2. Identification of Disease-Specific Spectral Signals

The Company subjects the compiled data of both the Standard Spectral Survey and Advanced Spectral Profile to multiple analytical strategies to identify spectral patterns and further characterize spectral differences between normal and disease subjects. Most spectral comparative computational methods employ multivariate analytical strategies that isolate key differentiating features of the spectra. Comparative methods include simple comparison of selected spectral variables, comprehensive methods that fully analyze underlying spectral features, as well as computationally 'intelligent' methods such as a neural net. Figure 1. Detection of a discriminatory intrinsic fluorescence spectral signal that differentiates between normal and HCV-infected human plasma samples. (See: [2001] Transfusion vol. 41(9), p77-78S)

This information provides the definition of a discriminatory spectral difference between a diseased and healthy cohort, and establishes the initial package of proprietary information supporting the out-licensing or further pursuit of the molecular determinants of the spectral difference. Recognizing that any spectral difference is a manifestation of an underlying molecular difference, the establishment of a definitive and reliable spectral difference represents valuable information for internal product development decision making and to prospective partners.

In addition to providing a decisive demonstration of discrimination between groups, these results provide the foundation for selecting detection methods and parameters for isolating the underlying indicator molecules. In some cases, like the results from SerOptix' HCV studies, these spectral features may offer sufficient discriminatory power for development of a direct detection assay (i.e. the ID-LBS). SerOptix will evaluate the potential of any spectral discriminators as parameters for the development of a direct assay based on the level of discrimination and specific business opportunity offered.


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