Abstract Details
Activity Number:
|
179
|
Type:
|
Contributed
|
Date/Time:
|
Monday, August 5, 2013 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Biopharmaceutical Section
|
Abstract - #308933 |
Title:
|
Improved Biosimilar Design via Disease-Progression Model
|
Author(s):
|
Russell Reeve*+ and Guochen Song and Michael O'Kelly
|
Companies:
|
Quintiles and Quintiles and Quintiles
|
Keywords:
|
biosimilars ;
disease-progression ;
model-based drug development ;
function norm
|
Abstract:
|
A biosimilar is a biological agent that is intended to be identical to a previously approved biological agent, a large molecule analog to the generic product. However, unlike small molecules, equivalent efficacy cannot be inferred from drug exposure alone, but must also involve equivalency in a relevant clinical endpoint. Following the FDA guidance on biosimilars can yield larger sample sizes than is practical, and so creative methods of reducing the sample sizes and risk associated with biosimilar development are sought. We have developed a novel methodology for assessing clinical equivalence based on the norm of a disease-progression model. We show that this method yields smaller sample size for a given power, and better detection of nonsimilarity when nonsimilarity exists. It does so because more information is used in the comparisons. The advantage is that this method shows that the entire disease progression are close, and not just a single time point. Thus the biosimilarity comparison is more stringent, but yet can have better statistical properties than the traditional approach, including smaller sample size. A motivating example is provided.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.