Now Available from Attogen Biomedical Research
PRL-3 monoclonals with high binding specificity and affinity to facilitate your tumor metastasis research
BCSG-1 MONOCLONALS SPECIFICALLY BIND TO ONCOPROTEIN, BREAST CANCER SPECIFIC GENE-I (BCSG-1), ALSO REFERRED TO AS SYNUCLEIN-GAMMA (SNCG)

Our Technologies

Epitope Mapping Technology

Epitope Mapping is a process for the identification and localization of an antibody’s binding site on a specific region of the protein antigen. The ability to characterize the epitope of a therapeutic antibody on its target protein can have impact on drug development program.  The epitope information can help researchers to understand the "mechanism of action" of the antibody drug, and to predict the potential cross-reactivity that lead to side-effects in animals or in human.  In addition, epitope mapping has been used as a powerful tool for rational drug design.  
Our Pioneering Epitope Mapping Technology combines the power of molecular biology techniques with a novel assay format. This allows systematic analysis of specific regions spanning the length of the entire protein.  We can streamline the tedious process of determining the epitope of your antibody of interest. Our job is to deliver fast, efficient, and accurate epitope maps so that you can focus your efforts in the most productive areas of your investigation.  Contact us to inquire how our epitope mapping services can facilitate your research.

Highlight of Our Epitope Mapping Technology:

  • Epitopes are expressed in human cell lines (or other species if appropriate) for natural post-translational modifications of the antigenic determinant
  • Each epitope is expressed and presented in a scaffold protein, which allow the epitope peptide to fold to its natural three-dimensional structure and to be stabilized within the environment of the scaffold protein

Direct, Normalized Biomarker Detection Technology

Protein biomarkers are an essential tool for drug discovery and development.  With advances in bioinformatics and combinatorial chemistry, the bottleneck is increasingly in understanding the biology.  Antibodies specific to the protein targets of interest are the only efficient way to directly measure target protein levels useful for screening and optimizing candidate compounds, and understanding the drug’s mechanism of action.  They can speed the advance of candidate drugs from R&D into the clinic, reducing the huge costs and risks of bringing new drugs to market. 

In addition, protein biomarkers are essential to predicting individual patient response to different therapeutic options.  This is the key to the concept of “personalized medicine” or “predictive medicine,” which is well accepted by the medical community as the wave of the future, but the reality of which has been slower to develop.  Increasingly, new drugs coming to market will be accompanied by diagnostic tests not for the disease condition, but for determining the likelihood that a particular therapy will be effective (or which of several therapeutic options will be most effective). 

In ELISA assays, detection of antibody-antigen binding invariably involves the use of a  “sandwich” consisting of a secondary antibody and tertiary probe.  This is inherently an indirect method requiring multiple steps, and may result in cross reactivity and the loss of signal specificity.  In some cases, limited binding sites make the design of an effective sandwich assay difficult or impossible.  

AttoSensorTM Detection Technology: 

Direct, quantifiable detection of antigen-antibody binding without using a sandwich assay is one of the unique capabilities of the AttoSensorTM  technology.  This allows biological samples to be screened faster and with less preparation and assay steps than with a sandwich assay.  In addition, it allows samples to be screened for multiple targets at once with normalized quantitations, which is not possible with the sandwich assay format.  In addition to benefits in drug development, this is also adaptable to clinical settings with enormous benefits for disease characterization, and predicting outcomes for different therapeutic choices.