DIA 2017 Annual Meeting

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-17-549-L04-P; CME 1.25; IACET 1.25; RN 1.25

It is estimated that about one-third of clinical trial failures may be due to enrollment challenges. Rare disease trials are no exception and encounter many patient recruitment and retention difficulties. Small numbers of patients who are spread over large geographic areas, as well as singular aspects of specific diseases that may not be well understood, contribute to the unique set of challenges faced by rare disease studies. Traditional methods for recruitment of patients are frequently not adequate to populate rare disease trials. This session will discuss the importance of tailoring the rare disease research process to the specific patient population to be studied, from early trial design and protocol planning through enrollment and study conduct. Successful approaches to improving recruitment through collaboration with patient groups in early planning stages and identification of patients through innovative analyses of real world data will be examined.

Learning Objectives

Identify new tools leveraging real-world data and innovation in advanced analytics including the growing field of machine learning technology, and how the advancements in this field are creating opportunities for dramatic improvements in identifying hard-to-find patients.

Chair

William B. Smith, MD

Speaker

Big Data with Investigator and Patient Advocacy Outreach in Idiopathic Pulmonary Fibrosis: A More Complete Picture
Adina Kay Knight, MD