Biostatistics in Biopharmaceutical Research and Development

Clinical Trial Analysis
2025
ISBN: 978-3-031-77325-9
Verlag: Springer

Buch, Englisch, 790 Seiten, Format (B × H): 155 mm x 235 mm

The Deming Conference on Applied Statistics has long been deemed an influential event in the biostatistics and biopharmaceutical profession. It provides learning experience on recent developments in statistical methodologies in biopharmaceutical applications and FDA regulations.

This book honors 80 years of contributions and dedication of the Deming Conference in biostatistics, and biopharmaceutical clinical trial methodology and applications. All chapters are contributed by world-class and prominent Deming speakers, who've contributed their cutting-edge research and developments to the community. This volume set covers Historical Milestones in Clinical Trial Design, FDA biopharmaceutical design guidance, and emerging development in Clinical Trial Design Methodology.

This book aims to booster research, education, and training in biostatistics and in biopharmaceutical research and development.

Zielgruppe

Research

Autoren/Hrsg.

Chen, Ding-Geng

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Public Health, Gesundheitsmanagement, Gesundheitsökonomie, Gesundheitspolitik
• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Bias and Randomization in Clinical Trials: 1980s – 2020s – 2060s.- The Markov Model for Survival Trials at 35 Years-Old.- Absolute Power Corrupts Absolutely: A Review of the Use of Unconditional Probabilities in the Planning of Clinical Trials.- Design of Clinical Trials with the Desirability of Outcome Ranking Methodology.- Benefit:Risk Assessments during Clinical Trials: A Prediction Approach Using the Desirability of Outcome Ranking (DOOR).- The Power of Integration: How the 2-in-1 Clinical Trial Design is Changing the Future of Drug Development.- A Unified Bayesian Decision Rule-Based Approach for Bayesian Design of Clinical Trials Using Historical Data.- Group Sequential Design Under Non-proportional Hazards: Methodologies and Examples.- Multiple Testing in Group Sequential Design.- Plan per-protocol (PP) causal inference analysis addressing intercurrent events following the targeted learning roadmap.- Maximum Tolerated Imbalance Randomization: Theory and Practice.- Response-adaptive randomization designs based on optimal allocation proportion.- Statistical Challenges in the Analysis of Biomarker Data.- Evaluating Predictive Accuracy of Prognostic Model for Censored Time-to-Event Data Analysis in Clinical Trials.- Statistical Methods for Accommodating Immortal Time: A Selective Review and Comparison.- Variable selection for partially functional additive Cox Model with interval-censored failure time data.- A Bayesian proportional hazards model to predict patient recruitment in multicenter clinical trials.- GET MORE INFORMATION FROM RECURRENT EVENTS DATA.- Introduction to Patient Preference Studies.- Machine Learning for Precision Medicine and Humanized AI for Future Healthcare.- The Statistical Evaluation of Surrogate Endpoints in Clinical Trials.- Treatment Effect Estimation Using Data from Observational and Non-Randomized Studies.- Methods for Comparing Two Treatments for a Dichotomous Outcome for a Two-Period Design with Treatment Switching of Control Group Period 1 Non-Responders.- Regression-based estimation of optimal adaptive treatment strategies: Key methods.- Vaccine Disease-Prevention Efficacy Studies: Traditional Approaches and New Frontiers.- Covariate Adjustment in Analyzing Randomized Clinical Trials: Approaches, Software, and Application.- Joint correlated responses and feedback effect with time-dependent covariates.- Distributions and Their Approximations for P-Values.

Über Autor(innen)

Din Chen is a Fellow of the American Statistical Association and is currently the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University. He is also an Extraordinary Professor and the SARChI in biostatistics at the University of Pretoria, and an honorary professor at the University of KwaZulu-Natal, South Africa. He is a senior biostatistics consultant for biopharmaceuticals and government agencies with extensive expertise in biostatistics, clinical trials, and public health statistics. Dr. Chen has more than 200 referred professional publications and co-authored 11 books and co-edited 24 books on clinical trial methodology, meta-analysis, data science, causal inference, and public health research. Professor Chen is the Deming publicity chair and he has been honored with the "Award of Recognition" from the Deming Conference Committee for highly successful advanced biostatistics workshop tutorials with his books.