This course provides a comprehensive understanding of clinical research processes involved in the development and evaluation of new drugs, medical devices, vaccines, and treatment strategies. Participants will learn the principles of clinical trial design, ethical and regulatory requirements, Good Clinical Practice (GCP) guidelines, data management, pharmacovigilance, and clinical trial monitoring.
This course provides a comprehensive understanding of how Artificial Intelligence (AI), Machine Learning (ML), and causal modeling techniques can be applied to generate reliable Real-World Evidence (RWE) from healthcare data. Participants will learn how to move beyond predictive analytics and establish causal relationships that support clinical, regulatory, and healthcare decision-making.
The program covers key concepts of causal inference, including confounding, bias, treatment effect estimation, propensity score methods, target trial emulation, and advanced AI/ML approaches for causal analysis.
RWE & HEOR focus on understanding how medical treatments perform in real-life settings and evaluating their economic and health impact. RWE uses real-world data—such as electronic health records, insurance claims, and patient registries—to generate insights on effectiveness, safety, and patient outcomes. HEOR complements this by assessing the value of healthcare interventions, helping decision-makers optimize pricing, reimbursement, and resource allocation.
This program integrates the core principles of clinical research, biostatistics, clinical data management, and CDISC-compliant statistical programming, providing learners with hands-on experience in analyzing clinical trial data and generating regulatory-ready outputs. Participants gain expertise in study design, protocol development, data collection methodologies, statistical concepts, hypothesis testing, survival analysis, and advanced clinical data interpretation.
This comprehensive course provides learners with a strong foundation in pharmacovigilance principles, drug safety regulations, adverse event reporting, case processing, signal detection, risk management, and global regulatory requirements. Participants will gain practical knowledge of how safety data is collected, analyzed, and communicated to regulatory authorities, healthcare professionals, and patients.