Prestudy validation

Validation of bioanalytical assays in general and LBAs in particular has been the subject of intensive debate for the past 18 years or more. Chapter 4 focuses on the key agreements on a phased approach to the validation of LB As, including evaluation of all critical validation parameters prior to implementation of the method to the analysis of any study samples (prestudy validation) as well as in-study validation to assure high performance of the assay during analysis of actual study samples. Also covered in this chapter are the topics of when and how to conduct full validations, partial validations, and cross-validation. 

Chapter 5 discusses in depth the statistical considerations related to LB A development and validation. In addition to the most appropriate algorithms for describing the nonlinear calibration curves typically found in LBAs, the authors also provide further insight into the performance characteristics to be evaluated during assay validation, including the concepts of total error in prestudy validation and the use of the 4-6-X rule. The decision rules at the prestudy validation and routine assay implementation stages are also discussed in some detail in Chapter 5. 

FIGURE 3.3 Steps in method development. A systematic approach for defining and devel oping a method is shown from the initial steps of determining the method scope to evaluation of reagents, method development, and optimization, and finally, transfer to prestudy validation. 

Table 4.4 lists the analytical performance characteristics that need to be confirmed during the prestudy validation phase [4 5,9]. In addition, this table highlights the activities that are needed to progress from method development to help ensure the method will meet the prestudy a priori criteria for method acceptance and for successful acceptance of batch runs (in-study validation). 

Performance Characteristic Method Development Prestudy Validation (Validation Phase) In-Study Validation (Implementation Phase, Sample Analysis Phase)... 

Dilutional linearity Evaluate Establish Monitor and establish dilutions not covered in prestudy validation... 

FIGURE 4.2 Graphical representation of a standard curve performance after a change in reference material. Standard A (open circles) was used during prestudy validation, while Standard B (open squares) was the reference material used during the clinical study. 

Selectivity, a concept related to specificity, is a measure of the extent to which the method can determine the analyte of interest in a biological matrix without interference from other constituents in the test sample (i.e., matrix components). Again, because LBAs determine analytes in the biological matrix without sample pretreatment, this methodology is prone to interference from components present in the sample matrix. Specificity and selectivity evaluations are conducted in prevalidation and confirmed early in prestudy validation. 

During prestudy validation, the performance of the assay with respect to specificity and selectivity is confirmed with the most relevant compounds and matrices. Selectivity is expressed as acceptable recovery, using the same criteria that are applied during the assessment of accuracy. The recommended target acceptance criterion for selectivity is that acceptable recovery (e.g., 80 120% relative to buffer control) is obtained in at least 80% of the matrices evaluated. 

In some instances, these recommended a priori acceptance criteria for model acceptance may be too restrictive and more lenient criteria may be appropriate with suitable justification and documentation. Model confirmation should precede the reporting of analytical results for validation samples. The standard curve for each in-study run (study sample analysis) should be monitored using the same criteria used during prestudy validation. 

During the prestudy validation phase, samples should be spiked at the anticipated LLOQ and the ULOQ of the assay. These validation samples should be assayed as part... 

Assessment Topic Method Development Prestudy Validation In-Study Validation... 

The conference report from the Crystal City III Workshop outlines the documentation requirements in detail [10]. The degree of documentation should be sufficient to recreate the validation. Prior to initiating a prestudy validation, an appropriate standard operating procedure or a detailed validation plan should be written. This plan can be a stand-alone document or can be contained in a laboratory notebook or some comparable format. The documentation should clearly state the intended use of the method and a summary of the performance parameters to be validated. The plan should include a summary of the proposed experiments and the target acceptance criteria for each performance parameter evaluated. 

Performance characteristics of ligand-binding assays are estimated using calculated concentrations from the spiked validation samples during prestudy validation and/or from the quality control samples during in-study validation. 

DECISION RULES AND RISK ASSESSMENT IN PRESTUDY VALIDATION... 

The measurement error profile is within the acceptance limits across the entire concentration range tested during prestudy validation. In other words, the tolerance intervals calculated at different concentration levels are all within the acceptance limits. In such a case, the method is declared valid across the entire range. The lower and upper limits of quantification are defined, respectively, by the lowest and highest concentrations of this tested range (see Fig. 5.1). 

Unlike the prestudy validation phase, where the experiments are relatively time consuming and need to be rigorous, validation rules during the in-study phase should be simple and inexpensive. An in-study rule that is largely accepted in the bioanalytical community is the 4 6 15 rule and is defined in the FDA guidance [3] as ... Atleast four of every six QC samples should be within 15% of their respective nominal values. .. to accept a run. This mle provides a simple and practical guide for routine follow-up. 

The basic aim when applying prestudy and in-study validation procedures to a measurement method is to reconcile the objectives of the two validation phases. When the tolerance interval approach is used for prestudy validation and the 4 6 2 rule is used during in-study validation, the common objective is to control the proportion n of measurement results (X — jiy) that fall within the acceptance limits [—2,+ 2]. 

The alignment of risk between the prestudy and in-study validation phases can be envisaged in two ways, as shown by Boulanger et al. [29]. On the one hand, if the number of QC samples, n, to be used and the minimum, 5, of QC samples within the acceptance limits in the s n X rule are fixed (e.g., 4 6 15), the value of 7imin should be chosen so as to ensure that if the method remains valid, the s n X rule is accepted in most cases (e.g., with a minimum probability ymin). On the other hand, for a given prestudy validation scheme and X fixed), the value of 5 QC samples within the acceptance limits (for a given n) should guarantee that most of the runs will be accepted if the method remains valid. 

Let us now consider the particular case of the 4 6 X rule. As stated above, a good prestudy validation rule should be based on a value of 7rmin that ensures acceptance of a routine test in most cases (say y = 90%) if the method is valid, that is,... 

FIGURE 5.3 Reconciling prestudy validation value of 7tlnil, with the 4 6 2 rule. 

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