MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202631097378 A) filed by Nikhil Ranjan Nayak; Tanmaya Bhoi; Prashant Sharma; Aadesh R Desai; Dr. Sunita Gupta; and Vijayasri Ganji on August 12, 2026, for Ai-Driven Drug Interaction Risk Prediction System Using Patient-Specific Biological Data.
Inventors include Nikhil Ranjan Nayak; Tanmaya Bhoi; Prashant Sharma; Aadesh R Desai; Dr. Sunita Gupta; and Vijayasri Ganji.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: 0031] The present invention discloses an AI-driven drug interaction risk prediction system utilizing patient-specific biological data for personalized medication safety assessment. The system integrates electronic health records, laboratory biomarkers, genomic information, physiological parameters, medication history, wearable sensor data, and disease characteristics into a unified artificial intelligence framework. Hybrid machine learning algorithms analyze individualized biological profiles to estimate drug interaction risks, classify severity levels, and generate personalized therapeutic recommendations. Explainable artificial intelligence provides transparent reasoning for every prediction by identifying influential biological variables. A continuous learning mechanism updates prediction models using validated clinical outcomes to improve accuracy over time. The invention reduces adverse drug events, minimizes false clinical alerts, supports precision medicine, enhances prescription safety, and improves evidence-based clinical decision-making across diverse healthcare environments.
Disclaimer: Curated by HT Syndication.
