MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641050244 A) filed by Dr. Latha Kiran Krishna Rajendran, Bangalore, Karnataka, on April 20, for 'ai-guided design of epr-responsive nanocarriers for personalized tumor-targeted chemotherapy.'
Inventor(s) include Dr. Latha Kiran Krishna Rajendran.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Cancer chemotherapy continues to face profound clinical limitations arising from the systemic toxicity of conventional drug delivery paradigms, wherein therapeutic agents are distributed non-selectively throughout the body, exposing healthy tissues to cytotoxic compounds while achieving sub-therapeutic drug concentrations within tumor microenvironments. The Enhanced Permeability and Retention (EPR) effect, arising from the aberrant vasculature and impaired lymphatic drainage characteristic of solid tumors, presents a fundamental biophysical opportunity for passive nanocarrier accumulation within tumor tissues, yet existing nanocarrier design methodologies lack the computational intelligence required to systematically optimize EPR exploitation across the heterogeneous tumor phenotypes encountered in personalized oncology practice. [510] Existing nanocarrier design platforms exhibit critical deficiencies in their capacity to simultaneously optimize physicochemical nanoparticle parameters including size, surface charge, polymer composition, and drug loading efficiency for individual patient tumor profiles, dynamically adapt drug release kinetics in response to tumor microenvironment biochemical signals, predict patient-specific EPR responsiveness from pre-treatment diagnostic imaging data, and integrate multi-omics biomarker information into nanocarrier formulation decision pipelines. These limitations result in suboptimal therapeutic outcomes, unnecessary patient exposure to ineffective treatment regimens, and significant delays in the translation of nanocarrier design innovations into clinically deployable personalized cancer therapeutics. [515] The integration of Artificial Intelligence capabilities including deep learning-based nanoparticle property prediction, generative molecular design algorithms, reinforcement learning-driven formulation optimization, and multimodal patient data fusion frameworks presents transformative opportunities for revolutionizing EPR-responsive nanocarrier design. AI systems capable of learning the complex relationships between nanocarrier physicochemical parameters and tumor accumulation efficiency from large experimental datasets can autonomously design optimized nanocarrier formulations tailored to individual patient tumor characteristics, predict clinical response probabilities, and accelerate the bench-to-bedside translation of personalized nanomedicine. [520] The present invention describes a comprehensive AI-Guided EPR-Responsive Nanocarrier Design System that integrates patient-specific tumor microenvironment characterization modules, deep learning nanoparticle property prediction engines, generative adversarial network-based nanocarrier molecular design frameworks, reinforcement learning formulation optimization controllers, and clinical outcome prediction systems within a unified personalized nanomedicine design platform. The system continuously analyzes patient diagnostic data, tumor biomarker profiles, and experimental nanocarrier performance databases to design, predict, and optimize tumor-targeted chemotherapy nanocarrier formulations with precision and personalization exceeding current empirical formulation methodologies. [525] Validation studies conducted across multiple oncology research institutions demonstrated that the AI-Guided EPR-Responsive Nanocarrier Design System achieved a 52.4 percent improvement in tumor accumulation efficiency, 61.7 percent reduction in off-target systemic drug exposure, 44.3 percent acceleration in nanocarrier formulation optimization timelines, and 68.9 percent improvement in patient-specific treatment response prediction accuracy compared to conventional empirical nanocarrier design and standard chemotherapy administration methodologies. [530] The research findings confirm that the AI-Guided EPR-Responsive Nanocarrier Design System constitutes a foundational technological advancement for personalized nanomedicine infrastructure, with deployment potential spanning oncology research institutions, pharmaceutical development organizations, clinical cancer treatment centers, biomarker diagnostic laboratories, and translational medicine facilities requiring intelligent, patient-adaptive, high-precision tumor-targeted drug delivery design capabilities."
Disclaimer: Curated by HT Syndication.
