Menu Back to Real-World-Evidence-Conference

Overview

Short Course: Coming Soon!
November 10-11: Conference

DIA is offering both a live in-person conference or an On Demand Library for the Real-World Evidence Conference that allows you to view all the session recordings from the comfort of your own home/office at your own pace. Upon registration, please indicate via the check box which avenue you are registering for: in-person or on demand.

In a market that is constantly adapting and adjusting to the needs of the healthcare field, real-world evidence (RWE) is increasingly becoming important for regulatory and reimbursement decision-making. RWE, in relation to the real-world data that is collected in combination with the advancement of artificial intelligence-based analytics platforms, has led to the real-time analysis of data to better understand and gain insights on disease, approaches to treatment, and how to substantiate coverage decisions. Historically used for post-market safety monitoring, RWE is now becoming integrated throughout the product development lifecycle. DIA’s Real-World Evidence Conference will explore new and innovative applications of RWE and deliver cutting-edge insights through successful use cases, case examples, and practical applications on how stakeholders are leveraging RWE to advance healthcare knowledge and decision-making.

While we prepare for the 2022 Real-World Evidence Conference check out our 2021 Program.

Who should attend?

Professionals involved in:
  • Real-World Evidence
  • Real-World Data
  • Epidemiology
  • Policy
  • Regulatory Science
  • Technology development
  • Data analytics
  • Clinical Research

Learning objectives

At the conclusion of this activity, participants should be able to:
  • Explain how RWE is being used today to inform biopharmaceutical development across the product lifecycle
  • Discuss “lessons learned” from current uses of RWE by regulators, and how they can be applied for other future applications of RWE
  • Recognize general considerations and key features of successful RWE studies acceptable to the regulators for effective decision-making
  • Identify guidance and best practices for generating fit-for-purpose RWE for payers and HTA bodies
  • Define the expanding applications of RWE to support clinical trials and evidence generation
  • Evaluate the future applications of RWE in drug development
  • Appraise how mobile technologies, artificial intelligence, machine learning, and other technologies are being used to generate RWE
  • Evaluate how patient reported outcomes, electronic health records, and other patient data is expanding the resources for RWE

Digital Learning Catalog

DIA Learning: eLearning Soultions
Download