Track 48: Artificial Intelligence in Pharmacotherapy

Artificial Intelligence in Pharmacotherapy refers to the application of advanced computational methods—such as machine learning, deep learning, and data analytics—to optimize the use of medications for improved patient outcomes.

AI enhances pharmacotherapy by analyzing large and complex datasets, including clinical records, genomic information, drug interaction databases, and real-world evidence. This enables more accurate drug selection, dose optimization, and prediction of therapeutic responses and adverse drug reactions. AI-driven models support personalized medicine by tailoring treatments to individual patient characteristics, thereby increasing efficacy and reducing risks.

In addition, AI plays a significant role in clinical decision support systems, treatment adherence monitoring, and post-marketing drug surveillance. By identifying patterns that may not be evident through traditional analysis, AI accelerates evidence-based decision-making, improves medication safety, and contributes to more efficient and cost-effective healthcare delivery.