MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202611073639 A) filed by Arti Sharma; Himanshi Sharma; Chanchal Singh; Babita Chaudhary; Sarika Tyagi; Deepa Solanki; Atinder Pal Singh; and Dr. Gaurav Dubey on June 13, 2026, for Method And System For Early Tuberculosis Drug Candidate Identification Using Ai-Assisted Virtual Screening.
Inventors include Arti Sharma; Himanshi Sharma; Chanchal Singh; Babita Chaudhary; Sarika Tyagi; Deepa Solanki; Atinder Pal Singh; and Dr. Gaurav Dubey.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: The present invention provides an early identification method and system of tuberculosis drug candidates by means of virtual screening with the help of artificial intelligence. The proposed framework involves collecting molecular data, preprocessing, generating the molecular descriptors, predicting activity, docking, prediction of the pharmacokinetic parameters, and ranking the candidates in a single platform. Molecules retrieved from one or many chemical databases are processed to remove any relevant structural and physicochemical properties. The features are therefore analyzed with machine learning and deep learning models to predict anti-tuberculosis activity. The compounds predicted are then subjected to molecular docking to evaluate binding affinity, ADMET analysis to assess its safety and pharmacokinetics, and are profiled.The predicted compounds are also profiled by molecular docking to check binding affinity, ADMET analysis for safety and pharmacokinetics. The compounds are ranked using a composite scoring and a prioritized list of potential drug candidates is generated. The system also includes an explainable AI layer for enhanced transparency in predictions, and an experimental validation mechanism for evaluating and refining the performance of the system over time. The proposed invention provides a process to accelerate drug discovery process, lower cost of screening and enhance the efficiency of identifying promising anti-tuberculosis lead drug compound for experimental validation.
Disclaimer: Curated by HT Syndication.
