(101b) Quantification and Machine Learning Prediction of Immunological Desensitization Biomarker

Allergic diseases pose a significant health burden globally. Immunotherapy offers a promising approach to alleviate symptoms and potentially cure allergies. However, current methods to monitor desensitization, the process by which the immune system becomes less sensitive to allergens, are subjective and lack precision. This research project aims to develop a quantitative and objective approach to assess immunological desensitization using machine learning. We will investigate the identification and quantification of immunological biomarkers that correlate with desensitization progress. Machine learning algorithms will be trained on patient data to predict desensitization outcomes and guide treatment decisions. This project has the potential to revolutionize allergy diagnosis and treatment by providing a data-driven approach to monitor desensitization and personalize immunotherapy regimens.