Analyst errors

The robustness of an assay becomes critical when evaluating its performance in a QC environment for the release of therapeutic proteins and antibodies. Over the past 5 — 10 years of product release experience in the biotech industry, assay failure rate is in the range of 5—30% depending on the method type and system suitability criteria. The types of assay failure are mainly as follows technical error (including analyst error), equipment error, and system suitability/assay acceptance errors. A periodic review of an assay s performance in the QC labs and timely feedback to the development labs are crucial to minimize the assay failure rate. A concerted effort in working with vendor is also helpful to ensure that instruments are in good condition to minimize the assay failure rate. 

Retesting the OOS drug product is necessary in cases in which the laboratory investigation indicates that analyst error caused the initial OOS result retesting is similarly acceptable where a review of the analyst s work is inconclusive. 

Out-of-specification laboratory results have been given additional emphasis by the FDA, particularly after the Barr v. FDA court case [55]. An out-of-specification result falls into three catogories laboratory error, non-process-related or operator error, and process-related or manufacturing process error. Retesting of the same sample is appropriate when the analyst error can documented. An outlier test on some chemical assays, particularily those involving extensive sample preparation and manipulation, is justifiable but is not a routine approach to rejecting results [56]. 

Consideration must be given as to whether analyst error, equipment malfunction, inappropriate reagents, or some other detectable and assignable cause was the reason for an OOS result. 

Automatic devices perform specific operations at a given point in an analysis, frequently the measurement step."65 The main characteristics of automation are objectivity, rapidity, flexibility, and reliability of the analytical instruments. With automation, the objectivity level increases. The reproducibility of the analytical information increases because analyst errors are eliminated. 

Determinate errors can arise from uncalibrated balances, improperly calibrated volumetric flasks or pipettes, malfunctioning instrumentation, impure chemicals, incorrect analytical procedures or techniques, and analyst error. 

In a functioning laboratory, development and testing is required for trouble shooting (see Chapter 12) and introducing improved methods. Problematic processes must be examined to determine whether the problem is due to method formulation, analyst error, or sample matrix complications. The method as written may be insufficiently stable to handle the wide range of radioactive or stable impurities in the samples, and may require more detailed specifications, added steps, or replacement. 

Review of the process prompted by analyst or operator concerns should involve the analyst, the supervisor, and possibly a specialist. This review may be able to distinguish among possible causes in chemical analysis such as matrix difference, method instability, bad reagents, or analyst error. In radiation detection, source problems, detector malfunction, and data analysis must be distinguished. The discussion should focus on what the analyst or operator remembers about the measurement series in question, in contrast to records for similar analyses this should help determine when the problem was first observed and the differences in the process since then. 

Problems in purifying a sample for radionuclide measurement can be due to inappropriate procedures or analyst error. The circumstances can be categorized by frequency as follows ... 

The OOS guidance document indicates that laboratory or analyst errors should be relatively rare, and frequent occurrence can be an indication of inadequate training of analysts, poorly calibrated/maintained equipment, or careless work. It should not be assumed that the failing result is attributable to analytical error without performing and documenting an investigation. When a laboratory error is confirmed, the company must determine the source of error, take appropriate corrective actions, and prevent reoccurrence of the incident. 

Flow rate. The flow rate accuracy will be determined by the instrument used and will be documented in the supplier s operational qualification documentation. The impact of analyst error made during system setup should be validated and it would be appropriate to investigate the effect of small changes in the region of 10% of the target flow rate. The flow rate may be adjusted by as much as 50%, provided that there are no adverse effects on the chromatography (i.e., resolution, peak shape and retention time). Common causes of flow rate error will be discussed further in Chapter 10. 

Mixing errors automated mobile phase preparation. Problems encountered with an automated system can still be the result of analyst error. For example, the wrong component may have been dispensed into the HPLC solvent reservoir. Where there is an apparent issue in relation to the retention time of a compound, the mobile phase should always be checked for accuracy of preparation. Proportioning valve errors can also cause a problem with automated systems. When the valve ceases to dispense the correct amount of either solvent, the retention time of the compounds of interest will vary. 

Incorrect column choice is usually due to analyst error (see Figure 10.5). Where there are significant changes in the chromatography, the column specification should be carefully checked and the column replaced if necessary. Column information is printed on the barrel of the column. 

Acceptable levels of peak tailing should be indicated in the system suitability section of the method as peak asymmetry or tailing factor. Once the limits have been exceeded, a number of basic checks can be carried out that can assist in the diagnosis. A lot of problems of this nature are found to be due to analyst error, and the mobile phase composition and column choice should always be checked as a matter of course. 

All of the validation parameters above deal with method performance during the critical phases of validation and method review. Unfortunately, no matter how rigorous the validation protocol is for a method, validation cannot preclude or anticipate the effect of instrumentation that is not wofijing properly or analyst error. It is for this reason that an on-going method-specific test (or set of tests) is needed. This is the reasoning behind the use of system suitability parameters. 

The tape was used inconsistently and with insufficient attention to detail. This is analyst error and would be classified as random. To detect it, the analyst would be tasked with measuring the height of the same person 10... 

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