Mathematical And Statistical Skills In The Biopharmaceutical Industry

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Mathematical and Statistical Skills in the Biopharmaceutical Industry

Author : Arkadiy Pitman
Publisher : CRC Press
ISBN 13 : 1498769802
Total Pages : 220 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Mathematical and Statistical Skills in the Biopharmaceutical Industry by : Arkadiy Pitman

Download or read book Mathematical and Statistical Skills in the Biopharmaceutical Industry written by Arkadiy Pitman and published by CRC Press. This book was released on 2019-07-15 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach describes a philosophy of efficient problem solving showcased using examples pertinent to the biostatistics function in clinical drug development. It was written to share a quintessence of the authors’ experiences acquired during many years of relevant work in the biopharmaceutical industry. The book will be useful will be useful for biopharmaceutical industry statisticians at different seniority levels and for graduate students who consider a biostatistics-related career in this industry. Features: Describes a system of principles for pragmatic problem solving in clinical drug development. Discusses differences in the work of a biostatistician in small pharma and big pharma. Explains the importance/relevance of statistical programming and data management for biostatistics and necessity for integration on various levels. Describes some useful statistical background that can be capitalized upon in the drug development enterprise. Explains some hot topics and current trends in biostatistics in simple, non-technical terms. Discusses incompleteness of any system of standard operating procedures, rules and regulations. Provides a classification of scoring systems and proposes a novel approach for evaluation of the safety outcome for a completed randomized clinical trial. Presents applications of the problem solving philosophy in a highly problematic transfusion field where many investigational compounds have failed. Discusses realistic planning of open-ended projects.

Applied Statistics in the Pharmaceutical Industry

Author : Steven P. Millard
Publisher : Springer Science & Business Media
ISBN 13 : 1475734662
Total Pages : 518 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Applied Statistics in the Pharmaceutical Industry by : Steven P. Millard

Download or read book Applied Statistics in the Pharmaceutical Industry written by Steven P. Millard and published by Springer Science & Business Media. This book was released on 2013-11-09 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a general guide to statistical methods used in the pharmaceutical industry, and illustrating how to use S-PLUS to implement these methods, the book explains why S-PLUS is a useful software package and discusses the results and implications of each particular application. It is targeted at graduates in biostatistics, statisticians involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the industry, as well as statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.

Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry

Author : Richard K. Burdick
Publisher : Springer
ISBN 13 : 3319501860
Total Pages : 379 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry by : Richard K. Burdick

Download or read book Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry written by Richard K. Burdick and published by Springer. This book was released on 2017-02-14 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines statistical techniques that are critically important to Chemistry, Manufacturing, and Control (CMC) activities. Statistical methods are presented with a focus on applications unique to the CMC in the pharmaceutical industry. The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader. The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995). We agreed that a more recent book would serve a need in our industry. Since we began this project, an edited book has been published on the same topic by Zhang (2016). The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.

Nonclinical Statistics for Pharmaceutical and Biotechnology Industries

Author : Lanju Zhang
Publisher : Springer
ISBN 13 : 3319235583
Total Pages : 698 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Nonclinical Statistics for Pharmaceutical and Biotechnology Industries by : Lanju Zhang

Download or read book Nonclinical Statistics for Pharmaceutical and Biotechnology Industries written by Lanju Zhang and published by Springer. This book was released on 2016-01-13 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a reference text for regulatory, industry and academic statisticians and also a handy manual for entry level Statisticians. Additionally it aims to stimulate academic interest in the field of Nonclinical Statistics and promote this as an important discipline in its own right. This text brings together for the first time in a single volume a comprehensive survey of methods important to the nonclinical science areas within the pharmaceutical and biotechnology industries. Specifically the Discovery and Translational sciences, the Safety/Toxiology sciences, and the Chemistry, Manufacturing and Controls sciences. Drug discovery and development is a long and costly process. Most decisions in the drug development process are made with incomplete information. The data is rife with uncertainties and hence risky by nature. This is therefore the purview of Statistics. As such, this book aims to introduce readers to important statistical thinking and its application in these nonclinical areas. The chapters provide as appropriate, a scientific background to the topic, relevant regulatory guidance, current statistical practice, and further research directions.

Design and Analysis of Subgroups with Biopharmaceutical Applications

Author : Naitee Ting
Publisher : Springer Nature
ISBN 13 : 3030401057
Total Pages : 404 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Design and Analysis of Subgroups with Biopharmaceutical Applications by : Naitee Ting

Download or read book Design and Analysis of Subgroups with Biopharmaceutical Applications written by Naitee Ting and published by Springer Nature. This book was released on 2020-05-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the theories and applications on subgroups in the biopharmaceutical industry. Drawing from a range of expert perspectives in academia and industry, this collection offers an overarching dialogue about recent advances in biopharmaceutical applications, novel statistical and methodological developments, and potential future directions. The volume covers topics in subgroups in clinical trial design; subgroup identification and personalized medicine; and general issues in subgroup analyses, including regulatory ones. Included chapters present current methods, theories, and case applications in the diverse field of subgroup application and analysis. Offering timely perspectives from a range of authoritative sources, the volume is designed to have wide appeal to professionals in the pharmaceutical industry and to graduate students and researchers in academe and government.

Digital Therapeutics

Author : Oleksandr Sverdlov
Publisher : CRC Press
ISBN 13 : 1000799379
Total Pages : 607 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Digital Therapeutics by : Oleksandr Sverdlov

Download or read book Digital Therapeutics written by Oleksandr Sverdlov and published by CRC Press. This book was released on 2022-12-06 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the hallmarks of the 21st century medicine is the emergence of digital therapeutics (DTx)—evidence-based, clinically validated digital technologies to prevent, diagnose, treat, and manage various diseases and medical conditions. DTx solutions have been gaining interest from patients, investors, healthcare providers, health authorities, and other stakeholders because of the potential of DTx to deliver equitable, massively scalable, personalized and transformative treatments for different unmet medical needs. Digital Therapeutics: Scientific, Statistical, Clinical, and Regulatory Aspects is an unparalleled summary of the current scientific, statistical, developmental, and regulatory aspects of DTx which is poised to become the fastest growing area of the biopharmaceutical and digital medicine product development. This edited volume intends to provide a systematic exposition to digital therapeutics through 19 peer-reviewed chapters written by subject matter experts in this emerging field. This edited volume is an invaluable resource for business leaders and researchers working in public health, healthcare, digital health, information technology, and biopharmaceutical industries. It will be also useful for regulatory scientists involved in the review of DTx products, and for faculty and students involved in an interdisciplinary research on digital health and digital medicine. Key Features: Provides the taxonomy of the concepts and a navigation tool for the field of DTx. Covers important strategic aspects of the DTx industry, thereby helping investors, developers, and regulators gain a better appreciation of the potential value of DTx. Expounds on many existing and emerging state-of-the art scientific and technological tools, as well as data privacy, ethical and regulatory considerations for DTx product development. Presents several case studies of successful development of some of the most remarkable DTx products. Provides some perspectives and forward-looking statements on the future of digital medicine.

Statistical Methods in Biomarker and Early Clinical Development

Author : Liang Fang
Publisher : Springer Nature
ISBN 13 : 3030315037
Total Pages : 354 pages
Book Rating : 4.0/5 (33 download)

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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 and published by Springer Nature. This book was released on 2019-12-26 with total page 354 pages. 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.

Development of Gene Therapies

Author : Avery McIntosh
Publisher : CRC Press
ISBN 13 : 1003855962
Total Pages : 490 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Development of Gene Therapies by : Avery McIntosh

Download or read book Development of Gene Therapies written by Avery McIntosh and published by CRC Press. This book was released on 2024-05-23 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cell and gene therapies have become the third major drug modality in pharmaceutical medicine of the 21st century after low molecular weight and antibody drugs. The gene therapy (GTx) field is rapidly advancing, and yet there are still fundamental scientific questions that remain to be answered. Development of GTx products poses unique challenges and opportunities for drug developers. However, there is lack of a systematic exposition of the GTx product development and the pivotal role of the biostatistician in this process. Development of Gene Therapies: Strategic, Scientific, and Regulatory, and Access Considerations attempts to summarize the current state-of-the-art strategic, scientific, statistical, and regulatory aspects of GTx development. Intended to provide an exposition to the GTx new product development through peer-reviewed papers written by subject matter experts in this emerging field, this book will be useful for researchers in gene therapy drug development, biostatisticians, regulators, patient advocates, graduate students, and the finance and business development community . Key Features: A collection of papers covering a wide spectrum of topics in gene therapies (GTx), written by leading subject matter experts An exposition of the core principles of GTx product development, emerging business models, industry standards, best practices, and regulatory pathways An exposition of statistical and innovative modeling tools for design and analysis of clinical trials of GTx Insights into commercial models, access hurdles, and health economics of gene therapies Case studies of successful GTx approvals from core team members that developed the first two FDA-approved AAV gene therapies: Luxturna and Zolgensma A discussion of potential benefits and hurdles to be overcome for GTx in coming years from a multi-stakeholder perspective

Contemporary Biostatistics with Biopharmaceutical Applications

Author : Lanju Zhang
Publisher : Springer
ISBN 13 : 303015310X
Total Pages : 339 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Contemporary Biostatistics with Biopharmaceutical Applications by : Lanju Zhang

Download or read book Contemporary Biostatistics with Biopharmaceutical Applications written by Lanju Zhang and published by Springer. This book was released on 2019-07-11 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume presents current research in biostatistics with emphasis on biopharmaceutical applications. Featuring contributions presented at the 2017 ICSA Applied Statistics Symposium held in Chicago, IL on June 25 to 28, 2017, this book explores timely topics that have a high potential impact on statistical methodology and future research in biostatistics and biopharmaceuticals. The theme of this conference was Statistics for a New Generation: Challenges and Opportunities, in recognition of the advent of a new generation of statisticians. The conference attracted statisticians working in academia, government, and industry; domestic and international statisticians. From the conference, the editors selected 28 high-quality presentations and invited the speakers to prepare full chapters for this book. These contributions are divided into four parts: Part I Biostatistical Methodology, Part II Statistical Genetics and Bioinformatics, Part III Regulatory Statistics, and Part IV Biopharmaceutical Research and Applications. Featuring contributions on topics such as statistics in genetics, bioinformatics, biostatistical methodology, and statistical computing, this book is beneficial to researchers, academics, practitioners and policy makers in biostatistics and biopharmaceuticals.

Geospatial Health Data

Author : Paula Moraga
Publisher : CRC Press
ISBN 13 : 1000732037
Total Pages : 295 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Geospatial Health Data by : Paula Moraga

Download or read book Geospatial Health Data written by Paula Moraga and published by CRC Press. This book was released on 2019-11-21 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulating and transforming point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fitting and interpreting spatial and spatio-temporal models with the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) approaches, Creating interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policymakers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modelling, and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Medical Risk Prediction Models

Author : Thomas A. Gerds
Publisher : CRC Press
ISBN 13 : 0429764235
Total Pages : 249 pages
Book Rating : 4.4/5 (297 download)

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Book Synopsis Medical Risk Prediction Models by : Thomas A. Gerds

Download or read book Medical Risk Prediction Models written by Thomas A. Gerds and published by CRC Press. This book was released on 2021-02-01 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk calculator from scratch Discrimination, calibration, and predictive performance with censored data and competing risks R-code and illustrative examples Interpretation of prediction performance via benchmarks Comparison and combination of rival modeling strategies via cross-validation Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years. Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research.

Advanced Survival Models

Author : Catherine Legrand
Publisher : CRC Press
ISBN 13 : 0429622554
Total Pages : 361 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Advanced Survival Models by : Catherine Legrand

Download or read book Advanced Survival Models written by Catherine Legrand and published by CRC Press. This book was released on 2021-03-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice. This book aims to gather in a single reference the most commonly used extensions, such as frailty models (in case of unobserved heterogeneity or clustered data), cure models (when a fraction of the population will not experience the event of interest), competing risk models (in case of different types of event), and joint survival models for a time-to-event endpoint and a longitudinal outcome. Features Presents state-of-the art approaches for different advanced survival models including frailty models, cure models, competing risk models and joint models for a longitudinal and a survival outcome Uses consistent notation throughout the book for the different techniques presented Explains in which situation each of these models should be used, and how they are linked to specific research questions Focuses on the understanding of the models, their implementation, and their interpretation, with an appropriate level of methodological development for masters students and applied statisticians Provides references to existing R packages and SAS procedure or macros, and illustrates the use of the main ones on real datasets This book is primarily aimed at applied statisticians and graduate students of statistics and biostatistics. It can also serve as an introductory reference for methodological researchers interested in the main extensions of classical survival analysis.

Estimands, Estimators and Sensitivity Analysis in Clinical Trials

Author : Craig Mallinckrodt
Publisher : CRC Press
ISBN 13 : 0429950063
Total Pages : 345 pages
Book Rating : 4.4/5 (299 download)

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Book Synopsis Estimands, Estimators and Sensitivity Analysis in Clinical Trials by : Craig Mallinckrodt

Download or read book Estimands, Estimators and Sensitivity Analysis in Clinical Trials written by Craig Mallinckrodt and published by CRC Press. This book was released on 2019-12-23 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concepts of estimands, analyses (estimators), and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language, providing technical details, real-world examples, and SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence. This book lays out a path toward bridging some of these gaps. It offers A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1) Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs: A perspective on the role of the intention-to-treat principle Examples and case studies from various areas Example code in SAS and R A connection with causal inference Implications and methods for analysis of longitudinal trials with missing data Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.

Confidence Intervals for Discrete Data in Clinical Research

Author : Vivek Pradhan
Publisher : CRC Press
ISBN 13 : 1351690175
Total Pages : 240 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Confidence Intervals for Discrete Data in Clinical Research by : Vivek Pradhan

Download or read book Confidence Intervals for Discrete Data in Clinical Research written by Vivek Pradhan and published by CRC Press. This book was released on 2021-11-15 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas in clinical research. The array of methodologies available in the literature to address the inferential questions for binomial and multinomial data can be a double-edged sword. On the one hand, these methods open a rich avenue of exploration of data; on the other, the wide-ranging and competing methodologies potentially lead to conflicting inferences, adding to researchers' confusion and frustration and also leading to reporting bias. This book addresses the problems that many practitioners experience in choosing and implementing fit for purpose data analysis methods to answer critical inferential questions for binomial and count data. The book is an outgrowth of the authors' collective experience in biomedical research and provides an excellent overview of inferential questions of interest for binomial proportions and rates based on count data, and reviews various solutions to these problems available in the literature. Each chapter discusses the strengths and weaknesses of the methods and suggests practical recommendations. The book's primary focus is on applications in clinical research, and the goal is to provide direct benefit to the users involved in the biomedical field.

Pharmaceutical Statistics Using SAS

Author : Alex Dmitrienko, Ph.D.
Publisher : SAS Institute
ISBN 13 : 1629590304
Total Pages : 464 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Pharmaceutical Statistics Using SAS by : Alex Dmitrienko, Ph.D.

Download or read book Pharmaceutical Statistics Using SAS written by Alex Dmitrienko, Ph.D. and published by SAS Institute. This book was released on 2007-02-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.

Essential Statistics for the Pharmaceutical Sciences

Author : Philip Rowe
Publisher : John Wiley & Sons
ISBN 13 : 1118913396
Total Pages : 434 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Essential Statistics for the Pharmaceutical Sciences by : Philip Rowe

Download or read book Essential Statistics for the Pharmaceutical Sciences written by Philip Rowe and published by John Wiley & Sons. This book was released on 2015-09-28 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Statistics for the Pharmaceutical Sciences is targeted at all those involved in research in pharmacology, pharmacy or other areas of pharmaceutical science; everybody from undergraduate project students to experienced researchers should find the material they need. This book will guide all those who are not specialist statisticians in using sound statistical principles throughout the whole journey of a research project - designing the work, selecting appropriate statistical methodology and correctly interpreting the results. It deliberately avoids detailed calculation methodology. Its key features are friendliness and clarity. All methods are illustrated with realistic examples from within pharmaceutical science. This edition now includes expanded coverage of some of the topics included in the first edition and adds some new topics relevant to pharmaceutical research. a clear, accessible introduction to the key statistical techniques used within the pharmaceutical sciences all examples set in relevant pharmaceutical contexts. key points emphasised in summary boxes and warnings of potential abuses in ‘pirate boxes’. supplementary material - full data sets and detailed instructions for carrying out analyses using packages such as SPSS or Minitab – provided at: https://www.wiley.com/go/rowe/statspharmascience2e An invaluable introduction to statistics for any science student and an essential text for all those involved in pharmaceutical research at whatever level.

Bayesian Methods in Pharmaceutical Research

Author : Emmanuel Lesaffre
Publisher : CRC Press
ISBN 13 : 1351718673
Total Pages : 547 pages
Book Rating : 4.3/5 (517 download)

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Book Synopsis Bayesian Methods in Pharmaceutical Research by : Emmanuel Lesaffre

Download or read book Bayesian Methods in Pharmaceutical Research written by Emmanuel Lesaffre and published by CRC Press. This book was released on 2020-04-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.