Validation samples , biomarker assays

As for immunoassays for pharmaceutical proteins, in-study validation of biomarker assays should include one set of calibrators to monitor the standard curve as well as a set of QC samples at three concentrations analyzed in duplicate for the decision to accept or reject a specific run. Recommended acceptance criterion is the 6-4-30 rule, but even more lenient acceptance criteria may be justified based on statistical rationale developed from experimental data [14]. 

A variety of biomarkers have been shown to be valuable individually for one or several toxicant or disease situations. Few of these biomarkers have been systematically evaluated for the plethora of situations that might provoke false positive responses. Acceleration of the current pace of biomarker evaluation and qualification demands (a) the availability of panels of biomarker-assays that can be comparatively evaluated on well-defined common sample sets, (b) fit-for-purpose performance evaluation in controlled animal studies with carefully benchmarked histological endpoints and samples from well-defined focused clinical trial cohorts, and (c) ready availability of banked blood and urine sample archives from clinical trial populations with carefully documented morbidities such as the Framingham Heart Study,45 or the Drug-Induced Liver Injury Network (DILIN) prospective study,46 to name a few. Availability of such panels of validated biomarker assays and well-documented preclinical and clinical samples, as well as increased cooperation between animal model researchers and clinical researchers will enable individual biomarkers to be qualified for sensitivity of specifically defined adverse events, qualified for appropriate specificity using samples of defined benign events, and collected into panels that yield complementary information about the health and safety of animals and patients. 

There are also practical limitations to the selection and use of biomarkers in human studies. The biomarker should be measurable in a relatively available tissue or fluid for example, urine and breath. Sampling blood is an invasive process and so is more difficult to perform although it is done routinely. However, sampling liver tissues from humans for DNA adducts is much too invasive and would not be performed except at the time of autopsy. In addition, the assays for the marker of interest should not be so expensive that the cost of a study using the marker is prohibitive. Finally, the marker must be validated for its accuracy in quantitatively reflecting either exposure or health outcome. Otherwise, the results of the biomarker assays cannot be interpreted. 

In-study validation entails the routine monitoring of the quality control samples to determine whether the analytical method is performing consistently over time and whether data from a particular plate or run are acceptable. In addition, especially for biomarker assays, evaluation of parallelism using incurred samples is carried out to confirm the validity and suitability of the reference standard. 

Since we accept that the majority of biomarker assays will be relative (as opposed to absolute) quantitative methods, the main concern is one of reproducibility of the assay over the time course of the relevant study for which it is being used. Therefore, it is often common at the validation stage to set no accuracy acceptance criteria for the QC samples analyzed in the validation batches but to evaluate the intra- and interassay performance of the method using the QC sample results obtained therein. Thereafter, it can be assessed as to whether the assay s performance meets the requirement of the study and if so, acceptance criteria for the sample analysis batches can be set a priori. 

Careful understauding of the effects of each preanalytical variable on the biomarker data is complex and necessitates a staged approach conceptually similar to the fit-for-purpose analytical validation of a biomarker assay (see Chapter 41). In the early exploratory phase of biomarker investigation, standardization of procedures with a defined protocol for sample collection and handling will permit comparative interpretation and analysis of the data within study and/or between studies. Minimally, variables that should be experimentally evaluated to optimize sample collection for a specific biomarker will include matrix type, preservation... 

Validation use of the biomarker assay that has been developed to test large numbers of samples... 

Microarrays have become robust, reliable research tools that enable researchers to screen for a multitude of parameters using minimal amounts of sample material. The acceptance of protein microarrays is growing constantly they have already been demonstrated to be useful tools in disease-related biomarker discovery. In addition, protein microarrays have been introduced into clinical trials in order to investigate the potential adverse effects of drug candidates. Depending on the number of validated disease-specific biomarkers, as well as on their therapeutic relevance, such assays are performed either on a protein microarray or a bead-based platform. 

Methods for Determining Biomarkers of Exposure and Effect. Section 2.6.1 reported on biomarkers used to identify or quantify exposure to diazinon. Some methods for the detection of the parent compound in biological samples were described above. The parent chemical is quickly metabolized so the determination of metabolites can also serve as biomarkers of exposure. The most specific biomarkers will be those metabolites related to 2-isopropyl-6-methyl-4-hydroxypyrimidine. A method for this compound and 2-(r-hydroxy-l -methyl)-ethyl-6-methyl-4-hydroxypyrimidine in dog urine has been described by Lawrence and Iverson (1975) with reported sensitivities in the sub-ppm range. Other metabolites most commonly detected are 0,0-diethylphosphate and 0,0-diethylphosphorothioate, although these compounds are not specific for diazinon as they also arise from other diethylphosphates and phosphorothioates (Drevenkar et al. 1993 Kudzin et al. 1991 Mount 1984 Reid and Watts 1981 Vasilic et al. 1993). Another less specific marker of exposure is erythrocyte acetyl cholinesterase, an enzyme inhibited by insecticidal organophosphorus compounds (see Chapter 2). Methods for the diazinon-specific hydroxypyrimidines should be updated and validated for human samples. Rapid, simple, and specific methods should be sought to make assays readily available to the clinician. Studies that relate the exposure concentration of diazinon to the concentrations of these specific biomarkers in blood or urine would provide a basis for the interpretation of such biomarker data. 

Application to Human Exposure (Urine and Blood). To date, there have been no reports of the collection of biomedical samples from individuals with suspected lewisite exposure. Samples from such an incident will be critical for confirming the validity of assaying for the biomarkers observed in animal models. Additionally, the biomarkers that have been investigated in animal studies to date have indicated a rapid clearance in urine and less so for blood. This will obviously create severe problems for the retrospective determination of lewisite exposure beyond a few days at most when analyzing urine samples. The blood assay for both bound and free CVAA will potentially provide a longer opportunity for retrospective confirmation of exposure (based on one animal study), but also indicates a substantial decrease (90%) in concentration levels observed over a 10 day period. 

FIGURE 6.14 Workflow diagram of in study validation and sample assay of biomarker. 

The acceptance criteria for a novel biomarker can initially be determined by assay performance in prestudy method validation. Data obtained from the in-study validation using subject samples can then be used to refine the initial acceptance criteria set during the prestudy validation. For example, an assay with 50% total error may still be acceptable for detecting a twofold treatment effect observed in a clinical trial. Setting acceptance criteria a priori may not be appropriate (or even possible) in an exploratory application of novel biomarkers, since the values seen in the incurred samples may not be what is expected or predicted. 

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