Preparing for a Method Verification (MV)? Every laboratory scientist knows the pressure of getting results right the first time. In this blog, we are going to take a closer look at how key elements play a critical role in building a confident verification process.
When doing MV, a laboratory needs to prove that a method is reliable before routine use. However, reliability of the method does not only depend on the analyzer and experiments alone. What often determines whether a verification runs smoothly - or requires unnecessary repeats - comes down to three key elements: samples, runs and replicates.
Together these elements form the framework of producing a reliable verification. Let’s discuss these one by one:
What are Samples?
In a laboratory, samples are the materials or substances being analyzed in a laboratory procedure. Samples can originate from a range of sources such as blood, urine, and standard samples from manufacturers. When selecting samples for MV, it is essential to choose ones that are similar in nature with the true specimen to be analyzed as real patient results will be used throughout the MV process.
The proper selection of a sample is important to ensure that results obtained represent the analyte being studied. For testing done under Clinical Chemistry, fresh human serum with detectable levels of the analyte should ideally be used. Choosing an inappropriate or biased specimen can lead to inaccurate results that compromise the reliability of the method being verified.
Aside from sample source, sample quality and proper handling should be taken into consideration. Sample should be free from contamination and interferences which could risk altering the results. The ideal sample should be stable to ensure its reliability over multiple testing.
What are Runs?
Run is the execution of an analytical method. A run involves analyzing a set of samples using the method to be verified. Think of it as a batch. A run is completed on a single day, with the same reagents, and on the same instrument. The results of a run are considered a single dataset.
During method verification, experiments are often performed multiple times—a process known as replication. Replicate results create the statistical foundation scientists need to evaluate whether a method is both consistent and precise.
What are Replicates?
Replicates refer to the repeated “run” of the same sample using the same analytical method. The goal of doing replicates is to evaluate precision and repeatability of the method being verified. When a method gives a consistent close range of results through each replicate, this suggests that the method being verified is precise and repeatable.
What is the importance of testing in replicates?
- Assess precision - replicates show the consistency of results when the same sample it tested multiple times.
- Reveals random errors → replicates detect unpredictable variations that may appear in one run but not in another. These errors may cause test results to be higher or lower than the target value.
- Support laboratory compliance → replicates meet regulatory and accreditation requirements by providing evidence of a reliable method performance.
How do these 3 work together in MV?
Samples, runs, and replicates come together to form the backbone of a reliable laboratory workflow:
- Start with the right sample – ensuring proper source, quality, and handling.
- Organize into runs – test samples in structured, systematic groups under the same conditions.
- Include replicates – repeat measurements of the same samples within runs to check consistency.
When combined, these steps allow the laboratory to identify and separate random errors from true method performance—strengthening confidence in the verification process.
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