Activity Number:
|
251
- SPEED: Biopharmaceutical Methods and Application I, Part 2
|
Type:
|
Contributed
|
Date/Time:
|
Monday, July 29, 2019 : 2:00 PM to 2:45 PM
|
Sponsor:
|
Biopharmaceutical Section
|
Abstract #307611
|
|
Title:
|
Meta-Analysis of Longitudinal Preclinical Efficacy Screens
|
Author(s):
|
William Forrest* and Bruno Alicke and Magdalena Osinska and Shannon Ruppert and Michal Jakubczak and Pawel Piatkowski
|
Companies:
|
Genentech, Inc and Genentech and Genentech and Genentech and Roche and Roche
|
Keywords:
|
preclinical;
translational;
longitudinal;
GAMM;
meta-analysis;
software
|
Abstract:
|
Preclinical in vivo efficacy screens are commonly employed with aims such as rank ordering of candidate molecules, estimation of potency, or detection of synergy in combination therapies. A typical design is a one-way layout or dose-escalation study with multiple mice per group and repeated measures per animal, with regimen efficacy summarized at the group level. When regimens are tested repeatedly across many studies, researchers can investigate reproducibility of findings and sharpen estimates of efficacy by employing meta-analytic techniques more commonly found in assessments of clinical trials or epidemiology. We present a framework for such meta-analyses in preclinical oncology and illustrate with a case study a statistical workflow based on summarization of study group-level effects via generalized additive mixed models, followed by meta analytic aggregation of effects to learn across studies. Implementation and visualization of results are developed via extensions of open-source tools in the R language.
|
Authors who are presenting talks have a * after their name.