Personalized Allergy Treatment Ecosystem
Legal Citation
Summary of the Inventive Concept
A comprehensive system integrating advanced genomics, machine learning, and nanotechnology to provide customized allergy diagnosis, treatment, and real-time monitoring, revolutionizing the field of immunology and allergy research.
Background and Problem Solved
The original pan-antiallergy vaccine patent, while groundbreaking, has limitations in terms of personalized treatment and real-time monitoring. The new inventive concept addresses these limitations by envisioning a next-generation allergy treatment ecosystem that leverages cutting-edge technologies to provide tailored solutions for individual patients.
Detailed Description of the Inventive Concept
The Personalized Allergy Treatment Ecosystem consists of multiple components, including a biomarker detection module, a treatment response prediction algorithm, a customized allergy vaccine generator, a wearable device for real-time allergy monitoring, and a cloud-based platform for allergy research and development. The system utilizes machine learning-based genomics analysis to identify an individual's specific allergy profile and synthesizes a vaccine composition comprising antigenic peptides specific to the identified allergens. The wearable device detects IgE levels and predicts allergic reactions, transmitting alerts to the user's device. The cloud-based platform facilitates collaboration among researchers and provides a database of genomic and proteomic data related to allergies.
Novelty and Inventive Step
The new inventive concept introduces a paradigm shift in allergy treatment by integrating personalized genomics, machine learning, and nanotechnology to provide a comprehensive and customized solution. The inventive step lies in the synergistic combination of these technologies to create a novel ecosystem that surpasses the capabilities of the original pan-antiallergy vaccine.
Alternative Embodiments and Variations
Alternative embodiments of the Personalized Allergy Treatment Ecosystem could include the use of different machine learning algorithms, various types of biomarkers, or alternative nanotechnology-based delivery systems. Variations of the system could also be designed for specific types of allergies or targeted towards particular demographics.
Potential Commercial Applications and Market
The Personalized Allergy Treatment Ecosystem has significant commercial potential in the pharmaceutical, biotechnology, and healthcare industries. The system could be marketed as a comprehensive solution for allergy treatment, offering a competitive advantage over existing treatments. The cloud-based platform could also generate revenue through subscription-based access to the database and collaboration tools.
CPC Classifications
| Section | Class | Group |
|---|---|---|
| A | A61 | A61K39/395 |
| A | A61 | A61K2039/544 |
| A | A61 | A61K2039/555 |
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Immunology, biotechnology, and personalized medicine, with expertise in protein engineering, vaccine design, and machine learning applications in medical diagnostics
Person of Ordinary Skill (PHOSITA) Profile
A researcher with advanced degrees in biotechnology or immunology, proficient in computational biology, protein modeling, machine learning techniques, and understanding of immunological systems and vaccine development
Obviousness Rationale
A PHOSITA would recognize that the personalized allergy treatment ecosystem represents a predictable extension of existing pan-antiallergy vaccine technologies by integrating known computational and diagnostic techniques. The combination of machine learning, genomic analysis, and targeted vaccine design follows established methodological approaches in precision medicine. The technical variations represent incremental improvements that would be obvious to a skilled practitioner seeking to enhance allergy treatment strategies.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,623 |
|---|---|
| Title | Pan-antiallergy vaccine |
| Assignee(s) | King Abdulaziz University |