Leveraging AI, ML, and Data Analytics to Evaluate Compliance Obligations in Annual Reports for Pharmaceutical Companies

Abstract

This paper delves into the utilization of artificial intelligence (AI), machine learning (ML), and data analytics to assess compliance obligations within annual reports for pharmaceutical companies. Annual reports serve as pivotal documents for showcasing a company's financial performance, regulatory adherence, and overall governance. However, ensuring compliance with regulatory standards poses significant challenges in the dynamic pharmaceutical landscape. By harnessing AI, ML, and data analytics technologies, this study aims to streamline the evaluation process, enhance accuracy, and identify potential areas of non-compliance within annual reports. Through a comprehensive analysis of regulatory frameworks, industry guidelines, and historical data, the paper explores how advanced analytics can facilitate proactive compliance management, mitigate risks, and ensure transparency and accountability. Insights derived from this research can inform pharmaceutical companies' strategies for optimizing compliance processes, fostering regulatory confidence, and maintaining stakeholders' trust in the industry.