AMV Acceptance Criteria
In-process and product specifications should be based on analytical capability.8 The mirror image must also be considered—AMV acceptance criteria must be related to specifications—because the observed
process variability is the sum of actual process variability, test method variability, and sampling variability as illustrated
in Equation 1 below.
[observed process variability]
[actual process variability]
[test method variability]
Known values for the observed (measured) process variability, the test method variability (intermediate precision), and sampling
(batch uniformity as measured) variability can be used to estimate actual process variability and vice versa. For example,
when the observed process variability is 10%, the method intermediate precision is 8%, and the sampling variability is 0%
or negligible, the actual process variability is approximately 6%.
Solved: X = 0.06
Figure 1 illustrates which data sources should be evaluated for a new method and new drug product with an understanding that
sometimes only reliable estimates for process variability and method variability may exist at the time of AMV studies. Naturally,
the (target) specifications are pushing the acceptance criteria towards less risk (narrow limits) for the patient, while actual
process, sampling and method performance imperfections push from the opposite side towards wider limits. Once we have estimates
for each source of variation we can then set balanced expectations that can protect the patient (and firm). Simply put, the
less data sources are available or evaluated, the more "gambling" will occur, because of the existing uncertainty, when setting
AMV protocol acceptance criteria. The less method performance requirements are understood, the less predictable will be the
understanding of the potential impact thus leading to greater risks to patients and the firm.6 When deriving acceptance criteria, balanced limits for the AMV protocol for accuracy, precision, and other assay characteristics
can be derived from the specifications (or target specifications) and historical data sources. Clearly, if the specifications
are not established, the method cannot be fully validated. Ultimately, we need balanced criteria that challenge the new method's
ability to assure product quality with the need to formally validate the new method.6
1. International Conference on Harmonization. Q2(R1), Validation of analytical procedures. Current Step 4 Version. Geneva,
2. Eurachem Guide. Fitness for Purpose of Analytical Methods. Teddington, UK; 1998.
3. Center for Drug Evaluation and Research. Guidance for Industry. Bioanalytical method validation. Bethesda, MD; 2001.
4. Center for Biologics Evaluation and Research. Draft Guidance for Industry. Analytical procedures and methods validation.
Bethesda, MD; 2000.
5. Krause SO. Development and validation of analytical methods for biopharma-ceuticals, part I: development and optimization.
BioPharm Intl. 2004; 16(10):52–61.
6. Krause SO. Validation of analytical methods for biopharmaceuticals–a guide to risk based validation and implementation
strategies. PDA/DHI Publishing. Bethesda, MD. 2007.
7. EURACHEM/CITAC Guide CG4, Tracebility in Chemical Measurements; 2003.