Contemporary Biostatistics with Biopharmaceutical Applications

Part I Biostatistical Methodology.- Dimension Reduction in High Dimensional Multivariate Time Series Analysis.- Multi-Panel Kendall Plot Applied to Measuring Dependence.- Flexible Optimal Design Strategies.- A Multivariate Spatial Modelling Approach with Nonparametric Cross-covariogram.- A Deterministic Global Optimization Method for Variational Inference.- Part II Statistical Genetics and Bioinformatics.- Subgroup identification with latent Dirichlet allocation.- Dictionary learning based genotype imputation to improve power for association testing.- Integrating Transcriptional Time Lag Information into Gene Regulatory Network Construction.- Optimal experimental designs for fMRI when the model matrix is uncertain.- On Exact and Approximate Distributions of K-homopolymer for iid and Markov Dependent DNA Sequences.- Part III Regulatory Statistics.- Utilizing Seamless Adaptive Designs for NASH Clinical Trials.- A Bayesian Non-inferiority Design with Companion Constancy Test in Active Controlled Trials.- A Study Design for Utilizing External Data to Augment the Control in a Randomized Controlled Trial.- Some thoughts in designing a Bayesian study: From a statistical reviewer's perspective.- On Weighted Performance Goals in Medical Device Single-Arm Clinical Studies.- Part IV Biopharmaceutical Research and Applications.-Current Status Data in the Presence of a Terminal Event.- Seamless Phase 2/3 Study Design with an Oncology Example.- A Bayesian meta-analysis method for estimating risk difference of rare events.- Comparison of multi-arm multi-stage design and adaptive randomization in platform clinical trials.- A Calibrated Power Prior Approach to Borrow Information from Historical Data with Application.- A Gatekeeping Test in a Group Sequential Design with Multiple Interim Looks.- Application of Bayesian Methods in Oncology Dose Escalation Studies with Late Onset Toxicity.- Bayesian hierarchical model estimation and comparison of immunogenicity assay

About the Editors:

Lanju Zhang is Director in Statistics and Research Fellow at the Department of Data and Statistical Sciences at AbbVie. He is leading a group providing statistical support to emerging immunology clinical programs. Prior to that, he was Head of Nonclinical Statistical Group at Abbvie and MedImmune. His research interests include adaptive design, multi-region clinical trials, real world evidence, and nonclinical statistics. He has published two books (both with Springer) and more than 30 papers. He is an associate editor of Journal of Biopharmaceutical Statistics. He received his PhD in Statistics in 2005 from University of Maryland Baltimore County.

Ding-Geng Chen is a Fellow of American Statistical Association and currently the Wallace H. Kuralt Distinguished Professor at the University of North Carolina at Chapel Hill. He was a professor at the University of Rochester and the Karl E. Peace Endowed Eminent Scholar Chairin Biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in Monte-Carlo simulations, clinical trial biostatistics and public health statistics. Professor Chen has more than 150 referred professional publications and co-authored and co-edited 18 books on clinical trial methodology, meta-analysis and public health applications and he has been invited nationally and internationally to give speeches on his research.

Hongmei Jiang is an associate professor of statistics at Northwestern University. Her current research focuses on developing statistical methods and computational algorithms to analyze and understand the massive amount of data generated by high throughput biological technologies, such as microarray and next generation sequencing technologies. She has published over 40 research articles in statistics and biostatistics research fields. She was the