Bayesian Analysis With R For Drug Development
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Bayesian Analysis With R For Drug Development
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Author : Harry Yang
language : en
Publisher: CRC Press
Release Date : 2019-06-26
Bayesian Analysis With R For Drug Development written by Harry Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-26 with Mathematics categories.
Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.
Bayesian Analysis With R For Drug Development
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Author : Harry Yang
language : en
Publisher: CRC Press
Release Date : 2019-06-26
Bayesian Analysis With R For Drug Development written by Harry Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-26 with Mathematics categories.
Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.
Bayesian Applications In Pharmaceutical Development
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Author : Mani Lakshminarayanan
language : en
Publisher: CRC Press
Release Date : 2019-11-07
Bayesian Applications In Pharmaceutical Development written by Mani Lakshminarayanan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Business & Economics categories.
The cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.
Theory Of Drug Development
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Author : Eric B. Holmgren
language : en
Publisher: CRC Press
Release Date : 2013-10-24
Theory Of Drug Development written by Eric B. Holmgren and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-24 with Mathematics categories.
Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. It examines the drug development process from the perspectives of drug companies and regulatory agencies. By quantifying various ideas underlying drug development, the book shows how to systematically address problems, such as: Sizing a phase 2 trial and choosing the range of p-values that will trigger a follow-up phase 3 trial Deciding whether a drug should receive marketing approval based on its phase 2/3 development program and recent experience with other drugs in the same clinical area Determining the impact of adaptive designs on the quality of drugs that receive marketing approval Designing a phase 3 pivotal study that permits the data-driven adjustment of the treatment effect estimate Knowing when enough information has been gathered to show that a drug improves the survival time for the whole patient population Drawing on his extensive work as a statistician in the pharmaceutical industry, the author focuses on the efficient development of drugs and the quantification of evidence in drug development. He provides a rationale for underpowered phase 2 trials based on the notion of efficiency, which leads to the identification of an admissible family of phase 2 designs. He also develops a framework for evaluating the strength of evidence generated by clinical trials. This approach is based on the ratio of power to type 1 error and transcends typical Bayesian and frequentist statistical analyses.
Applications Of Computational Tools In Drug Design And Development
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Author : S.N. Koteswara Rao G.
language : en
Publisher: Springer Nature
Release Date : 2025-05-20
Applications Of Computational Tools In Drug Design And Development written by S.N. Koteswara Rao G. and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Medical categories.
This book provides a comprehensive overview of the role of computers and computational tools at different stages of drug discovery and development. Designed to meet the needs of a beginner to advanced learner, the book provides the information on the tools, how they work, with the latest reports on applications in drug design, drug delivery and building network pharmacology models. Part I explores the pharmacological aspects, covering computational simulation of drug delivery at the molecular level, modeling for formulation design, and the revolutionary use of computational fluid dynamics in pharmaceutical processes. Specific applications such as pharmaceutical die filling processes, inhalation aerosol-based targeted drug delivery, and the development of inhalation compounds using in silico modeling tools are discussed. The use of computational tools in cheminformatics and their application in preformulation perspectives for drug delivery are also included. Part II expands the scope to include solubility prediction, absorption prediction, protein binding prediction, bio-permeability prediction, toxicity prediction, and metabolism prediction. It covers the identification of potential sites of metabolism in lead molecules and computer-assisted simulation studies to understand drug-polymer interactions. Recent advances in drug likeness screening using software and online tools are also reviewed. Part III focuses on specific therapeutic areas. The chapters examine the mechanistic understanding of anti-Alzheimer's agents, the design of novel antidiabetic agents, and the exploration of drug design for atherosclerosis. It also covers modern computational intelligence-based drug repurposing for cancer therapeutics, computational analyses of the mechanism of action of antiepileptic agents, and rational approaches for designing antihypertensive agents. The final chapters explore drug discovery and computational strategies in the context of multi-drug-resistant tuberculosis and the network pharmacology approach to uncover the pharmacological mechanisms of natural products. The book will be a useful reference for researchers, students and professionals in the field of life sciences, chemistry, pharmaceutics and bioinformatics.
Quantitative Decisions In Drug Development
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Author : Christy Chuang-Stein
language : en
Publisher: Springer Nature
Release Date : 2021-09-03
Quantitative Decisions In Drug Development written by Christy Chuang-Stein and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-03 with Mathematics categories.
This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug. It takes a holistic approach towards drug development by incorporating explicitly knowledge learned from the earlier part of the development and available historical information into decisions at later stages. In addition, the book shares lessons learned from several select examples published in the literature since the publication of the first edition. The second edition reiterates the need for making evidence-based Go/No Go decisions in drug development discussed in the first edition. It substantially expands several topics that have seen great advances since the publication of the first edition. The most noticeable additions include three adaptive trials conducted in recent years that offer excellent learning opportunities, the use of historical data in the design and analysis of clinical trials, and extending decision criteria to the cases when the primary endpoint is binary. The examples used to illustrate the additional materials all come from real trials with some post-trial reflections offered by the authors. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. Prior knowledge includes information pertaining to historical controls. To assist decision making, the book discusses appropriate metrics and the formulation of go/no-go decisions for progressing a drug candidate to the next development stage. Using the concept of the positive predictive value in the field of diagnostics, the book leads readers to the assessment of the probability that an investigational product is effective given positive study outcomes. Lastly, the book points out common mistakes made by drug developers under the current drug-development paradigm. The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization. The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves.
Modeling Dose Response Microarray Data In Early Drug Development Experiments Using R
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Author : Dan Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-27
Modeling Dose Response Microarray Data In Early Drug Development Experiments Using R written by Dan Lin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-27 with Mathematics categories.
This book focuses on the analysis of dose-response microarray data in pharmaceutical settings, the goal being to cover this important topic for early drug development experiments and to provide user-friendly R packages that can be used to analyze this data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students. Part I of the book is an introduction, in which we discuss the dose-response setting and the problem of estimating normal means under order restrictions. In particular, we discuss the pooled-adjacent-violator (PAV) algorithm and isotonic regression, as well as inference under order restrictions and non-linear parametric models, which are used in the second part of the book. Part II is the core of the book, in which we focus on the analysis of dose-response microarray data. Methodological topics discussed include: • Multiplicity adjustment • Test statistics and procedures for the analysis of dose-response microarray data • Resampling-based inference and use of the SAM method for small-variance genes in the data • Identification and classification of dose-response curve shapes • Clustering of order-restricted (but not necessarily monotone) dose-response profiles • Gene set analysis to facilitate the interpretation of microarray results • Hierarchical Bayesian models and Bayesian variable selection • Non-linear models for dose-response microarray data • Multiple contrast tests • Multiple confidence intervals for selected parameters adjusted for the false coverage-statement rate All methodological issues in the book are illustrated using real-world examples of dose-response microarray datasets from early drug development experiments.
Quantitative Evaluation Of Safety In Drug Development
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Author : Qi Jiang
language : en
Publisher: CRC Press
Release Date : 2014-12-08
Quantitative Evaluation Of Safety In Drug Development written by Qi Jiang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-08 with Mathematics categories.
State-of-the-Art Methods for Drug Safety AssessmentResponding to the increased scrutiny of drug safety in recent years, Quantitative Evaluation of Safety in Drug Development: Design, Analysis and Reporting explains design, monitoring, analysis, and reporting issues for both clinical trials and observational studies in biopharmaceutical product deve
Clinical Trial Modernization
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Author : Harry Yang
language : en
Publisher: CRC Press
Release Date : 2025-05-26
Clinical Trial Modernization written by Harry Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Mathematics categories.
As the pharmaceutical industry navigates this new era of technological innovation, the integration of AI, big data, and advanced analytics into clinical trials holds immense potential to transform drug development. Clinical Trial Modernization: Technological, Operational, and Regulatory Advances provides a comprehensive overview of the current trends, challenges, and opportunities in modernizing clinical trials, offering a roadmap for stakeholders in this evolving field. This book serves as a valuable resource for professionals, researchers, and regulators, providing actionable insights into the future of clinical trials and their critical role in bringing new therapies to market faster and more effectively.
Statistical Issues In Drug Development
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Author : Stephen S. Senn
language : en
Publisher: John Wiley & Sons
Release Date : 2008-02-28
Statistical Issues In Drug Development written by Stephen S. Senn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-28 with Medical categories.
Drug development is the process of finding and producingtherapeutically useful pharmaceuticals, turning them into safe andeffective medicine, and producing reliable information regardingthe appropriate dosage and dosing intervals. With regulatoryauthorities demanding increasingly higher standards in suchdevelopments, statistics has become an intrinsic and criticalelement in the design and conduct of drug development programmes. Statistical Issues in Drug Development presents anessential and thought provoking guide to the statistical issues andcontroversies involved in drug development. This highly readable second edition has been updated toinclude: Comprehensive coverage of the design and interpretation ofclinical trials. Expanded sections on missing data, equivalence, meta-analysisand dose finding. An examination of both Bayesian and frequentist methods. A new chapter on pharmacogenomics and expanded coverage ofpharmaco-epidemiology and pharmaco-economics. Coverage of the ICH guidelines, in particular ICH E9,Statistical Principles for Clinical Trials. It is hoped that the book will stimulate dialogue betweenstatisticians and life scientists working within the pharmaceuticalindustry. The accessible and wide-ranging coverage make itessential reading for both statisticians and non-statisticiansworking in the pharmaceutical industry, regulatory bodies andmedical research institutes. There is also much to benefitundergraduate and postgraduate students whose courses include amedical statistics component.