MS-based Detection Platforms
Dr. Anderson hopes that this low cost, high throughput method will become a gold standard for biomarker validation.
However, for peptide biomarkers and their MS-based detection platforms, the gap between discovery and diagnostics is still wide. Some of the outstanding issues include: finding ways to reduce the costs associated with validation of biomarkers or proteomic platforms, demonstration of biomarkers' clinical significance, minimizing technical complexity, gaining regulatory approvals, and reaching pharmaceutical levels of reproducibility and sensitivity.
"After we discover the markers, they could be easily tested in a routine IVD format, such as ELISA or RIA," says Lloyd Segal, president and CEO of Caprion Pharmaceuticals. The clinical testing of the biomarkers could be done concurrently with pharmaceutical clinical trials. Biomarkers could be evaluated for their positive predictive value one-by-one or as a group, just as any other parameter in the study. Therefore, the companion diagnostics based on plasma biomarkers can be more quickly developed and tested since the protein sequence is available. But the unfortunate economics of clinical diagnostics precludes diagnostic companies in investing into biomarker discovery. They are not willing to take on significant upfront costs and risks of biomarker prospecting," continues Segal.
"It is also hard to foresee that an MS-based system such as CellCarta would be used by clinical labs for routine diagnostics," adds Dr. Opiteck. "The payoff period would be too long, especially if the tests are used for conditions with low-incidence of occurrence. ELISA-based assays are portable, cheap, sensitive, easy to use and require minimal training to perform. If one cannot raise antibodies against particular biomarkers, perhaps those biomarkers should not be used at all."
"Tracking larger sets of biomarkers is more informative, but ELISA assays are limited to measuring just a few markers at the same time. It is more feasible to look at multiple markers simultaneously by using MS," counters Dr. Becker. "If diagnostic labs believe that an MS-based test is important and that there is enough clinical data supporting the system's sensitivity, specificity and its predictive value, then they will invest. Certain high-value tests may become an important source of revenue."
Nevertheless, Predicant Biosciences makes its first steps into the diagnostics field not by selling their system, but via an internal reference lab, which the company will own and operate. "It will all come down to how strong your clinical results are," adds Dr. Becker.
"Clinical diagnostic companies are generally risk-averse," agrees Dr. Nelson. "However, they are not afraid to invest in the range of a quarter of a million dollars for biomarker discovery." According to the company, IBI entered into research agreements with several diagnostic companies. At the present time diagnostic companies are after a protein biomarker. However, the proteomic platforms themselves may have a great potential in clinical diagnostics. Their acceptance in diagnostics would depend on changes in general misperception of their costs and technical complexity.
The solution may be in full automation, minimization of human involvement, and focused interpretation of the data. Dr. Nelson envisions that performing the diagnostics using the MASSAY platform would simply require loading of the plate into the robotic workstation. The MS output would show only changes related to the protein of interest, i.e., three peaks where before it was one. "It would be a disservice to the world not to introduce proteomics tools into clinical diagnostics," continues Dr. Nelson.
"The equipment manufacturers have to start designing systems with the clinical, and not research, goals in mind. And the scientific community has to show a lot more cohesiveness and collaboration in order to develop an MS platforms for diagnostics use," concludes Haywood. "Collaborations are absolutely critical to develop a reproducible and standardized work flow from the sample collection to the final result. Parallel studies, data sharing and tying in with systems biology are the main factors that will determine success of proteomics in the diagnostic world."