Molecular Database for Antibody Characterization

Dana-Farber Cancer Institute
posted on 07/28/2010

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Quantitative flow cytometry (FC) captures the complexity of monoclonal antibody (mAb) binding interactions on a per-cell (or per-particle) basis. The resulting FC histogram contains a wealth of information; careful interpretation of this data is key to capturing the power of this technique. This invention provides a computer repository of FC histograms accessible through the internet. Search algorithms allow the user to obtain information concerning mAbs that meet selection criteria. Novel algorithms allow for comparison of histograms across several mAbs, cell types and subpopulations within cell types. The database is not stagnant-new histograms will be added as users submit mAbs for FC analysis against a panel of cell types. The database will be continually be updated with this histogram information. New mAbs may produce histograms that do not correspond to known patterns; discussion threads on the website will guide the identification of these potentially novel mAbs.

Applications/Advantages: Because the generation of mAbs depends upon complex biologic processes, the characterization of novel mAbs can be unpredictable, expensive, and time-consuming. A database approach can significantly reduce expenditures in both time and cost. The Leukocyte Differentiation Antigen Database contains cytometry data, however these data were compiled across multiple laboratories, confounding comparison among mAbs. In contrast, this technology features data compiled under equivalent conditions in the same laboratory, and between-lab variability is eliminated from the comparison. Furthermore, this invention provides a well-defined algorithm for the comparison of complex FC histograms. Currently, investigators often compare pairs of histograms by eye. The computer-based algorithm approach is both more objective and amenable to database-wide comparisons.