Analytical Techniques & Instrumentation - Lecture 2

Analytical Techniques and Instrumentation - Lecture 2

• Learning Goals: Students should be able to list, define, and distinguish among performance standards; explain the importance of method evaluation; make inferences about method acceptability based on evaluation; and formulate or judge the soundness of a method evaluation plan.

What is Method Evaluation?

• Method evaluation (or method validation) is a procedure for conducting assessments to ensure an analytical test system is suitable for its intended use and produces reliable analytical data.

Why Evaluate Methods?

• Ethical Considerations: Good science/good medicine, illness or health/life or death, establish fitness-for-purpose.
• Commercial Considerations: Product liability, laboratory reputation.
• Regulatory/QA Requirements: Legal requirements, consistent application of method, comparability between analysts/labs.

When to Validate/Verify?

• After periods of non-use.
• Periodically as per Quality Management System.
• New methods.
• Methods developed in-house.
• Amended standard/commercial methods.
• If there are changes to: application (use), working environment, or analyst.

Selecting an Analytical Method

• Considerations: Sample matrix, analyte concentration, accuracy needed, number of samples to be analyzed (turnaround time), cost, time and available equipment/expertise.

Evaluation of Methods: How to Evaluate?

• Define the analytical requirement.
• Develop/Identify a candidate method.
  • If the analytical requirement isn't met go to the next step.
  • If the analytical requirement is met, determine acceptability.
• Plan evaluation experiments.
• Carry out experiments.
• Use data to assess acceptability.
• Statement of acceptability.

Performance Standards/Characteristics

• Method evaluation (or method validation) is a process involving numerous assessments.
• Performance standards/characteristics involve tests or assessments used to evaluate an analytical method.

A Validation Puzzle

• Limit of detection
• Precision
• Working range
• Selectivity
• Uncertainty
• Linearity
• Limit of quantitation
• Bias/Trueness
• Ruggedness

Precision

• Precision expresses the closeness of agreement (degree of scatter) among measurements obtained from multiple samplings of the same homogeneous sample under specified conditions.
• Precision can be considered at two levels: repeatability and reproducibility.

Repeatability

• Expresses precision under the same operating conditions over a short time interval (e.g., same analyst, same instrument, same day).

Reproducibility

• Refers to the degree of agreement between results from experiments conducted by different individuals, at different locations, with different instruments.

Accuracy

• Accuracy expresses the closeness of agreement between a measured value and a known or accepted reference value (often referred to as trueness).

Precision vs. Accuracy

• High accuracy/high precision
• Low accuracy/high precision
• High accuracy/low precision
• Low accuracy/low precision

Specificity

• Specificity refers to the ability to unequivocally assess the analyte of interest in the presence of other components like impurities, degradation products, and matrix components.
• Concerns the extent to which other substances interfere with the analyte's identification.

Limit of Detection (LOD) and Limit of Quantitation (LOQ)

• LOD: The lowest analyte amount detectable in a sample, but not necessarily quantifiable under specified conditions.
• LOQ: The lowest analyte amount quantifiable in a sample with acceptable precision and accuracy under specified conditions.

Linearity and Range

• Linearity: Ability of test results to be directly proportional (or have a defined mathematical transformation) to analyte concentration over a given range.
• Range: The interval between the upper and lower levels demonstrated to have suitable precision, accuracy and linearity with the method.

Ruggedness

• Ruggedness measures reproducibility of test results under various conditions (different labs, analysts, instruments, reagents, temperatures, time intervals)
• Normally expressed by the lack of influence of inherent variables on test results.

Robustness

• Method robustness describes the method's ability to remain unaffected by small deliberate changes in method parameters (e.g., pH, temperature, reagents, brands).