|
KEYNOTE
SPEAKERS
|
|
The 120th president of the American Statistical Association, Dr. Ji-Hyun Lee, will give the ASA Presidential Address. Dr. Lee’s term begins on January 1, 2025, and her priority will be to build strong bridges both within and outside the ASA community. For more information on Dr. Lee, click here.
|
 |
|
|
|
|
|
|
The Keynote Speaker will be Dr. Daniel Lee of Zelus Analytics presenting on Sports Analytics using Bayesian Models. Daniel Lee co-created Stan, the open-source statistical modeling language. He has developed models for a wide range of applications including professional sports teams, vote share for U.S. elections, and clinical trials for cancer and rare disease. For more information on Zelus Analytics, click here.
|
 |
|
|
|
|
|
|
SHORT
COURSES
|
|
A Primer on Spatial Transcriptomics Analysis
Dr. Joon Sang Lee, Sanofi
Clinical success in drug discovery hinges on a deep understanding of disease biology and the mechanisms of drug action. Emerging spatial technologies can quantify hundreds of transcripts up to whole transcriptome at single-cell or near single-cell resolution without losing spatial information. These technologies now offer unprecedented insights into the diversity of cell types, states, their interactions and spatial organization of gene expression within tissues. This enables us to advance our understanding of disease and drug mechanism.
This course will provide a brief introduction to spatial transcriptomics technologies widely used in the pharmaceutical and biotech industries. We will discuss data pre- and post-processing, as well as in-depth spatial omics analyses such as the identification of spatial domains.
|
 |
|
|
|
|
|
|
Making Project Work Better with R
Dr. Max Kuhn, Posit
"I need to make sure that my future self isn't going to be mad at my present self." - Kjell Johnson
A nonclinical statistician often has many simultaneous data analysis projects. Some of these may have been handed to them and others might eventually be handed to someone else. What are good practices for organizing and maintaining the raw data, source files, results, and other artifacts when doing data analysis?
We’ll discuss some tools to organize your project work, painlessly write good R code, manage changes to code and data, write resilient project reports, and enable reproducibility. Participants should have some experience with R, Rmarkdown/Quarto, and have used the RStudio IDE.
|
 |
|
|
|
|
|
|
INVITED SPEAKERS
|
|
Chemistry, Manufacturing, and Controls
Common Statistical Issues During Regulatory Review
Dr. Jennifer Kirk and Dr. Chao Wang, FDA
|
|
|
|
Discovery / Biomarkers
Translating Lupus: Comparative Transcriptional Profiles of Preclinical Lupus Models and Their Relevance to Human Disease
Dr. Veavi (Ching-Yun) Chang, Eli Lilly and Company
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
Dr. Michael Li, Harvard Business School
|
|
|
|
Safety / Pharmacology
Challenges in early-stage drug safety predictions
Dr. Helena Geys, Janssen
Virtual Control Groups in Preclinical Drug Safety Assessment
Dr. Dingzhou (Dean) Li, Pfizer
Sample Size Reduction in Preclinical Experiments: A Bayesian Sequential Decision-Making Framework
Dr. Jizhou Kang, University of California, San Francisco
|
|
|
|
Data Sciences and Emerging Tools
Modern Tools to Meet the Challenges of Preclinical Translation to the Clinic
Dr. Steven Novick, Takeda
Differential Projection Pursuit on Flow Cytometry Data to Identify and Profile Immune Cells Compromised by Exposure to HIV
Dr. Davit Sargsyan, Janssen
Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research
Sam Parmar, Pfizer
|
|