AI and Automation in Regulatory Operations: The Future of eCTD Submissions

Abstract

The focus of this study is the effect that AI and automation will have on the efficiency, accuracy and compliance with the process using the Electronic Common Technical Document (eCTD) Submission Process as the case study. Construction of the submission workflow was made easier utilising the AI-driven tools machine learning (ML), robotic process automation (RPA) and predictive analytics to make them streamline, decrease errors and help the regulatory decision-making. The case studies of case studies, such as using AI with optimisation of compliance and uploading product information for Roche, Pfizer, and Novartis, have been demonstrated. One of the well-known challenges of data security, AI can nevertheless significantly increase regulatory efficiency. More research should be done towards more automated submission of regulatory data without losing interactions on the seamless global level and with integration problems in existing systems.