Nusrat Rabbee

Biomarker Analysis in Clinical Trials with R (eBook, ePUB)

• Format: ePub

Produktbeschreibung

The book offers practical guidance on how to incorporate biomarker data analysis in clinical trial studies. The book discusses the appropriate statistical methods for evaluating pharmacodynamic, predictive and surrogate biomarkers for delivering increased value in the drug development process.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 228
• Erscheinungstermin: 11. März 2020
• Englisch
• ISBN-13: 9780429766794
• Artikelnr.: 58789499

Autorenporträt

Nusrat Rabbee is a biostatistician and data scientist at Rabbee & Associates, where she creates innovative solutions to help companies accelerate drug and diagnostic development for patients. Her research interest lies in the intersection of data science and personalized medicine. She has extensive experience in bioinformatics, clinical statistics and high-dimensional data analyses. She has co-discovered the RLMM algorithm for genotyping Affymetrix SNP chips and co-invented a high-dimensional molecular signature for cancer. She has spent over 17 years in the pharmaceutical and diagnostics industry focusing on biomarker development. She has taught statistics at UC Berkeley for 4 years.

Inhaltsangabe

Section I Pharmacodynamic Biomarkers 1. Introduction 2. Toxicology Studies
3. Bioequivalence Studies 4. Cross-Sectional Profile of Pharmacodynamics
Biomarkers 5. Timecourse Profile of Pharmacodynamics Biomarkers 6.
Evaluating Multiple Biomarkers Section II Predictive Biomarkers 7.
Introduction 8. Operational Characteristics of Proof-of-Concept Trials with
Biomarker-Positive and -Negative Subgroups 9. A Framework for Testing
Biomarker Subgroups in Confirmatory Trials 10. Cutoff Determination of
Continuous Predictive Biomarker for a Biomarker-Treatment Interaction 11.
Cutoff Determination of Continuous Predictive Biomarker Using Group
Sequential Methodology 12. Adaptive Threshold Design 13. Adaptive Seamless
Design (ASD) Section III Surrogate Endpoints 14. Introduction 15.
Requirement # 1: Trial Level - Correlation Between Hazard Ratios in
Progression-Free Survival and Overall Survival Across Trials 16.
Requirement # 2: Individual Level - Assess the Correlation Between the
Surrogate and True Endpoints After Adjusting for Treatment (R2 indiv) 17.
Examining the Proportion of Treatment Effect in AIDS Clinical Trials 18.
Concluding Remarks Section IV Combining Multiple Biomarkers 19.
Introduction 20. Regression-Based Models 21. Tree-Based Models 22. Cluster
Analysis 23. Graphical Models Section V Biomarker Statistical Analysis Plan