MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641072570 A) filed by Dr. Ramakrishnan Varadharajan; Snehal Sudhakar Patwardhan; Dr. Annapurna Reddy; Khan Sana Zarrin; Hadiya Mohd Shahed Moin; R. Grace Janet Mary Ann; and Dr. Bany Joy on June 11, 2026, for Role And Potential Of Agentic Ai In Drug Discovery And Clinical Trials : A Comprehensive Study Of Ai In Healthcare.
Inventors include Dr. Ramakrishnan Varadharajan; Snehal Sudhakar Patwardhan; Dr. Annapurna Reddy; Khan Sana Zarrin; Hadiya Mohd Shahed Moin; R. Grace Janet Mary Ann; and Dr. Bany Joy.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: Role and Potential of Agentic AI in Drug Discovery and Clinical Trials : A Comprehensive study of AI in Healthcare ABSTRACT: The pharmaceutical industry progresses rapidly, albeit not necessarily at an adequate pace. The abundance of clinical data and constantly evolving laws exert significant pressure on pharmaceutical firms to perpetually innovate. Agentic AI in pharmaceuticals and healthcare can facilitate innovation and enhance efficiency. This novel category of AI examines and forecasts, but more significantly, it executes tasks and adapts dynamically. AI agents are currently transforming workflows from research and development to medical care.Agentic AI signifies a significant advancement in artificial intelligence within healthcare, featuring systems that can function independently to accomplish specified clinical objectives. The literature exhibits a deficiency in conceptual clarity about the differentiation between AI agents and Agentic AI, and few research has thoroughly investigated their applicability. Swift progress in artificial intelligence (AI) has initiated a period of hyperautomation and intelligent orchestration across various technical fields, with healthcare standing out as a particularly significant application area. Agentic AI has recently garnered interest as a sub-domain of artificial intelligence that operates autonomously, makes decisions, and exhibits goal-oriented behaviour with less human involvement. The agentic AI role mitigates the generation of unnecessary pharmaceutical information by circumventing the anomalies or artefacts included in drug action data restrictions. Retrospective and prospective pharmacovigilance identifies unknown ligand issues and associated molecular processes for the safety of medicines. Subsequently, candidate ligands that are established in their concepts and mechanisms of action may lack real-world evidence when formulated as investigational new drugs or during the suspension of existing drug licenses, potentially expediting the ligand-to-market process and significantly reducing the convoluted drug discovery pathway associated with the substantial costs of drug development.
Disclaimer: Curated by HT Syndication.
