Chin Adaptive and Flexible Clinical Trials

Erscheinungsjahr 2012
ISBN: 978-1-4398-3833-4
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 198 Seiten

Adaptive clinical trial designs, unlike traditional fixed clinical trial designs, enable modification of studies in response to the data generated in the course of the trial. This often results in studies that are substantially faster, more efficient, and more powerful. Recent developments in web-based real-time data entry and advances in statistical methods have made adaptive clinical trials much more popular because they have become both more practical and attractive. However, there is paucity of resources that explain the mathematical framework and the practical considerations for adaptive designs without the use of highly technical statistical jargon.
Suitable for readers in academia, industry, and government involved in drug development, Adaptive and Flexible Clinical Trials is the first book that comprehensively explains all essential aspects of adaptive clinical trials. Written in an easy-to-understand style aimed at clinicians and other non-statisticians, this book focuses not on the statistical details, but rather on the application of statistical concepts for adaptive clinical trials. Utilizing concrete examples, the book thoroughly explains the design, conduct, and analysis of adaptive and flexible clinical trials, allowing readers to select and design the appropriate trial designs from a conceptual perspective. From basic theory to real-life practical issues, it covers all aspects of adaptive and flexible clinical trials, including regulatory issues, interim analysis, adaptive dosing, and sequential designs.

Zielgruppe

Physicians, clinicians, researchers, and practitioners in clinical trials.

Autoren/Hrsg.

Chin, Richard

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien

Inhaltsverzeichnis

Background
Introduction
Definition and History of Traditional Clinical Trials
Definition of Adaptive Clinical Trial
Precursors to Modern Adaptive Clinical Trials
New Enabling Technologies and Other Requirements for Adaptive Trials
Rationale for Adaptive Clinical Trials
Learn and Confirm
Classification and Terminology of Adaptive Clinical Studies
Non-Adaptive Study Designs
Limitations of Adaptive Clinical Trials
Performance Criteria for Well Designed Clinical Trials
Evolving Regulatory Environment for Adaptive Clinical Trials
Regulatory Guidance from the FDA
References

Background: Conventional Statistics
Basic Statistics
Statistical Schools
Frequentist Method
Bayesian Method
Likelihood Method
Other Schools
Descriptive Statistics
Inferential Statistics
Comparative Statistics
Hypothesis Testing
Null Hypothesis and Standard of Proof in Clinical Trials
Example of Inference and Hypothesis Testing
Statistical Tests and Choice of Statistical Test
Examples of Statistical Tests
Fundamental Statistical Assumptions

Statistics Used in Adaptive Clinical Trials
Introduction
Preserving the Alpha
What Is Alpha?
Misconception about p Values
Splitting the Alpha
Methodologies for Allocating Alpha
Evolution of Adaptive Analytic Methods: Interim Analysis
Adaptive Methods
Limitations of Adaptive Statistical Techniques
Bayesian Approach
Simulations and Modeling
The FDA’s Stance on Adaptive Techniques
References

Specific Requirements for Adaptive Trials
Requirements for Endpoints in Adaptive Studies
Surrogates and Biomarkers
Practical Requirements

Adaptive Randomization and Allocation
Traditional Fixed Allocation
Simple Randomization
Restricted and Blocked Randomization
Stratified, Nested, and Similar Randomization
Balancing (Covariate) Adaptive Randomization
Response (Outcome) Adaptive Randomization
Combination and Multimodal Randomization
Bayesian Randomization
Adaptation of Inclusion and Exclusion Criteria Based on Blinded Data
Patient Enrichment Adaptations

Sample Size Reestimation
Background
Sample Size Reestimation Based on Blinded Data
Sample Size Reestimation Based on Unblinded Data
Adjustment in Follow-Up Time
Internal Pilot Studies
Additional Rules
References

Traditional Dosing
Introduction
Definitions and Objectives of Dose Selection
Issues
Pharmacokinetics
Factors Affecting Pharmacokinetics
Dose–Response Curves
Types of Dosing
Traditional Dose-Escalation and Dose-Ranging Studies

Adaptive Dosing
Adaptive Dose Finding
Phase I Studies
3 + 3 and Related Designs
Continual Reassessment Method
Dose Escalation with Overdose Control
Stochastic Approximation Methods
Summary of Single-Parameter Models
Additional Models and Methods
Dose Adaptation in a Pivotal Study
Changes in Concomitant Medications and Procedures
References

Interim Analysis and Adaptive Termination of Study and Study Arms
Overview
Data and Safety Monitoring Boards
Stopping Rules
Individual Sequential Designs
Group Sequential Designs
References

Adaptive Changes in Study Design and Decision Rules
Overview
Changes to Follow-Up Period
Flexible Designs
Changing the Endpoints and Hypothesis
Changes to Test Statistic or Analysis
References

Seamless Designs and Adaptive Clinical Trial Conduct
Seamless Designs
Challenges in Adaptive Trials
Maintaining the Blind
Infrastructure and Operations
Adaptive Trial Protocols

Analysis and Interpretation of Results
General Issues in Interpretation of Clinical Trial Results
Interpretation of Adaptive Trial Results
Documentation of Trial Integrity
Statistics of Adaptive Trial Analysis
Summary
References
Index

Über Autor(innen)

Richard Chin, M.D. is the Chief Executive Officer of OneWorld Health, a nonprofit pharmaceutical company largely funded by the Bill and Melinda Gates Foundation, developing drugs for impoverished patients in the developing world. Previously, Dr. Chin held multiple senior positions in several biotechnology companies and has extensive expertise in drug development including 10 new drug registrations filings/launches and over 45 Investigational New Drug (IND) Applications. Some of the drugs he has overseen include Rituxan, Lucentis, Tysabri, TNKase, Raptiva, Xolair, Cathflo, Prialt, Protropin, Nutropin, Pulmo- zyme, Azactam, Maxipime, and Bapineuzumab, among others. Dr. Chin was named by Businessweek in 2006 as one of the youngest 99 public company CEOs in the United States. Dr. Chin earned his M.D. from Harvard and the equivalent of a J.D. from Oxford, where he studied as a Rhodes Scholar. Dr. Chin serves as Associate Professor at UCSF School of Medicine and was previously on the adjunct faculty at Stanford University School of Medicine.