Biomedical Engineering Reference
In-Depth Information
benefit. Some of the common surrogate markers include blood pressure and choles-
terol (for predicting therapy benefit in heart disease), CD4 count/viral load (for
assessing HIV infection), and prostate-specific antigen (PSA; for prostate cancer
screening).
3.3 TECHNOLOGY PLATFORMS
In the past, biomarker assays were mostly quantitative using immunoassays and to
a lesser degree quantitative mass spectrometry methods. These methods mostly
analyzed a single biomarker such as a circulating protein, peptide, or metabolite.
Today, we are seeing more multiplexed assays being developed and a move toward
patient stratification biomarkers using genotyping or gene expression. We are also
exposed to many new and novel technologies that claim improved accuracy and/or
increased sensitivity. Some of these technologies will have significant effects on the
measurements of biomarkers. One such example is the Erenna
platform (Singulex,
Inc.) used for measurement of troponin I, which has shown that its limit of detection of
0.2 ng/mL surpasses that of most of the commercial assays [13]. Using the Erenna
platform for measurement of IL-13 in serum lowered the lower limit of quantitation
of IL-13 in serum from 9.8 to 0.07 pg/mL, a 140-fold increase in sensitivity, using
identical antibody pairs [14]. A number of recent advances in technology are
contributing to the discovery of new biomarkers and to the development of new
biomarker tools to measure them in a variety of tissue types. Molecular technology
platforms such as arrays for DNA, mRNA, and miRNA, Q-PCR, and sequencing;
platforms for measuring proteins such as ELISA and IHC/FISH; multiplexed plat-
forms using Luminex, MesoScale Discovery, mass spectrometry-based technologies,
and so on; and cellular platforms such as FACS and CellSearch are being widely used
for biomarker research [15-18].
Major challenges with many of the “omics” technologies (proteomics, genomics,
metabolomics, etc.) and other multiplexed technologies are the sheer volume of data
generated and the lack of clear guidelines from regulatory agencies on the required
analytical validation of these methods, especially when using newly developed
technologies. Nowhere has the revolution been greater than in DNA sequencing.
Some of the most advanced technologies today, such as SOLiD and Illumina GAIIx,
are capable of producing 400 million 50 bp and
200 million 75-100 bp reads,
respectively [19]. The cost of performing extensive analytical validation of many
of these new technologies is somewhat prohibiting, but nowhere close to the cost of
conducting translational medicine clinical studies to qualify a biomarker or a set
of biomarkers. FDA has regulatory oversight over all medical devices when it comes
to the analytical and clinical validity of a test and considers the most crucial validation
to be the clinical performance of a test [20]. Several research papers have proposed
a “fit-for-purpose” approach to method development and validation [21, 22] based on
the intended use of the biomarker results in discovery and/or clinical development.
This approach is gaining acceptance, but seems to be usedmostly for internal decision
making in the pharmaceutical industry. When using biomarker results for regulatory
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