Personalized Influenza Vaccination System with Integrated AI, IoT, and Blockchain Technologies
Legal Citation
Summary of the Inventive Concept
A comprehensive system integrating AI-driven predictive modeling, IoT-enabled wearable devices, blockchain-secured electronic health records, and synergistic vaccine formulations to optimize influenza vaccination efficacy in elderly populations.
Background and Problem Solved
The original patent addressed the limitations of traditional influenza vaccines in elderly populations by using saponins and agonists of the intracellular stimulator of interferon genes pathway. However, the new inventive concept tackles the broader challenge of personalized vaccine efficacy by incorporating cutting-edge technologies to enhance immune response, track patient data, and ensure vaccine authenticity.
Detailed Description of the Inventive Concept
The system consists of a database of patient genomic data, an AI-powered predictive model identifying high-risk patients, and a vaccine formulation comprising an influenza vaccine and a mixture of purified Quillaja saponins QA-7, QA-17, QA-18, and QA-21. The IoT-enabled wearable device monitors immune response and transmits data to a cloud-based server for AI-driven analytics. The blockchain-based platform tracks and verifies vaccine authenticity, ensuring compliance with regulatory standards. The composite material for vaccine delivery enhances immune response and provides sustained release of the saponins.
Novelty and Inventive Step
The new claims introduce a novel combination of AI, IoT, blockchain, and synergistic vaccine formulations, which is not obvious from the original patent. The inventive step lies in the integration of these distinct technologies to create a more powerful system for personalized influenza vaccination.
Alternative Embodiments and Variations
Alternative embodiments may include using different AI algorithms, incorporating additional IoT devices, or substituting the blockchain platform with other decentralized ledger technologies. Variations may include adapting the system for other vaccine types or expanding the predictive model to incorporate additional patient data.
Potential Commercial Applications and Market
The personalized influenza vaccination system has significant commercial potential in the healthcare and biotechnology industries, particularly in the elderly care and vaccine development sectors. The system's ability to optimize vaccine efficacy and ensure authenticity can lead to improved public health outcomes and reduced healthcare costs.
CPC Classifications
| Section | Class | Group |
|---|---|---|
| A | A61 | A61K39/145 |
| A | A61 | A61K39/39 |
| A | A61 | A61P31/16 |
| A | A61 | A61K2039/55 |
| A | A61 | A61K2039/55555 |
| A | A61 | A61K2039/55561 |
| A | A61 | A61K2039/55577 |
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Vaccine development, immunology, and medical informatics with a focus on geriatric vaccination technologies and personalized medical systems
Person of Ordinary Skill (PHOSITA) Profile
A professional with advanced degrees in biomedical engineering, immunology, or medical informatics, possessing expertise in vaccine design, AI-driven healthcare technologies, and understanding of immune response modulation techniques
Obviousness Rationale
A PHOSITA would recognize that integrating AI, IoT, and blockchain technologies with existing vaccine formulation techniques represents a predictable extension of known medical informatics approaches. The use of Quillaja saponins as an immune response enhancer is directly derived from the source patent, and the additional technological layers represent standard engineering design choices for personalizing medical interventions. The combination of known elements produces no unexpected results that would suggest non-obviousness.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,618 |
|---|---|
| Title | Boosting immunogenicity of vaccines using saponins and agonists of the intracellular stimulator of interferon genes pathway |
| Assignee(s) | Emory University |