Share

Statistical Methods in Biomarker and Early Clinical Development

2019-12-26 Medical
Download Statistical Methods in Biomarker and Early Clinical Development PDF Online Free

Author :
Release : 2019-12-26
Genre : Medical
Kind : eBook
Book Rating : 037/5 ( reviews)

GET EBOOK


Book Synopsis Statistical Methods in Biomarker and Early Clinical Development by : Liang Fang

Download or read book Statistical Methods in Biomarker and Early Clinical Development written by Liang Fang. This book was released on 2019-12-26. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume offers a much-needed overview of the statistical methods in early clinical drug and biomarker development. Chapters are written by expert statisticians with extensive experience in the pharmaceutical industry and regulatory agencies. Because of this, the data presented is often accompanied by real world case studies, which will help make examples more tangible for readers. The many applications of statistics in drug development are covered in detail, making this volume a must-have reference. Biomarker development and early clinical development are the two critical areas on which the book focuses. By having the two sections of the book dedicated to each of these topics, readers will have a more complete understanding of how applying statistical methods to early drug development can help identify the right drug for the right patient at the right dose. Also presented are exciting applications of machine learning and statistical modeling, along with innovative methods and state-of-the-art advances, making this a timely and practical resource. This volume is ideal for statisticians, researchers, and professionals interested in pharmaceutical research and development. Readers should be familiar with the fundamentals of statistics and clinical trials.

Statistical Approaches in Oncology Clinical Development

2018-12-07 Mathematics
Download Statistical Approaches in Oncology Clinical Development PDF Online Free

Author :
Release : 2018-12-07
Genre : Mathematics
Kind : eBook
Book Rating : 706/5 ( reviews)

GET EBOOK


Book Synopsis Statistical Approaches in Oncology Clinical Development by : Satrajit Roychoudhury

Download or read book Statistical Approaches in Oncology Clinical Development written by Satrajit Roychoudhury. This book was released on 2018-12-07. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Approaches in Oncology Clinical Development : Current Paradigm and Methodological Advancement presents an overview of statistical considerations in oncology clinical trials, both early and late phase of development. It illustrates how novel statistical methods can enrich the design and analysis of modern oncology trials. The authors include many relevant real life examples from the pharmaceutical industry and academia based on their first-hand experience. Along with relevant references, the book highlights current regulatory views. The book covers all aspects of cancer clinical trial starting from early phase development. The early part of the book covers novel phase I dose escalation design, exposure response analysis, and innovative phase II design. This includes early development strategy for cancer immunotherapy trials. The contributors also emphasized the role of biomarker and modern era of precision medicine. The second part focuses on the late stage development. This includes the application of adaptive design, safety analysis, and quality of life (QoL) data analysis. The final part discusses current regulatory perspective and challenges. Features: Covers a wide spectrum of topics related to real-life statistical challenges in oncology clinical trials. Provides a comprehensive overview of novel statistical methods to improve trial design and statistical analysis. Detailed case studies illustrate the real life applications. Satrajit Roychoudhury is a Senior Director and a member of the Statistical Research and Innovation group in Pfizer Inc. Prior to joining; he was a member of Statistical Methodology and consulting group in Novartis. He has 11 years of extensive experience in working with different phases of clinical trial. His area of research includes early phase oncology trials, survival analysis, model informed drug development, and use of Bayesian methods in clinical trials. He is industry co-chair for the ASA Biopharmaceutical Section Regulatory-Industry Workshop and has provided statistical training in major conferences including the Joint Statistical Meetings, ASA Biopharmaceutical Section Regulatory-Industry Workshop, and ICSA Applied Statistics Symposium. Soumi Lahiri has 12 years of extensive experience in working different therapeutic areas. She is the former Director of Biostatistics in Clinical Oncology, GlaxoSmithKline. She has also worked in the oncology division of Novartis Pharmaceutical Company for two years. She is an active member of the ASA Biopharmaceutical section and former chair of the membership committee.

Biomarker Analysis in Clinical Trials with R

2020-03-11 Mathematics
Download Biomarker Analysis in Clinical Trials with R PDF Online Free

Author :
Release : 2020-03-11
Genre : Mathematics
Kind : eBook
Book Rating : 793/5 ( reviews)

GET EBOOK


Book Synopsis Biomarker Analysis in Clinical Trials with R by : Nusrat Rabbee

Download or read book Biomarker Analysis in Clinical Trials with R written by Nusrat Rabbee. This book was released on 2020-03-11. Available in PDF, EPUB and Kindle. Book excerpt: The world is awash in data. This volume of data will continue to increase. In the pharmaceutical industry, much of this data explosion has happened around biomarker data. Great statisticians are needed to derive understanding from these data. This book will guide you as you begin the journey into communicating, understanding and synthesizing biomarker data. -From the Foreword, Jared Christensen, Vice President, Biostatistics Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the pharmaceutical industry 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. The topic of combining multiple biomarkers to predict drug response using machine learning is covered. Featuring copious reproducible code and examples in R, the book helps students, researchers and biostatisticians get started in tackling the hard problems of designing and analyzing trials with biomarkers. Features: Analysis of pharmacodynamic biomarkers for lending evidence target modulation. Design and analysis of trials with a predictive biomarker. Framework for analyzing surrogate biomarkers. Methods for combining multiple biomarkers to predict treatment response. Offers a biomarker statistical analysis plan. R code, data and models are given for each part: including regression models for survival and longitudinal data, as well as statistical learning models, such as graphical models and penalized regression models.

Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials

2019-03-20 Mathematics
Download Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials PDF Online Free

Author :
Release : 2019-03-20
Genre : Mathematics
Kind : eBook
Book Rating : 535/5 ( reviews)

GET EBOOK


Book Synopsis Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials by : Mark Chang

Download or read book Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials written by Mark Chang. This book was released on 2019-03-20. Available in PDF, EPUB and Kindle. Book excerpt: "This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

Statistical Design, Monitoring, and Analysis of Clinical Trials

2021-10-26 Medical
Download Statistical Design, Monitoring, and Analysis of Clinical Trials PDF Online Free

Author :
Release : 2021-10-26
Genre : Medical
Kind : eBook
Book Rating : 811/5 ( reviews)

GET EBOOK


Book Synopsis Statistical Design, Monitoring, and Analysis of Clinical Trials by : Weichung Joe Shih

Download or read book Statistical Design, Monitoring, and Analysis of Clinical Trials written by Weichung Joe Shih. This book was released on 2021-10-26. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Design, Monitoring, and Analysis of Clinical Trials, Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters. Developed from the authors’ courses taught to public health and medical students, residents, and fellows during the past 20 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, phase 2/3 seamless design and trials with predictive biomarkers, exploit multiple testing procedures, and explain the concept of estimand, intercurrent events, and different missing data processes, and describe how to analyze incomplete data by proper multiple imputations. This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing, monitoring, and analyzing various types of trials. The book’s balanced set of homework assignments and in-class exercises are appropriate for students and researchers in (bio)statistics, epidemiology, medicine, pharmacy, and public health.

You may also like...