In-Study Validation Phase

However, in situations where more stringent criteria are needed to support a clinical (e.g., bioequivalence study, or pivotal preclinical study), additional efforts may be warranted to develop and validate a LBA that exhibits more stringent performance criteria. Conversely, more lenient criteria may be proposed if a sound scientific rationale is provided. 

5 IN-STUDY VALIDATION PHASE 4.5.1 Batch/Run Acceptance Criteria 

The acceptability of in-study batches/runs is based on the performance of standard calibrators and quality control samples run in an assay. As mentioned previously, it is desirable to have prestudy method acceptance criteria consistent with the in-study batch acceptance criteria. If not, a higher percentage of assay failures can be expected. This rationale was the genesis for the 4-6-30 rule as recommended by DeSilva et al. [3 5]. The standard curve acceptance criteria for macromolecule LB As are that at least 75% of the standard points should be within 20% of the nominal concentration (%RE of the back-calculated values), except at the LLOQ and ULOQ where the value should be within 25%. This requirement does not apply to anchor concentrations, which are typically outside the validation range of the assay and are used to facilitate and improve the nonlinear curve fitting. 

Run acceptance criteria that have been embraced for both chromatographic and LBAs require at least two-thirds of all QC results for a run to be within a specific percentage (e.g., 15%, 20%, 25%, or 30%) of the corresponding nominal reference values, with at least 50% of the results within the specified limit for each QC concentration. Assays of conventional small-molecule drugs have adopted a 4-6-15 rule [7,10,18]. In contrast, a 4-6-30 rule was proposed for LBAs of 

The topic of incurred sample reanalysis (ISR) was introduced at the Crystal City III Conference in May 2006 to help understand the poor reproducibility of results found by FDA in some cases when samples from studies were reanalyzed. The recommendation from the workshop report [10] on this topic is that an adequate evaluation of incurred sample reproducibility should be conducted for each species used for GLP toxicology experiments and in selected clinical studies. It is also recognized that the degree of reproducibility could be different in human samples in comparison to the animal samples. Selection of the studies to be evaluated for ISR was left up to the sponsor. 

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Dewe, W., Govaerts, B., Boulanger, B., Rozet, E., Chiap, P., Hubert, P. Risk management for analytical methods Conciliating the objectives of the pre-study and in-study validation phases. Chemometr. Intell. Lab. System, 85, 2007, 262-268. 

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. 

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. 

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)... 

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 acceptance criteria used during prestudy validation and in-study validation should be consistent with each other. Lack of consistency can result in a validated method failing more often than expected during the in-study phase or vice versa. To ensure this consistency, either the commonly used in-study acceptance criteria such as the 4 6 15 rule can be modified by increasing the number of QC samples (e.g., 8 12 15 rule) or the prestudy validation criteria based on tolerance intervals can be altered to ensure that a higher proportion of the measured results fall within the acceptance limits. 

The stages of validation of biomarker assays include establishment of the biomarker (development), so-called prevalidation, prestudy validation, and in-study validation [13-15]. The following short discussion will focus on the GLP-like definitive and relative quantitative assays. As the development and validation of an assay for novel biomarkers is quite diverse, the application of strict validation procedures appears problematic. Therefore, upon establishment of the prototype assay in the development phase, a formalized validation plan should be developed that... 

Use of Vendors. During the validation phase of the study, vendors can be effectively employed. Often, vendors w ill provide quite detailed studies free of charge for goodwill or in hopes of a later sale. Contractors use vendor help routinely for process designs or studies. Credit is usually given in the contractor s presentation of results for any vendor participation. 

Also, electronic SOPs and protocols must be available to staff at all test sites for multisite studies. If the electronic documents are to be available at several sites, the validation phase of the system must include functionality testing at each site. Documentation of system validation needs to be available at each test site as well. Electronic SOPs must have a limited life span when printed to avoid the use of an outdated document. This may be achieved by stamping each SOP hard copy Printout not valid after date xx/xx/xx . This practice helps to ensure that system users will not retain printed SOPs long after the electronic SOP is revised. For company SOPs that are to be followed by an outside contractor who has no access to the electronic system, an alternative stamp may be used on the hard-copy SOPs that will be provided to the contractor that defines the date printed or indicates that the SOP is valid for use in a particular study. Whatever procedure is used, it must be clearly documented in an SOP. 

Development and validation of PD assays to confirm drug effect on molecular target in pre-clinical studies and clinical trials conducted under an exploratory INDA, or in a traditional Phase I/II setting... 

In general, liquid-phase reactions (Sc > 1) and fast chemistry are beyond the range of DNS. The treatment of inhomogeneous flows (e.g., a chemical reactor) adds further restrictions. Thus, although DNS is a valuable tool for studying fundamentals,4 it is not a useful tool for chemical-reactor modeling. Nonetheless, much can be learned about scalar transport in turbulent flows from DNS. For example, valuable information about the effect of molecular diffusion on the joint scalar PDF can be easily extracted from a DNS simulation and used to validate the micromixing closures needed in other scalar transport models. 

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