AI-Enabled Real-World Evidence for Optimizing Pharmacotherapy Integration of Electronic Health Records, Big Data Analytics, and Predictive Modeling

Abstract

The rapid expansion of digital healthcare technologies has generated vast amounts of real-world health data, creating new opportunities to improve pharmacotherapy and drug safety monitoring. Real-world evidence (RWE), derived from sources such as electronic health records (EHRs), administrative claims databases, patient registries, and wearable health devices, provides valuable insights into treatment effectiveness and medication safety in routine clinical practice. In recent years, the integration of artificial intelligence (AI) and big data analytics has significantly enhanced the ability to analyze these complex datasets and generate clinically meaningful insights. AI-driven predictive modelling techniques, including machine learning and natural language processing, enable the identification of treatment patterns, prediction of drug responses, and early detection of adverse drug reactions. These technologies have the potential to support personalized pharmacotherapy, improve clinical decision-making, and strengthen pharmacovigilance systems. Regulatory agencies such as the U.S. Food and Drug Administration and the European Medicines Agency have increasingly recognized the importance of RWE in regulatory decision-making, drug safety evaluation, and post-marketing surveillance. However, several challenges remain in the effective implementation of AI-enabled RWE, including issues related to data quality, interoperability between healthcare systems, algorithm transparency, and patient privacy. This review examines the role of artificial intelligence in leveraging real-world evidence to optimize pharmacotherapy, focusing on the integration of electronic health records, big data analytics, and predictive modelling approaches. The review also highlights current regulatory perspectives, implementation challenges, and future directions for AI-driven healthcare analytics aimed at improving medication safety and patient outcomes.