EpitoPredikt – Ongoing projects

AN AI model to predict IgA epitopes

Mucosal immunization has numerous advantages over needle-based administrations; improved safety, self-delivery, capacity for mass immunizations, and no requirement for specialized training. Mucosal membranes are exposed to antigenic substances which induce specific antibody as well as cell-mediated immune responses through the secretory IgA. This could prevent the attachment of pathogens to the mucosa and plays a major role in mucosal protection. IgA is the main immunoglobulin found in mucous secretions, tears, saliva, sweat, colostrum, and secretions from the genitourinary tract and respiratory epithelium. Currently, accurate identification of IgA epitopes requires an expensive and painstakingly long screening process, and presently no prediction models have been developed to speed up the in vitro process of identifying IgA-rich antigens. However, using our in-house experimental data, we have developed an early model that can pinpoint IgA-inducing epitopes. We believe our IgA specific model will improve the accuracy of identifying IgA-epitopes, which will ultimately pave the way for the development of oral-based vaccines.

 

AN AI model to predict IgE epitopes

Allergic reactions can range from mild to severe, but in some severe cases, allergies can trigger life-threatening reactions known as anaphylaxis. IgE is associated with allergic reactions and certain infectious agents and since, IgE levels are significantly upregulated following allergic reactions, accurate identification of IgE epitopes will improve the diagnostic performance of current assays . Our EpitoGen^® scaffold, with its multiplexing capabilities, provides the ideal platform to combine allergy-causing epitopes into an accurate, affordable and user-friendly test.