Tutorial- Tuesday at 2:00 PM EDT
Title: Decentralized Clinical Trials –Statistical and Data Considerations
Presenters: Fanni Natanegara, Eli Lilly

Abstract:

The pandemic has changed the landscape of clinical trials to be more patient centric and to enable continuous access for patients to health care and promising medicines through the decentralized framework. Decentralized approach may include capabilities such as digital recruitment, telemedicine, mobile health care, and digital health tools (DHT). Decentralized Clinical Trial (DCT) can increase trial access by expanding geographic boundaries and patient demographic representations; thereby, increasing generalizability of the trial result and reduce bias. At the same time, DCT present challenges with lack of standardization of remote data collection and DHTs, potential mixed modalities of data collection and technical interruption which can lead to additional variability associated with the outcomes of interest and missed opportunity on identifying potentially effective treatments. In this talk, we will discuss study design, method, and data considerations in DCT to overcome these challenges and to generate the scientific evidence needed for promising investigative treatments.


Bio:
Fanni Natanegara, Ph.D. , is a Research Advisor and currently serve as the Statistics Group Leader for the Neurodegeneration team at Eli Lilly and Company. She is also currently leading the internal statistical effort on Decentralized Clinical Trials (DCT) with the mission to develop  evidence based on recommendations on the use of appropriate digital health technology, data collection method, study designs and statistical analyses in DCT.  Dr. Natanegara is also actively engaged in external professional organizations including serving as Chair of the cross industry-regulatory-academic Drug Information Association (DIA) Bayesian Scientific Working Group with a vision to ensure that Bayesian methods are well-understood and broadly utilized for design and analysis throughout the medical product development process and to improve industrial, regulatory, and economic decision making. She is currently the Chair of the American Statistical Association (ASA) Statistical Partnership among Academe, Industry, and Government (SPAIG) committee with a charge to identify, lead, and promote initiatives that foster statistical partnerships or amongst Academic, Industry, and/or Government sectors.