Experiment Design

Experiment Design

Experiment Design

Experiments are separated in the Qualitative and Quantitative test experiments.

Overview

Experiments are separated in the Qualitative and Quantitative test experiments. This section covers the general principles of how to set up and use Cualia experiments including selecting experiments, acceptance criterias, and data entry.

Lab Juice

MV Experiment are performed in MVs to evaluate the performance of laboratory methods, providing empirical evidence to confirm their accuracy and reliability. These experiments identify systematic and random errors, ensuring the methods meet necessary performance standards. They also facilitate regulatory compliance, as empirical validation is required to confirm adherence to established criteria. Comparative analysis during these experiments benchmarks new methods against reference standards, ensuring their reliability and accuracy.

Controlled experiments in MV are essential for maintaining quality control by ensuring the consistency and reproducibility of results. This process is vital for preserving the integrity of laboratory testing and ensuring high-quality patient care. Thus, MV experiments are fundamental for verifying the efficacy and reliability of laboratory methods, providing confidence in their performance and suitability for clinical use.

Qualitative Experiments

Qualitative Test Experiments, including Method Comparison (MC), Precision (Prec), Limit of Detection (LoD), and Trueness experiments, are essential for confirming the validation information provided in the manufacturer insert.

These experiments verify that the manufacturer's claims about the method's performance—such as accuracy, precision, detection limits, and trueness—are accurate and applicable in the specific laboratory's environment.

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**Cualia Support Docs Definitions (Public)**

Name
Definition
Agreements

The total number of measurements between actual and reference value in agreement.

Eligible (Sample and Results)

Samples that provide the necessary information for statistical calculations to be performed. Usually this is possessing both an actual and expected result.

Label

The general identification used to identify a specific Sample.

Replicate

Multiple tests on the same sample to assess precision and repeatability, conducted within a run or across multiple runs.

Run

A sequence of measurements on a set of samples under the same conditions, performed within a defined time period.

Sample Source

The original source of the Sample such as Sample, EQA, or the name of the Manufacturer.

Sample Type

Can describe the specific Sample Type, source and/or medium that is used to collect and/or store the sample.

Sample(s)

Individual specimens collected for testing representing the source. In MV experiments with Runs, this can refer to to the number of concentration levels used.

Test Details

Information about a test relevant to the description, background and performance metrics.

Quantitative Experiments

Quantitative Test Experiments confirm the performance characteristics claimed by manufacturers by evaluating precision, accuracy, sensitivity, and linearity. These experiments ensure that the method performs reliably under specific laboratory conditions, maintaining the integrity of test results.

Linearity and Reference Interval experiments assess the method’s accuracy across various concentrations and population groups. Trueness, Carryover, and Interference experiments further validate the method’s reliability in practical clinical scenarios.

By replicating these experiments, laboratories ensure that the method performs as described in the manufacturer insert, providing consistency and reliability. This process ensures regulatory compliance and builds confidence in the method’s suitability for clinical use.

Quantitative MV experiments verify that methods yield accurate and reproducible results, enhancing the quality and effectiveness of laboratory testing. This validation is essential for maintaining high standards of diagnostic accuracy and patient care.

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**Cualia Support Docs Definitions (Public)**

Name
Definition
Precision (Prec) Experiment

An experiment that evaluates Random Error through replicate measurements across concentration levels.

Limit of Blank (LoB) Experiment

An is the highest concentration of analyte detected for a blank sample. This can be determined through the LoB MV Experiment. LoB=μ+1.645×σLoB=μ+1.645×σ μμ: Mean of the results σσ: Standar Deviation of results

Limit of Quantitation (LoQ) Experiment

An MV Experiment used to determine the lowest amount of analyte that can be reliably determined.

Method Comparison (MC) Experiment

An MV experiment used to estimate the systematic difference on the basis of the differences observed between the methods. See: QL Method ComparisonQL Method Comparison

Linearity (Lin) Experiment

Linearity is an MV experiment to establish the correlation between Reference and Actual Results

Reference Interval (RI) Experiment

An experiment used to determine the normal ranges for a test within populations measured by the laboratory

Trueness (TN) Experiment

Trueness is an MV Experiment that evaluates the performance of a test by comparing sample test results with true values. Usually an EQA.

Carryover Experiment

An MV experiment used to evaluate the effect of high concentration testing on subsequent low concentration samples.

Interference Experiment

An MV experiment used to evaluate the effect of interfering substances on sample concentration measurements.

Subscription Plans

Free Plan Each MV is limited to 3 tests and all experiments available.
Core Lab Plan Unlimited tests and experiments
Organization Plan -Coming Soon- Unlimited tests and experiments

Managing MV Tests

After starting the MV, the analyzer tests and all its information will automatically be available in the MV. To view the selected tests in the MV, navigate to the Experiment Design section of the MV and then the Quantitative or Qualitative Tests tab.

Using the Tests Selected dropdown you will be able to toggle whether the test should be included in the MV. The drag on the right side of each test allows the order of tests to be changed.

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Deciding Which Experiments Need to be Performed

Deciding which experiments must be performed begins with reviewing the manufacturer's insert which will outline the Oftentimes the manufacturer insert will specifically use the same MV terms such as “LoD.” Focus on confirming these under your lab’s conditions and

It’s also important to consider clinical importance, analytes, and regulatory requirements. For example, the Limit of Blank (LoB) Experiment may not be required for RBC tests as human levels could never reach that low. Prioritize experiments addressing potential variances in your lab, and consult guidelines from bodies like the FDA, CLSI, and EMA to ensure thorough verification.

Managing Experiments

There are 2 ways to Manage Experiments: By test or by experiment.

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When starting an MV all experiments will be selected by default.

Managing Experiments by Test

To Manage Experiments by test, navigate to the Experiment Design section of the MV and then to the Quantitative or Qualitative Tests section where the test resides.

In the test’s row, the Experiment Selection dropdown may be used to toggle whether the experiment will be included.

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Manage Experiments by Experiment

To Manage Experiments by experiment, navigate to the Experiment Design section of the MV and then to experiments.

The experiment section allows for toggling of tests for each experiment. Each test can be selected individually or toggling the experiment itself will the experiment from all tests.

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Overview the Status of Each Experiment

Getting an Overview of the Status of each experiment offers a quick glance method of seeing the whole state of the MV instead of clicking through individual files and PDFs. To access this view navigate to the Experimental Design section and then Experiments.

The toolbar above the sections allows to:

  • View all experiment with a specific experiment state
  • View all experiments by result type
  • Expand/collapse all experiment blocks
  • Search by keywords
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Experiment States

Experiment States indicate the current condition of the experiment to give clean identifiers to their status. These identifiers may also be found on individual samples with replicates and runs.

Experiment States for Experiments
Experiment States for Experiments
Experiment States for Samples with Replicates
Experiment States for Samples with Replicates

Experiment State Descriptions

Status
Description
Not Started
No measurements have been entered into the experiment.
Incomplete
Measurement has been entered, however an insufficient amount to fulfill the criterias of the experiment.
Failed
Sufficient measurements have been entered, however the results do not pass the requirements set by the acceptance criterias.
Passed
Sufficient measurements have been entered and passed the requirements set by the acceptance criterias.