Assay validation

6.0

Why validate

Validation is a crucial process because it ensures data reliability, complies with regulatory authorities (such as the ICH), guarantees patient safety, and reduces costly errors. There are four key validation parameters (Pharmaffiliates, 2026):

1. 01Linearity. The ability to get test results that are directly proportional to the concentration of the sample in a particular range.
2. 02Accuracy. How close the test result is to the true reference value set out.
3. 03Precision. How close the measurements and results are to each other when performed under the exact same conditions.
4. 04Specificity. The ability of a particular assay to measure only the substance intended for analysis, without any interference.

6.1

Linearity

This parameter is evaluated by plotting the detector signals as a function of analyte concentration. To assess linearity, a minimum of five concentrations distributed across a specified range is required. For the procedure to be reliable, the obtained analyte signals must be directly proportional to the true sample concentrations.

Test results should be evaluated using appropriate statistical methods, such as calculating the linear regression line, to provide mathematical estimates of linearity. Additional reporting requirements include:

• —A plot of the data
• —The correlation coefficient
• —The y-intercept
• —The slope of the regression line

Lastly, analysing the deviation of actual data points from the regression line is useful, as all points impact the overall linearity.

6.2

Accuracy

Accuracy is shown by comparing results obtained from the procedure with expected values. It is important that accuracy is demonstrated with test conditions that remain consistent within the procedure. In this case, the concentration of acetylcysteine obtained from the HPLC can be compared to a reference material — such as the concentration of the standard — and the measured versus theoretically expected results evaluated.

As per the British Pharmacopoeia for Acetylcysteine Injection, the percentage stated is required to be 95.0 to 105.0 %.

6.3

Precision

Validation tests for assays usually include an evaluation of precision. One of the ways in which precision can be evaluated is through repeatability. According to the ICH Q2 (R2) Guideline, there are two ways repeatability can be assessed:

• —Obtaining a minimum of 9 determinations along the desired range — such as 3 concentrations with 3 replicates each.
• —Having a minimum of 6 determinations at 100 % of the test concentration.

Following this, using the results obtained from the analytical procedure, a percentage relative standard deviation (%RSD) can be calculated:

For the results to be considered precise, the %RSD has to fall within the BP range, which is ≤ 2 %.

6.4

Specificity

In this particular procedure, using HPLC means having an inherently selective method with respect to interference from impurities. By looking at the chromatogram obtained at the end of the procedure and comparing it to reference material, it can be determined that there is no presence of impurities and no impact of them on the identification or quantification of the analyte. This is done by comparing the relative peaks of the chromatograms, as well as determining whether any additional peaks are present.

6.5

Cross-validation

Finally, a cross-validation comparison can be made using iodometric titration. Due to iodine's ability to bind to the thiol group in acetylcysteine, quantification of acetylcysteine can be made via this titration and compared to the results obtained from HPLC.

It is important to note that iodometric titration is used to validate the results from HPLC — it is a precautionary measure. However, it is non-selective, as discussed under Section 5.11, and therefore does not exclude any potential impurities that could be present, which can skew the results obtained. The iodometric titration is therefore used purely as a precaution for cross-validation.