CLINICAL AND PHARMACOEPIDEMIOLOGY: REAL-WORLD EVIDENCE, DRUG SAFETY, AND POPULATION-BASED THERAPEUTICS

Abstract

Clinical epidemiology and pharmacoepidemiology are rapidly evolving scientific disciplines that integrate clinical medicine, epidemiological principles, pharmacology, and advanced data science to improve healthcare decision-making and optimize therapeutic outcomes. Clinical epidemiology focuses on applying quantitative methods to clinical practice, enabling improved diagnosis, prognosis, and treatment evaluation at the individual patient level. In contrast, pharmacoepidemiology extends these principles to large populations, assessing the use, effectiveness, and safety of pharmaceutical products under real-world conditions.

The increasing complexity of modern therapeutics, including biologics, biosimilars, combination therapies, and personalized medicine approaches, has necessitated more robust and scalable methods for drug safety and effectiveness evaluation. Traditional randomized controlled trials (RCTs), although considered the gold standard, often lack external validity due to strict inclusion criteria and controlled environments. Therefore, pharmacoepidemiological approaches based on real-world data (RWD) have become essential in complementing clinical trial evidence.

In recent years, the integration of electronic health records (EHRs), insurance claims databases, patient registries, and mobile health technologies has enabled large-scale real-world evidence (RWE) generation. Simultaneously, advancements in artificial intelligence (AI), machine learning (ML), and big data analytics have revolutionized pharmacovigilance and drug utilization research by enabling automated adverse drug reaction (ADR) detection and predictive modeling of drug safety outcomes. Despite these advancements, challenges such as confounding bias, data heterogeneity, privacy concerns, and regulatory standardization remain significant barriers. This review provides a comprehensive Scopus-level overview of clinical epidemiology and pharmacoepidemiology, emphasizing methodological foundations, real-world evidence generation, pharmacovigilance systems, AI integration, and future perspectives in precision public health.