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Statistical Methods in Biomarker and Early Clinical Development

  • Book
  • © 2019

Overview

Editors:
  1. Liang Fang

    1. MyoKardia Inc., South San Francisco, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Cheng Su

    1. BioMarin Pharmaceutical Inc., San Rafael, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Presents statistical methods in early clinical drug and biomarker development in one convenient volume
  • Includes chapters written by experts in the pharmaceutical industry
  • Emphasizes practical applications by highlighting real-world examples, state-of-the-art developments, and innovative methods

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Predictive Subgroup/Biomarker Identification and Machine Learning Methods

    • M. Man, T. S. Nguyen, C. Battioui, G. Mi
    Pages 1-22

  3. Characterize and Dichotomize a Continuous Biomarker

    • G. Mi, W. Li, T. S. Nguyen
    Pages 23-38

  4. Surrogate Biomarkers

    • Yongming Qu
    Pages 39-52

  5. Innovative Designs for Biomarker-Guided Trials

    • Jing Wang, Mark Chang
    Pages 53-65

  6. Statistical Considerations in the Development of Companion Diagnostic Device

    • Meijuan Li, Rui Tang
    Pages 67-86

  7. Biomarker Assay Development, Qualification, and Validation

    • Guang Chen, Shuguang Huang, Winnie Weng, Cheng Su
    Pages 87-115

  8. Validation of Genomic-Based Assay

    • Yoonha Choi, Jing Huang
    Pages 117-136

  9. Clinical Application of Molecular Features in Therapeutic Selection and Drug Development

    • Ruixiao Lu, Rui Tang, Jing Huang
    Pages 137-166

  10. Big Data, Real-World Data, and Machine Learning

    • Jing Lu, Yangyang Hao, Jing Huang, Su Yeon Kim
    Pages 167-195

  11. Design and Analysis of Clinical Pharmacology Studies

    • Winnie Weng, Liang Fang
    Pages 197-220

  12. Statistical Considerations in Proof-of-Concept Studies

    • Laurence Colin, Brian Smith
    Pages 221-245

  13. Safety in Early Phase Studies

    • Laurence Colin, Brian Smith
    Pages 247-274

  14. Statistical Evaluation of QT/QTc Interval Prolongation

    • Liang Fang, Winnie Weng, Lu Wang, Xiaoru Wu
    Pages 275-299

  15. Phase II Dose Finding

    • Qiqi Deng, Naitee Ting
    Pages 301-320

  16. Pharmacometrics

    • Alan H. Hartford, Kenneth G. Kowalski
    Pages 321-348
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Keywords

About this book

This contributed volume offers a much-needed overview of the statistical methods in early clinical drug and biomarker development. Chapters are written by expert statisticians with extensive experience in the pharmaceutical industry and regulatory agencies. Because of this, the data presented is often accompanied by real world case studies, which will help make examples more tangible for readers. The many applications of statistics in drug development are covered in detail, making this volume a must-have reference.


Biomarker development and early clinical development are the two critical areas on which the book focuses. By having the two sections of the book dedicated to each of these topics, readers will have a more complete understanding of how applying statistical methods to early drug development can help identify the right drug for the right patient at the right dose. Also presented are exciting applications of machine learning and statistical modeling, along with innovative methods and state-of-the-art advances, making this a timely and practical resource.


This volume is ideal for statisticians, researchers, and professionals interested in pharmaceutical research and development. Readers should be familiar with the fundamentals of statistics and clinical trials.

Editors and Affiliations

  • MyoKardia Inc., South San Francisco, USA

    Liang Fang

  • BioMarin Pharmaceutical Inc., San Rafael, USA

    Cheng Su

About the editors

​Liang Fang is an Executive Director and Head of Biostatistics in MyoKardia Inc. His research interests include statistical applications in drug development, precision medicine, and digital health.

Cheng Su is an Executive Director of Data Science & Analytics at BioMarin, Inc. His research interests include statistical applications and tool development in drug discovery, biomarkers, clinical trials design, risk based monitoring, mobile health and big data.

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