Biomarkers


Figure 4 The drawing shows the utility of immunoassay and mass spectrometry technology platforms. The role, application as well as the potential benefit derived from each platform is mapped to the development stage. [Sources: Adapted from MIT Broad Institute and NCI/CPTC websites and E. A. Dalmasso, GEN, Planning for Success in Biomarker Discovery Appropriate Proteomics Platform and Careful Study Design Can Improve Positive Results, Jun 15 2008 (Vol. 28, No. 12)]


and systematic influences, ie, both precision and trueness. Its numerical value is the total error of measurement. Other metrics of analytical per- formance include a number of different ‘detection limits’ that define different properties of the assay, including the Lower Limit of Detection (LLOD), the Instrument Detection Limit (IDL), the Method Detection Limit (MDL), the (Lower) Limit of Quantitation (LOQ or LLOQ), and the Practical Quantitation Limit (PQL), as well as the Coefficient of Variation (CV) as a normalised measure of dispersion of a probability distribution (defined as the ratio of the standard deviation to the mean). In addition, parameters such as analyt- ical range, analyte stability, standard stability and reagent stability need to be tested and described as part of analytical performance characterisation.


Diagnostic accuracy and clinical validation: Diagnostic accuracy, determined by a process com- monly referred to as clinical validation, refers to the degree with which results of a test concur with what would be considered the current gold stan- dard of clinical assessment of the interrogated question. This may be another biomarker (ie an established reference test) or – the real gold stan- dard – a clinical outcome or endpoint, such as sur- vival or death. Accuracy can be expressed through


Drug Discovery World Winter 2010/11


sensitivity and specificity, positive and negative predictive values, or positive and negative diagnos- tic likelihood ratios. Each measure of accuracy should be used in combination with its comple- mentary measure: sensitivity complements speci- ficity, positive predictive value complements nega- tive predictive value, and positive diagnostic likeli- hood ratio complements negative diagnostic likeli- hood ratio. All of these parameters are not intrin- sic to the test and are determined by the clinical context in which the test is employed. A summary of the characteristics, and the strengths and weak- nesses of these metrics is presented in Table 2. Biomarker validation requirements typically progress from the early to the later stages of drug discovery and development. Research-grade (‘home-brew’) assays are sufficient in the early, exploratory stage where biomarkers are discov- ered or interrogated as putative markers. As evi- dence is accumulated and the likelihood of clini- cal validation rises, assays that fulfill somewhat higher quality requirements (such as ‘analyte-spe- cific reagents’) will be used, in a setting that is more controlled (eg CLIA accreditation). In yet later stages of clinical development, ultimately fully approved in vitro device status for regulato- ry authority approved tests fit for commercialisa- tion is required. If a biomarker is to be used as a


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