Which characteristics are typically included in a method validation?

• A. Only accuracy.
• B. Accuracy, precision, bias, linearity, range, detection limits, and ruggedness.
• C. Only linearity and range.
• D. Instrument maintenance schedule.

Answer: (D)

When validating a method, you’re defining how well the analytical procedure performs for its intended use. This means assessing key performance characteristics that describe data quality: accuracy (how close results are to the true value), precision (how reproducible results are under the same conditions), and bias (systematic error). You also look at linearity (whether the response is proportional to concentration across the range), the range over which the method is valid, and the detection and quantitation limits (how small a amount you can reliably detect or quantify). Ruggedness or robustness (how results hold up under small deliberate changes in conditions) is included to show the method remains reliable in routine work. These elements together establish that the method can produce trustworthy results.

Maintenance actions, like an instrument maintenance schedule, belong to keeping the instrument in good working order and are part of equipment qualification and ongoing reliability, not a validation property of the method itself.