Statistical and Computational Challenges in Precision Medicine

November 07 - 09, 2018

Content

Overview

Poster:

SW11.7-9.18_poster.pdf

Organizers:

Singdhansu Chatterjee	University of Minnesota, Twin Cities
Feifang Hu	George Washington University
Marianthi Markatou	University at Buffalo (SUNY)
David Vock	University of Minnesota, Twin Cities
Lan Wang	University of Minnesota, Twin Cities

Precision medicine aims to use a patient's specific characteristics, such as genetic information, health history, environmental exposure, needs and preferences, to guide effective drug discovery and treatment intervention. Many challenging statistical problems arise in precision medicine. The workshop will bring together experts from academia and industry to exchange new research ideas on developing accurate and reliable statistical and machine learning tools for estimating the optimal treatment regimes.

Schedule

Wednesday, November 07, 2018

8:30 am - 9:00 am	Coffee and registration	Lind 400
9:00 am - 9:20 am	Welcome and introduction	Lind 305
9:20 am - 10:10 am	How good is your selected subgroup? Xuming He (University of Michigan)	Lind 305
10:10 am - 10:40 am	A Bayesian Imputation Approach to Optimizing Dynamic Treatment Regimes Thomas Murray (University of Minnesota, Twin Cities)	Lind 305
10:40 am - 11:00 am	Break	Lind 400
11:00 am - 11:30 am	Optimal treatment and timing of routine surveillance in children after allogeneic hematopoietic cell transplantaion Zhezhen Jin (Columbia University)	Lind 305
11:30 am - 12:00 pm	Thinking Causally About High-Dimensional Databases Debashis Ghosh (University of Colorado Denver)	Lind 305
12:00 pm - 2:00 pm	Lunch
2:00 pm - 2:30 pm	Estimating Causal (Personalized) Effects within Regulatory Tobacco Randomized Controlled Trials David Vock (University of Minnesota, Twin Cities)	Lind 305
2:30 pm - 3:00 pm	Analysis of implantable cardiac device diagnostics to tailor management of heart failure Tracy Bergemann (Medtronic)	Lind 305
3:00 pm - 3:30 pm	Digital Health and Big Data for Drug Development Ray Liu (Takeda Pharmaceuticals Inc.)	Lind 305
3:30 pm - 4:00 pm	Break	Lind 400
4:00 pm - 4:30 pm	Selection of the Optimal Personalized Treatment from Multiple Treatments with Multivariate Outcome Measures Somnath Datta (University of Florida)	Lind 305
4:30 pm - 5:00 pm	Matched Learning for Optimizing Individualized Treatment Strategies Using Electronic Health Records Yuanjia Wang (Columbia University)	Lind 305
5:00 pm - 6:00 pm	Poster session and reception Zhengling Qi (University of North Carolina, Chapel Hill)	Lind 400

Thursday, November 08, 2018

8:30 am - 9:00 am	Coffee	Lind 400
9:00 am - 9:50 am	Keynote Eric Laber (North Carolina State University)	Lind 305
9:50 am - 10:20 am	Clustering Mixed-Type Data Marianthi Markatou (University at Buffalo (SUNY))	Lind 305
10:20 am - 10:40 am	Break	Lind 400
10:40 am - 11:10 am	Group and Individual Non-Gaussian Components Analysis David S. Matteson (Cornell University)	Lind 305
11:10 am - 11:40 am	Quantile Regression in Genetic studies Ying Wei (Columbia University)	Lind 305
11:40 am - 12:10 pm	Learning Multi-relations in Biomedical Networks and Tensors Rui Kuang (University of Minnesota, Twin Cities)	Lind 305
12:10 pm - 2:00 pm	Lunch
2:00 pm - 2:30 pm	Adaptive testing on a high-dimensional parameter with application to precision medicine Wei Pan (University of Minnesota, Twin Cities)	Lind 305
2:30 pm - 3:00 pm	Statistical Inference of Covariate-Adjusted Randomized Experiment Feifang Hu (George Washington University)	Lind 305
3:00 pm - 3:30 pm	Estimating and testing targeted mediation effect in the presence of high-dimensional mediators Lei Liu (Washington University School of Medicine)	Lind 305
3:30 pm - 3:40 pm	Group photo	Lind 305
3:40 pm - 4:00 pm	Break	Lind 400
4:00 pm - 4:30 pm	HASS: Hybrid Algorithm for Subgroup Search via ADMM and EM Algorithms Peter Song (University of Michigan)	Lind 305
4:30 pm - 5:00 pm	Quantile-optimal Treatment Regimes with Censored Data Lan Wang (University of Minnesota, Twin Cities)	Lind 305
5:00 pm - 5:30 pm	Statistical Analysis of SMART Studies via Artifcial Randomization Abdus Wahed (University of Pittsburgh)	Lind 305

Friday, November 09, 2018

8:30 am - 9:00 am	Coffee	Lind 400
9:00 am - 9:50 am	Personalized risk prediction using longitudinal data: Applications in obstetrics and cancer Paul Albert (National Cancer Institute)	Lind 305
9:50 am - 10:20 am	Outcome-Weighted Learning for Personalized Medicine with Multiple Treatment Options Donglin Zeng (University of North Carolina, Chapel Hill)	Lind 305
10:20 am - 10:40 am	Break	Lind 400
10:40 am - 11:10 am	C-learning: A New Classification Framework to Estimate Optimal Dynamic Treatment Regimes Min Zhang (University of Michigan)	Lind 305
11:10 am - 11:40 am	Efficient Discovery of Heterogeneous Treatment Effects via Anomalous Pattern Detection Edward McFowland (University of Minnesota, Twin Cities)	Lind 305
11:40 am - 12:10 pm	A novel method to identify and prioritize drugs for an individual (N=1) based on clinical and multi-omics data Krishna Kalari (Mayo Clinic)

Participants

Name	Department	Affiliation
Paul Albert	Biostatistics Branch	National Cancer Institute
Sakshi Arya	School of Statistics	University of Minnesota, Twin Cities
Tracy Bergemann	Clinical Statistics	Medtronic
Jeffrey Boatman	Division of Biostatistics	University of Minnesota, Twin Cities
Evan Bollig	Minnesota Supercomputing Institute	University of Minnesota, Twin Cities
Irfan Bulu		UnitedHealth Group
Singdhansu Chatterjee	School of Statisitics	University of Minnesota, Twin Cities
Jesse Clifton	Department of Statistics	North Carolina State University
Somnath Datta	Department of Biostatistics	University of Florida
Christopher Desjardins	Center for Applied Research and Educational Improvement	University of Minnesota, Twin Cities
Debashis Ghosh	Department of Biostatistics	University of Colorado Denver
Birgit Grund	School of Statistics	University of Minnesota, Twin Cities
Yinglong Guo	Department of Research and Development	UnitedHealth Group
Qie He	Department of Industrial and Systems Engineering	University of Minnesota, Twin Cities
Xuming He	Department of Statistics	University of Michigan
Feifang Hu	Department of Statistics	George Washington University
Zhezhen Jin	Department of Biostatistics	Columbia University
Krishna Kalari	Department of Biomedical Statistics and Informatics	Mayo Clinic
Rui Kuang	Department of Computer Science and Engineering	University of Minnesota, Twin Cities
Eric Laber	Department of Statistics	North Carolina State University
Xiaoou Li	School of Statistics	University of Minnesota
Zhuliu Li	Department of Computer Science and Engineering	University of Minnesota
Lei Liu	Division of Biostatistics	Washington University School of Medicine
Ray Liu		Takeda Pharmaceuticals Inc.
Gregory Lyng		UnitedHealth Group
Marianthi Markatou	Department of Biostatistics	University at Buffalo (SUNY)
David S. Matteson	Department of Statistical Science and Social Statistics	Cornell University
Edward McFowland	Carlson School of Management	University of Minnesota, Twin Cities
Weibin Mo	Department of Statistics and Operations Research	University of North Carolina, Chapel Hill
Thomas Murray	Department of Biostatistics	University of Minnesota, Twin Cities
Wei Pan	Division of Biostatistics	University of Minnesota, Twin Cities
Raphael Petegrosso	Department of Computer Science and Engineering	University of Minnesota
Yevgeniy Ptukhin	Department of Mathematical Sciences	Worcester Polytechnic Institute
Zhengling Qi	Department of Statistics and Operations Research	University of North Carolina, Chapel Hill
Sheng Ren	Department of Research and Development	UnitedHealth Group
Mahsa Salsabili	Department of Pharmaceutical Care & Health Systems	University of Minnesota, Twin Cities
Sanhita Sengupta	School of Statistics	University of Minnesota, Twin Cities
Peter Song	Department of Biostatistics	University of Michigan
Ben Strasser	Department of Mathematics	University of Minnesota, Twin Cities
Xiaojia Tang	Department of Health Sciences Research	Mayo Clinic
Julia Udell	Center for Individualized Medicine	Mayo Clinic
Sithara Vivek	Department of Laboratory Medicne and Pathology	University of Minnesota
David Vock	School of Public Health	University of Minnesota, Twin Cities
Abdus Wahed	Department of Biostatistics	University of Pittsburgh
Lan Wang	School of Statistics	University of Minnesota, Twin Cities
Yuanjia Wang	Department of Biostatistics	Columbia University
Ying Wei	Department of Biostatistics	Columbia University
Yunan Wu	School of Statistics	University of Minnesota, Twin Cities
Donglin Zeng	Department of Biostatistics	University of North Carolina, Chapel Hill
Min Zhang	Department of Biostatistics	University of Michigan
Yiwang Zhou	Department of Biostatistics	University of Michigan - School of Public Health