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Activity Number: 641
Type: Topic Contributed
Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #318841
Title: Use of the VG (Virtual Twins Combined with GUIDE) Method in the Development of Precision Medicines
Author(s): Jia Jia* and Qi Tang and Wangang Xie and Richard A. Rode
Companies: and AbbVie and AbbVie and AbbVie
Keywords: subgroup identification ; precision medicines ; individual treatment effect ; Type I error

A lack of understanding of human biology creates a hurdle for the development of precision medicines. To overcome this hurdle we need to better understand the potential synergy between a given treatment (vs. placebo or active control) and various demographic or genetic factors, disease history and severity, etc., with the goal of identifying those patients at increased risk of exhibiting meaningful treatment benefit. For this reason we proposed the VG method, which combines the idea of individual treatment effect (ITE) from the Virtual Twins method (Foster et al 2013, Stat Med) and the unbiased variable selection and cutoff value determination algorithm from the GUIDE method (Loh 2015, Stat Med). Simulation results showed the VG method to have less variable selection bias than Virtual Twins and higher statistical power than GUIDE in the presence of prognostic variables with strong treatment effects. The type I error and predictive performance of Virtual Twins, GUIDE and VG were also compared through the use of simulation studies and a randomized clinical trial for Alzheimer's disease.

Authors who are presenting talks have a * after their name.

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