and claims.
2. Conduct verification studies tailored to laboratory needs.
3. Analyze results and compare with specifications.
4. Document verification outcomes and approve the method for clinical use.

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4. Practical Scenarios and Applications

1. Scenario 1: Validating a New Immunoassay
   • Steps:
     • Conduct replication, method comparison, linearity, and interference studies.
     • Establish LoD, LoQ, and reference ranges.
   • Outcome: Comprehensive dataset proving the assay’s reliability for patient testing.
2. Scenario 2: Verifying a Commercially Approved Assay
   • Steps:
     • Confirm accuracy, precision, and reportable range using patient samples.
   • Outcome: Assurance that the method meets manufacturer’s claims under local conditions.

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5. Documentation and Reporting

Accurate documentation is critical for compliance and audit readiness. The following should be included:

• Detailed protocol for validation/verification studies.
• Raw data from experiments.
• Statistical analyses and acceptance criteria.
• Summary of findings and conclusions.
• Sign-off by responsible personnel.

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6. Conclusion

Validation and verification are distinct yet complementary processes that ensure the reliability and accuracy of diagnostic methods in clinical laboratories. By following CLSI guidelines, laboratory professionals can maintain high standards of quality and patient safety. Whether introducing new methods or verifying existing ones, adherence to these practices is essential for operational excellence and regulatory compliance.

7. References

list of essential CLSI guidelines for validation and verification:

CLSI EP5-A3: Evaluation of Precision of Quantitative Measurement Procedures.
CLSI EP6-A: Evaluation of the Linearity of Quantitative Measurement Procedures.
CLSI EP9-A3: Method Comparison and Bias Estimation Using Patient Samples.
CLSI EP17-A2: Protocols for Determination of Limits of Detection and Limits of Quantitation.
CLSI C28-A3: Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory.