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Statistical Methods in Biomarker and Early Clinical Development

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Statistical Methods in Biomarker and Early Clinical Development/ edited by Liang Fang, Cheng Su.
other author:	Fang, Liang.
Description:	XII, 348 p. 54 illus., 31 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-030-31503-0
ISBN:	9783030315030

Statistical Methods in Biomarker and Early Clinical Development
Statistical Methods in Biomarker and Early Clinical Development[electronic resource] /edited by Liang Fang, Cheng Su. - 1st ed. 2019. - XII, 348 p. 54 illus., 31 illus. in color.online resource.

Predictive Subgroup/Biomarker Identification and Machine Learning Methods -- Characterize and Dichotomize a Continuous Biomarker -- Surrogate Biomarkers -- Innovative Designs for Biomarker Guided Trials -- Statistical Considerations in the Development of Companion Diagnostic Device -- Biomarker Assay Development, Qualification and Validation -- Validation of Genomic Based Assay -- Clinical Application of Molecular Features in Therapeutic Selection and Drug Development -- Big data, real-world data, and machine learning -- Design and Analysis of Clinical Pharmacology Studies -- Statistical Considerations in Proof of Concept Studies -- Safety in Early Phase Studies -- Statistical Evaluation of QT/QTc Interval Prolongation -- Phase II Dose Finding -- Pharmacometrics.

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.

ISBN: 9783030315030

Standard No.: 10.1007/978-3-030-31503-0doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Statistical Methods in Biomarker and Early Clinical Development
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520 $a 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.
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