Case Studies in Innovative Clinical Trials (eBook, ePUB)

Redaktion: Broglio, Kristine; Yu, Binbing

• Format: ePub

Produktbeschreibung

Advances in technology and data infrastructure call for innovations in clinical trial design. This book will be an important showcase of the potential for these innovative designs in modern drug development and will be an important resource to guide those who wish to undertake them for themselves.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 302
• Erscheinungstermin: 27. November 2023
• Englisch
• ISBN-13: 9781000987249
• Artikelnr.: 69227252

Autorenporträt

Binbing Yu is a Senior Director in the Oncology Statistical Innovation group at AstraZeneca. He serves as the statistical expert across the whole spectrum of drug R&D, including drug discovery, clinical trials, operation and manufacturing, clinical pharmacology, oncology medical affairs and post-marketing surveillance. He obtained his PhD in Statistics from the George Washington University. His primary research interests are clinical trial design and analysis, cancer epidemiology, observational studies, PKPD modelling and Bayesian analysis. He has published three books on immunogenicity, cure modelling and RWD/RWE. Kristine Broglio is a Statistical Science Director in the Astrazeneca Oncology Statistical Innovation group with interests in adaptive clinical trials and Bayesian statistics. She earned an MS in Biostatistics from the University of Washington and joined the University of Texas M.D. Anderson Cancer Center where she specialized in applied statistical analysis relating to the diagnosis, treatment, and long-term outcomes of breast cancer. Later at Berry Consultants, she led the design, execution, and analysis of well over 100 Bayesian adaptive and complex clinical trials. Ms Broglio is a member of numerous cross-industry working groups through the ASA and DIA and has contributed to over 120 papers to the medical and statistical literature.

Inhaltsangabe

1. Review of Advances in Complex Innovative Clinical Trials Part 1. Case
Studies in Adaptive Trial Design 2. ANBL1531: The Children's Oncology Group
(COG) Experience using a Bayesian Approach 3. Being SMART about Behavioral
Intervention Trials for the Management of Chronic Conditions: Lessons
Learned using Sequential Multiple Assignment Randomized Trials (SMARTs) 4.
Adapting the Primary Endpoint of TULIP 2 - A Hybrid Bayesian-Frequentist
Framework to Incorporate Relevant Information from Prior Studies in
Confirmatory Trials in SLE Patients 5. Unblinded Sample Size Re-Estimation:
A Case Study. 6. Evaluation of a Method for Sample Size Re-Estimation for a
Confirmatory Phase 3 Clinical Trial to Compare Two Test Treatments to
Control 7. Hierarchical Composite Endpoints in COVID-19: The DARE-19 Trial
Part 2. Case Studies in Other Innovative Clinical Trial Methods 8. Deep
Learning Constructed Statistics with Application to Adaptive Designs for
Clinical Trials 9. Predicting Phase III Results by Incorporating Historical
Data using Bayesian Additive Regression Trees (BART) Extensions 10.
Unleashing the Power of Digital Tools in Clinical Trials: A Systematic
Review of Digital Measurement Considerations from Implementation Experience
11. Use of Surrogate Endpoints in Clinical Development 12. Advanced
Clinical Trial Design that Utilizes Real-World Evidence Part 3. Case
Studies in Regulatory and Operational Considerations 13. Case Studies in
Statistical Safety 14. Bayesian Dynamic Borrowing and Regulatory
Considerations 15. Case Studies in CID and Model-Informed Drug Design
(MIDD) Part 4. Case Studies in Collaboration and Communication 16. Project
Management in Innovative Clinical Trial Design