Cases 1A and 2A are routinely monitored by SPC. Cases 1B and 2B originate from other uncertainties such as imperfect test method performance or poor sampling and are not readily visible by SPC. Cases 2A and 2B are obviously not desirable because the firm cannot process nor sell this product or material. Case 1B constitutes a risk primarily to patients, but also means a risk to the firm if adverse product-related reactions or over or under-dosing would actually occur. Case 2B constitutes a loss solely to the firm and should also be avoided mainly for profit reasons although other problems may also arise from this situation.

Table 1. Analytical method transfer (AMT) execution matrix

To meaningfully estimate risk to patients and the firm, we must understand our process data and integrate test measurement aspects into our risk-based validation strategies. Good risk management tools will dictate how much assay performance characteristics can deviate from ideal. This will then set limits on how much we can tolerate over time for a test method to deviate from ideal (100% accurate and precise). It should also now become apparent why it is so important to maintain our validation status with an AMM program. When this is ignored, we negatively affect all four cases. (Negative here means increased risk to patient or firm). Although undetected, negative effects will occur for the "invisible" cases 1B and 2B because measurement errors are not captured by regular SPC. This may also cause the lack of process understanding and control, and may also lead to conflicts with current regulatory expectations (process analytical technology, [PAT]) and may impact a firm's profits in the long run.⁹

Validated analytical methods can be transferred from one laboratory to another without the need for revalidation at the receiving laboratory.^8,10 A typical AMT is accomplished by testing at the sending and receiving laboratories in a round-robin format. Testing is performed on three different product lots over three days, using two operators and two instruments in each laboratory.^8,10 Reproducibility of test results, in and between laboratories, is demonstrated in Table 1 by evaluating intermediate precision (different operators, instruments, days, and product lots at each site) using an analysis of variance (ANOVA) and by comparing the differences in mean results for each lot between both sites.^8,10 For each AMT, preset acceptance criteria for intermediate precision and for the absolute differences between sites are derived and justified from the validation at the sending laboratory.⁸

The AMT reports should include descriptive statistics (means, standard deviations and coefficients of variance), comparative statistics (ANOVA p-values) for interlaboratory results, and the differences-of-mean values for both (or each) laboratories. Each report documents evidence that the transferred test method is suitable (qualified) for testing at the receiving laboratory.

For cases where the ANOVA p-value is less than 0.05, secondary acceptance criteria should be established for the comparison-of means and variability of the results to demonstrate the overall laboratory-to-laboratory reproducibility of test results. It is advisable to include a numerical fall-back limit (or percentage) because the likelihood of observing statistical differences may increase with the precision of the test method. In addition, some differences (bias) between instruments, operator performances and days are expected.⁸ We should tailor our acceptance criteria for overall (intermediate) precision and for the maximum tolerated difference between mean laboratory results (accuracy or matching) to minimize the likelihood of obtaining OOS results (2A and 2B) or 1B results.⁸ The setting and justification of all acceptance criteria must strike a balance and is a critical part of each protocol. A detailed AMT case study was presented elsewhere.⁸