MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641082546 A) filed by Arockia Raj A; Dr. N. Vijayalakshmi; Sivaprabha T; B. Jyothi; Dr. G. Anandhakumari; Dr. Neha Khanam; Mr. Rathod Shubham Shrikant; P. Subhash Chandra Bose; Dr. P. Srikanth Reddy; Vishwanath Patil; Dr. I. D. Soubache; and Vishnupriya. K on July 04, 2026, for Integrated Artificial Intelligence And Nanoparticle Platform For Personalized Breast Cancer Treatment.
Inventors include Arockia Raj A; Dr. N. Vijayalakshmi; Sivaprabha T; B. Jyothi; Dr. G. Anandhakumari; Dr. Neha Khanam; Mr. Rathod Shubham Shrikant; P. Subhash Chandra Bose; Dr. P. Srikanth Reddy; Vishwanath Patil; Dr. I. D. Soubache; and Vishnupriya. K.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: INTEGRATED ARTIFICIAL INTELLIGENCE AND NANOPARTICLE PLATFORM FOR PERSONALIZED BREAST CANCER TREATMENT This invention presents an Integrated Artificial Intelligence and Nanoparticle Platform for Personalised Breast Cancer Treatment, integrating artificial intelligence (AI), machine learning, nanotechnology, and precision medicine to improve the diagnosis, treatment, and monitoring of breast cancer. The platform gathers multimodal patient data, encompassing medical images, histopathology reports, genomic information, biomarker profiles, laboratory results, and electronic health records, and analyses the data with sophisticated AI algorithms to identify breast cancer, categorise tumour subtypes, forecast disease progression, and assess individual treatment responses. The AI-generated analysis recommends personalised treatment strategies and optimises nanoparticle-based targeted drug delivery by selecting appropriate nanoparticle formulations, drug dosages, particle sizes, surface functionalization’s, and controlled-release properties for the efficient delivery of anticancer drugs directly to tumour cells. The invention includes real-time patient monitoring via wearable devices, follow-up imaging, laboratory tests, and clinical evaluations, facilitating ongoing assessment of treatment efficacy and the dynamic adjustment of therapy strategies through adaptive learning models. A secure cloud architecture and clinician decision-support dashboard offer explainable AI recommendations, predictive analytics, and thorough patient care while maintaining data privacy and regulatory compliance. The invention enhances treatment precision, minimises systemic toxicity and adverse effects, improves therapeutic efficacy, facilitates personalised medicine, and contributes to better survival rates and quality of life for breast cancer patients by integrating intelligent clinical decision support with targeted nanoparticle drug delivery. FIG.1.
Disclaimer: Curated by HT Syndication.
