Statistical Methods in Biomarker and Early Clinical Development

1. Front Matter

   Pages i-xii

   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

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.

• Biomarkers
• Biomarker testing
• Biomarker Development
• Biomarker data
• Biomarker book
• Early clinical development
• Predictive biomarker
• Drug development statistics
• Biostatistics
• Personalized Medicine
• Precision Medicine
• Translational Medicine
• Clinical Trials
• Pharmaceutical Development
• Machine learning medicine
• Clinical pharmacology
• Clinical pharmacology in drug development
• Pharmacodynamics

• MyoKardia Inc., South San Francisco, USA

  Liang Fang

• BioMarin Pharmaceutical Inc., San Rafael, USA

  Cheng Su

​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.

Policies and ethics