A STUDY ON IDENTIFYING GAPS IN TRADITIONAL REGULATORY DOSSIER PROCESSES AND THE ROLE OF ARTIFICIAL INTELLIGENCE IN STREAMLINING SUBMISSION WORKFLOWS

Abstract

Preparing regulatory dossiers is essential for getting pharmaceutical products approved, as it ensures their quality, safety, and effectiveness. However, current dossier processes are still largely manual, which leads to repetitive work, delays, and a higher chance of errors or compliance issues. This review identifies key gaps in conventional regulatory dossier processes and explains how Artificial Intelligence (AI) can streamline submission workflows to improve efficiency, accuracy, and global harmonization. The study explores various AI technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Robotic Process Automation (RPA) that automate data collection, document authoring, and validation. Secondary data were gathered from published literature, regulatory portals, and global digital initiatives. Regulatory agencies like the FDA and EMA have already begun using AI systems, and India’s CDSCO is moving toward digital transformation with SUGAM 2.0. AI-based tools including Veeva Vault, PhlexSubmission, and Genpact Cora Regulatory AI are improving accuracy, transparency, and overall workflow efficiency. The study envisions Smart Dossier Management Systems (SDMS) integrating blockchain and predictive analytics for real-time compliance and global harmonization. This shift represents a move from manual, document-heavy processes to intelligent, data-driven regulatory practices.

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