MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641111059 A) filed by Pragati Engineering College on September 16, 2026, for Ai-Based Medicine Expiry Prediction And Redistribution Management System.
Inventors include Dr. Chandra Sekhar Koppireddy; Dr. Subodh Kumar Panda; Mr. N Raghuveer; and Mr. Krishna Chaitanya Pidugu.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: Medicine expiry and inefficient inventory management is one of the top most problems found in hospitals, pharmacies, clinics, distribution centres of healthcare. Traditional methods mainly count on manual checking, hardcoded expiration date notifications, limited stock ledger which might not identify the medicines that will remain unused even before their respective dates. It is noticed that overstocking, sporadic consumption, uncoordinated management among different healthcare institutions, lack of intelligent redistribution mechanism ultimately led to huge medicine Wastage and financial losses. The proposed solution is the AI-Based Medicine Expiry Prediction and Redistribution Management System. The proposed system consists of medicine inventory management, Medicine expiry tracking, Historical consumption management, Artificial intelligence (AI) & Machine learning (ML), Medicine demand Forecasting, and multi-location redistribution of medicines. Data inputs consist of medicine details such as medicine name, batch number, quantity, manufactured date, expiry date, shelf location, historical demand for medicines. These details would be stored in central database. The AI/ML module will analyse the remaining shelf life of the medicine, stock available, last month consumption, predicted future demand to calculate probability for the medicine to expire. Medicines could be categorized by its category of expiry risk level, which allows healthcare workers to take adequate measures. Medicines can be predicted using their predicted demand using the Demand forecasting model. Based on the predicted demand and future stock available in different healthcare facilities, the system compares potential expiring medicines with surplus quantity against other healthcare’s predicted need of it. When a medicine is predicted to have higher expiry risk and some healthcare institutions predict the need for it, the system initiates the recommendation for redistribution. All relevant stakeholders can access a real-time centralized dashboard, which showcases the information on stocks, their predicted expire probability, future demand, and redistribution recommendations. The envisioned system shifts the paradigm of traditional reactive inventory management to intelligent and coordinated stock keeping. It will also help to reduce medicine wastage, unnecessary procurement, increase stock utilisation, supply timely medicine availability in due course.
Disclaimer: Curated by HT Syndication.
