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Interface between Regulation and Statistics in Drug Development [Kõva köide]

, , (Pfizer Inc., New York)
  • Formaat: Hardback, 146 pages, kõrgus x laius: 234x156 mm, kaal: 381 g, 1 Tables, black and white; 9 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Biostatistics Series
  • Ilmumisaeg: 12-Nov-2020
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 036749048X
  • ISBN-13: 9780367490485
Teised raamatud teemal:
Interface between Regulation and Statistics in Drug DevelopmentSuurem pilt
  • Formaat: Hardback, 146 pages, kõrgus x laius: 234x156 mm, kaal: 381 g, 1 Tables, black and white; 9 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Biostatistics Series
  • Ilmumisaeg: 12-Nov-2020
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 036749048X
  • ISBN-13: 9780367490485
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780367490485.html
Märksõnad:
"The book is designed to be accessible to readers with an intermediate knowledge of statistics, and can be a useful resource to statisticians, medical researchers, and regulatory personnel in drug development, as well as graduate students in the health sciences. The authors' decades of experience in the pharmaceutical industry and academia, and extensive regulatory experience, comes through in the many examples throughout the book"--

With the critical role of statistics in the design, conduct, analysis and reporting of clinical trials or observational studies intended for regulatory purposes, numerous guidelines have been issued by regulatory authorities around the world focusing on statistical issues related to drug development. However, the available literature on this important topic is sporadic, and often not readily accessible to drug developers or regulatory personnel. This book provides a systematic exposition of the interplay between the two disciplines, including emerging themes pertaining to the acceleration of the development of pharmaceutical medicines to serve patients with unmet needs.

Features:

  • Regulatory and statistical interactions throughout the drug development continuum

  • The critical role of the statistician in relation to the changing regulatory and healthcare landscapes

  • Statistical issues that commonly arise in the course of drug development and regulatory interactions

    • Trending topics in drug development, with emphasis on current regulatory thinking and the associated challenges and opportunities

    • The book is designed to be accessible to readers with an intermediate knowledge of statistics, and can be a useful resource to statisticians, medical researchers, and regulatory personnel in drug development, as well as graduate students in the health sciences. The authors’ decades of experience in the pharmaceutical industry and academia, and extensive regulatory experience, comes through in the many examples throughout the book.

    List of figures
    		xi
    List of abbreviations
    		xiii
    Authors' Disclosure xvii
    Acknowledgment xix
    Preface xxi
    About the Authors xxv
    Chapter 1 Fundamental Principles of Clinical Trials
    		1(22)
    1.1 Introduction
    		1(4)
    1.2 General Statistical Considerations
    		5(4)
    1.2.1 Statistical Analysis Plan
    		5(1)
    1.2.2 Trial Design
    		6(1)
    1.2.3 Randomization and Blinding
    		7(1)
    1.2.4 Statistical Methodology
    		7(2)
    1.2.5 Reporting and Interpretation of Study Results
    		9(1)
    1.2.6 Data Quality and Software Validity
    		9(1)
    1.3 Evolving Roles Of The Statistician In Drug Development
    		9(5)
    1.4 Potential Statistical Issues In Regulatory Review
    		14(3)
    1.4.1 Data Quality
    		14(1)
    1.4.2 Endpoint Definition
    		14(1)
    1.4.3 Design and Analysis Issues
    		15(1)
    1.4.4 Evaluation of Safety
    		16(1)
    1.4.5 Analysis Populations and Subgroups
    		16(1)
    1.4.6 Assessing Interpretation and Reliability of Results
    		17(1)
    1.5 Concluding Remarks
    		17(6)
    Chapter 2 Selected Statistical Topics of Regulatory_Importance
    		23(74)
    2.1 Introduction
    		23(1)
    2.2 Multiplicity
    		24(6)
    2.2.1 Multiple Endpoints
    		24(4)
    2.2.2 Multiple Testing Over the Course of the Study
    		28(2)
    2.3 Missing Values And Estimands
    		30(11)
    2.3.1 General Considerations
    		30(2)
    2.3.2 Missingness Mechanisms
    		32(2)
    2.3.3 Approaches for Missing Data
    		34(2)
    2.3.4 Sensitivity Analyses
    		36(1)
    2.3.5 Estimands and Other Recent Regulatory Developments
    		37(3)
    2.3.6 Concluding Remarks
    		40(1)
    2.4 Non-Inferiority Study
    		41(9)
    2.4.1 Efficacy Objective
    		41(1)
    2.4.2 Non-inferiority Hypothesis / Non-inferiority Margin
    		42(1)
    2.4.3 Determination of NIM
    		43(1)
    2.4.4 Example: FDA Guidance Document
    		43(1)
    2.4.5 Implications of Choice of NIM
    		44(1)
    2.4.6 Strength of a Non-inferiority Study
    		45(1)
    2.4.7 Synthesis Method for Non-inferiority
    		46(1)
    2.4.8 Summary Points
    		47(1)
    2.4.9 Non-inferiority Study with a Safety Objective
    		47(2)
    2.4.10 Summary Points
    		49(1)
    2.5 Innovative Trial Designs
    		50(10)
    2.5.1 Adaptive Designs
    		50(1)
    2.5.2 Adaptive Randomization
    		50(1)
    2.5.3 Sample Size Reestimation
    		51(2)
    2.5.4 Sequential Designs
    		53(1)
    2.5.5 Adaptive Designs for Dose and Treatment Selection
    		54(1)
    2.5.6 Adaptive Enrichment Designs
    		55(1)
    2.5.7 Master Protocols
    		55(1)
    2.5.7.1 Basket Trials
    		56(2)
    2.5.7.2 Umbrella Trials
    		58(1)
    2.5.7.3 Platform Trials
    		58(1)
    2.5.7.4 Regulatory and Operational Considerations with Novel Trials
    		59(1)
    2.6 Bayesian Analysis In A Regulatory Framework
    		60(6)
    2.6.1 Introduction
    		60(2)
    2.6.2 Potential Areas of Application
    		62(2)
    2.6.3 Regulatory Considerations
    		64(2)
    2.6.4 Challenges with Bayesian Statistics
    		66(1)
    2.6.5 Concluding Remarks
    		66(1)
    2.7 Surrogate Endpoints And Biomarkers
    		66(7)
    2.7.1 Introduction
    		66(2)
    2.7.2 Statistical Considerations
    		68(3)
    2.7.3 Regulatory Considerations
    		71(1)
    2.7.4 Concluding Remarks
    		72(1)
    2.8 Subgroup Analyses
    		73(5)
    2.8.1 Introduction
    		73(1)
    2.8.2 Subgroup Analyses in the Traditional Confirmatory Clinical-Trial Setting
    		73(1)
    2.8.3 Statistical Approaches
    		74(1)
    2.8.4 Reporting and Interpretation of Subgroup Results
    		75(1)
    2.8.5 Subgroup Analyses in the Changing Clinical-Trial and Regulatory Setting
    		76(1)
    2.8.6 Conclusion
    		77(1)
    2.9 Benefit-Risk Assessment
    		78(19)
    2.9.1 Introduction
    		78(1)
    2.9.2 Methodological Considerations in Benefit-Risk Analysis
    		79(2)
    2.9.3 Regulatory Perspectives
    		81(3)
    2.9.4 Benefit-Risk in Health-Technology Assessment
    		84(1)
    2.9.5 Concluding Remarks
    		84(13)
    Chapter 3 Statistical Engagement in Regulatory Interactions
    		97(14)
    3.1 Introduction
    		97(1)
    3.2 Internal Behaviors
    		98(1)
    3.3 Data Monitoring Committee
    		99(2)
    3.4 Regulatory Meetings And Advisory Committee Meetings
    		101(5)
    3.5 Statistical Role In Promotional Material And Medical Communication
    		106(2)
    3.6 Concluding Remarks
    		108(3)
    Chapter 4 Emerging Topics
    		111(32)
    4.1 The Use Of RWE To Support Licensing And Label Enhancement
    		111(9)
    4.1.1 Introduction
    		111(2)
    4.1.2 Methodological and Operational Considerations
    		113(4)
    4.1.3 Current Regulatory Landscape
    		117(2)
    4.1.4 Concluding Remarks
    		119(1)
    4.2 Patient-Reported Outcomes In Regulatory Settings
    		120(9)
    4.2.1 Introduction
    		120(1)
    4.2.2 Development and Validation of PRO Instruments
    		121(2)
    4.2.3 Statistical Considerations
    		123(2)
    4.2.4 Regulatory Considerations
    		125(3)
    4.2.5 Concluding Remarks
    		128(1)
    4.3 Artificial Intelligence And Modern Analytics In Regulatory Settings
    		129(14)
    4.3.1 Introduction
    		129(2)
    4.3.2 AI in Drug Development
    		131(1)
    4.3.3 Regulatory Experience with Machine Learning and Artificial Intelligence
    		132(1)
    4.3.4 Concluding Remarks
    		133(10)
    Index 143
    Demissie Alemayehu, PhD, is Vice President and Head of the Statistical Research and Data Science Center at Pfizer Inc. He is a Fellow of the American Statistical Association, has published widely, and has served on the editorial boards of major journals, including the "Journal of the American Statistical Association" and the "Journal of Nonparametric Statistics." Additionally, he has been on the faculties of both Columbia University and Western Michigan University. He has co-authored a monograph entitled, "Patient-Reported Outcomes: Measurement, Implementation and Interpretation," and co-edited another, "Statistical Topics in Health Economics and Outcome Research" both published by Chapman & Hall/CRC Press.

    Birol Emir, PhD, is Senior Director and Statistics Lead of Real-World Evidence (RWE) at Pfizer Inc. In addition, Dr. Emir has served as Adjunct Professor of Statistics and Lecturer at Columbia University in New York and as an External PhD Committee Member, Graduate School of Arts and Sciences, Rutgers, The State University of New Jersey. Recently, his primary focuses have been on big data, predictive modelling and genomic data analysis. He has numerous publications in refereed journals, and he has co-edited "Statistical Topics in Health Economics and Outcome Research" published by Chapman & Hall/CRC Press. He has taught many short courses and has given several invited presentations.

    Michael Gaffney, PhD, is Vice President, Statistics at Pfizer, and received his Ph.D. from New York University School of Environmental Medicine with his dissertation in the area of multistage model of cancer induction. Dr. Gaffney has spent his 43-year career in pharmaceutical research concentrating in the areas of design and analysis of clinical trials and regulatory interaction for drug approval and product defense. He has interacted with FDA, EMA, MHRA and regulators in Canada and Japan on over 25 distinct regulatory approvals and product issues in many therapeutic areas. Dr. Gaffney has published 40 peer-reviewed articles and presented at numerous scientific meetings in diverse areas of modelling cancer induction, variance components, harmonic regression, factor analysis, propensity scores, meta-analysis, large safety trials and sample size re-estimation. Dr. Gaffney was recently a member of the Council for International Organizations of Medical Sciences (CIOMS) X committee and was a co-author of, CIOMS X: Evidence Synthesis and Meta-Analysis for Drug Safety.