Innovative Strategies Statistical Solutions And Simulations For Modern Clinical Trials

Innovative Strategies Statistical Solutions And Simulations For Modern Clinical Trials Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Innovative Strategies Statistical Solutions And Simulations For Modern Clinical Trials book. This book definitely worth reading, it is an incredibly well-written.

Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials

Mark Chang,John Balser,Jim Roach,Robin Bliss
Innovative Strategies Statistical Solutions and Simulations for Modern Clinical Trials Book PDF

Author : Mark Chang,John Balser,Jim Roach,Robin Bliss
Publisher : CRC Press
Page : 362 pages
File Size : 53,7 Mb
Release : 2019-03-20
Category : Mathematics
ISBN : 9781351214537

Get Book

Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials by Mark Chang,John Balser,Jim Roach,Robin Bliss Pdf

"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.

Case Studies in Innovative Clinical Trials

Kristine Broglio,Binbing Yu
Case Studies in Innovative Clinical Trials Book PDF

Author : Kristine Broglio,Binbing Yu
Publisher : CRC Press
Page : 303 pages
File Size : 43,7 Mb
Release : 2023-11-27
Category : Mathematics
ISBN : 9781000987218

Get Book

Case Studies in Innovative Clinical Trials by Kristine Broglio,Binbing Yu Pdf

Drug development is a strictly regulated area. As such, marketing approval of a new drug depends heavily, if not exclusively, on evidence generated from clinical trials. Drug development has seen tremendous innovation in science and technology that has revolutionized the treatment of some diseases. And yet, the statistical design and practical conduct of the clinical trials used to test new therapeutics for safety and efficacy have changed very little over the decades. Our approach to clinical trials is steeped in convention and tradition. The large, fixed, randomized controlled trial methods that have been the gold standard are well understood and expected by many trial stakeholders. However, this approach is not well suited to all aspects of modern drug development and the current competitive landscape. We now see new therapies that target a small fraction of the patient population, rare diseases with high unmet medical needs, and pediatric populations that must wait for years for new drug approvals from the time that therapies are approved in adults. Large randomized clinical trials are at best inefficient and at worst completely infeasible in many modern clinical settings. Advances in technology and data infrastructure call for innovations in clinical trial design. Despite advances in statistical methods, the availability of information, and computing power, the actual experience with innovative design in clinical trials across industry and academia is limited. 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. This book is ideal for professionals in the pharmaceutical industry and regulatory agencies, but it will also be useful to academic researchers, faculty members, and graduate students in statistics, biostatistics, public health, and epidemiology due to its focus on innovation. Key Features: Is written by pharmaceutical industry experts, academic researchers, and regulatory reviewers; this is the first book providing a comprehensive set of case studies related to statistical methodology, implementation, regulatory considerations, and communication of complex innovative trial design Has a broad appeal to a multitude of readers across academia, industry, and regulatory agencies Each contribution is a practical case study that can speak to the benefits of an innovative approach but also balance that with the real-life challenges encountered A complete understanding of what is actually being done in modern clinical trials will broaden the reader’s capabilities and provide examples to first mimic and then customize and expand upon when exploring these ideas on their own

Mathematical and Statistical Skills in the Biopharmaceutical Industry

Arkadiy Pitman,Oleksandr Sverdlov,L. Bruce Pearce
Mathematical and Statistical Skills in the Biopharmaceutical Industry Book PDF

Author : Arkadiy Pitman,Oleksandr Sverdlov,L. Bruce Pearce
Publisher : CRC Press
Page : 247 pages
File Size : 41,8 Mb
Release : 2019-07-15
Category : Business & Economics
ISBN : 9780429532238

Get Book

Mathematical and Statistical Skills in the Biopharmaceutical Industry by Arkadiy Pitman,Oleksandr Sverdlov,L. Bruce Pearce Pdf

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.

Foundation, Architecture, and Prototyping of Humanized AI

Mark Chang
Foundation Architecture and Prototyping of Humanized AI Book PDF

Author : Mark Chang
Publisher : CRC Press
Page : 385 pages
File Size : 54,7 Mb
Release : 2023-08-08
Category : Computers
ISBN : 9781000911480

Get Book

Foundation, Architecture, and Prototyping of Humanized AI by Mark Chang Pdf

Humanized AI (HAI), emerging as the next of the AI waves, refers to artificial social beings that are very close to humans in various aspects, beings who are machine-race humans, not digital slaves. Foundation, Architecture, and Prototyping of HAI deploy a novel smalldata approach to vertically explore the spectrum of HAI. Different from the popular big-data philosophy that is based on the rigid notion that the connotation of each concept is fixed and the same to everyone, this book treats understanding as a process from simple to complex, and uses the similarity principle to effectively deal with novelties. Combining the efficiency of the Behaviorists’ goal-driven approach and the flexibility of a Constructivists’ approach, both the architecture of HAI and the philosophical discussions arising from it are elaborated upon. Advancing a unique approach to the concept of HAI, this book appeals to professors and students of both AI and philosophy, as well as industry professionals looking to stay at the forefront of developments within the field.

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare

Mark Chang
Artificial Intelligence for Drug Development Precision Medicine and Healthcare Book PDF

Author : Mark Chang
Publisher : CRC Press
Page : 372 pages
File Size : 45,9 Mb
Release : 2020-05-07
Category : Business & Economics
ISBN : 9781000766721

Get Book

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare by Mark Chang Pdf

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods

Sandeep Menon,Richard C. Zink
Modern Approaches to Clinical Trials Using SAS Classical Adaptive and Bayesian Methods Book PDF

Author : Sandeep Menon,Richard C. Zink
Publisher : SAS Institute
Page : 364 pages
File Size : 47,7 Mb
Release : 2015-12-09
Category : Computers
ISBN : 9781629600840

Get Book

Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods by Sandeep Menon,Richard C. Zink Pdf

This book covers domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods applicable to and used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, it covers topics including: dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs incorporating historical data; adaptive sample size re-estimation and randomization to allocate subjects to effective treatments; population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology and rheumatology. --

Economic Evaluation of Cancer Drugs

Iftekhar Khan,Ralph Crott,Zahid Bashir
Economic Evaluation of Cancer Drugs Book PDF

Author : Iftekhar Khan,Ralph Crott,Zahid Bashir
Publisher : CRC Press
Page : 334 pages
File Size : 40,8 Mb
Release : 2019-06-14
Category : Mathematics
ISBN : 9780429531842

Get Book

Economic Evaluation of Cancer Drugs by Iftekhar Khan,Ralph Crott,Zahid Bashir Pdf

Cancer is a major healthcare burden across the world and impacts not only the people diagnosed with various cancers but also their families, carers, and healthcare systems. With advances in the diagnosis and treatment, more people are diagnosed early and receive treatments for a disease where few treatments options were previously available. As a result, the survival of patients with cancer has steadily improved and, in most cases, patients who are not cured may receive multiple lines of treatment, often with financial consequences for the patients, insurers and healthcare systems. Although many books exist that address economic evaluation, Economic Evaluation of Cancer Drugs using Clinical Trial and Real World Data is the first unified text that specifically addresses the economic evaluation of cancer drugs. The authors discuss how to perform cost-effectiveness analyses while emphasising the strategic importance of designing cost-effectiveness into cancer trials and building robust economic evaluation models that have a higher chance of reimbursement if truly cost-effective. They cover the use of real-world data using cancer registries and discuss how such data can support or complement clinical trials with limited follow up. Lessons learned from failed reimbursement attempts, factors predictive of successful reimbursement and the different payer requirements across major countries including US, Australia, Canada, UK, Germany, France and Italy are also discussed. The book includes many detailed practical examples, case studies and thought-provoking exercises for use in classroom and seminar discussions. Iftekhar Khan is a medical statistician and health economist and a lead statistician at Oxford Unviersity’s Center for Statistics in Medicine. Professor Khan is also a Senior Research Fellow in Health Economics at University of Warwick and is a Senior Statistical Assessor within the Licensing Division of the UK Medicine and Health Regulation Agency. Ralph Crott is a former professor in Pharmacoeconomics at the University of Montreal in Quebec, Canada and former head of the EORTC Health Economics Unit and former senior health economist at the Belgian HTA organization. Zahid Bashir has over twelve years experience working in the pharmaceutical industry in medical affairs and oncology drug development where he is involved in the design and execution of oncology clinical trials and development of reimbursement dossiers for HTA submission.

Bayesian Cost-Effectiveness Analysis of Medical Treatments

Elias Moreno,Francisco Jose Vazquez-Polo,Miguel Angel Negrín-Hernández
Bayesian Cost Effectiveness Analysis of Medical Treatments Book PDF

Author : Elias Moreno,Francisco Jose Vazquez-Polo,Miguel Angel Negrín-Hernández
Publisher : CRC Press
Page : 284 pages
File Size : 44,7 Mb
Release : 2019-01-30
Category : Mathematics
ISBN : 9781351744379

Get Book

Bayesian Cost-Effectiveness Analysis of Medical Treatments by Elias Moreno,Francisco Jose Vazquez-Polo,Miguel Angel Negrín-Hernández Pdf

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems. Cost-Effectiveness of Medical Treatments formulates the cost-effectiveness analysis as a statistical decision problem, identifies the sources of uncertainty of the problem, and gives an overview of the frequentist and Bayesian statistical approaches for decision making. Basic notions on decision theory such as space of decisions, space of nature, utility function of a decision and optimal decisions, are explained in detail using easy to read mathematics. Features Focuses on cost-effectiveness analysis as a statistical decision problem and applies the well-established optimal statistical decision methodology. Discusses utility functions for cost-effectiveness analysis. Enlarges the class of models typically used in cost-effectiveness analysis with the incorporation of linear models to account for covariates of the patients. This permits the formulation of the group (or subgroup) theory. Provides Bayesian procedures to account for model uncertainty in variable selection for linear models and in clustering for models for heterogeneous data. Model uncertainty in cost-effectiveness analysis has not been considered in the literature. Illustrates examples with real data. In order to facilitate the practical implementation of real datasets, provides the codes in Mathematica for the proposed methodology. The motivation for the book is to make the achievements in cost-effectiveness analysis accessible to health providers, who need to make optimal decisions, to the practitioners and to the students of health sciences. Elías Moreno is Professor of Statistics and Operational Research at the University of Granada, Spain, Corresponding Member of the Royal Academy of Sciences of Spain, and elect member of ISI. Francisco José Vázquez-Polo is Professor of Mathematics and Bayesian Methods at the University of Las Palmas de Gran Canaria, and Head of the Department of Quantitative Methods. Miguel Ángel Negrín is Senior Lecturer in the Department of Quantitative Methods at the ULPGC. His main research topics are Bayesian methods applied to Health Economics, economic evaluation and cost-effectiveness analysis, meta-analysis and equity in the provision of healthcare services.

Mixture Modelling for Medical and Health Sciences

Shu-Kay Ng
Mixture Modelling for Medical and Health Sciences Book PDF

Author : Shu-Kay Ng
Publisher : CRC Press
Page : 222 pages
File Size : 49,5 Mb
Release : 2019-05-03
Category : Mathematics
ISBN : 9780429529092

Get Book

Mixture Modelling for Medical and Health Sciences by Shu-Kay Ng Pdf

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in

Analysis of Incidence Rates

Peter Cummings
Analysis of Incidence Rates Book PDF

Author : Peter Cummings
Publisher : CRC Press
Page : 474 pages
File Size : 53,8 Mb
Release : 2019-04-16
Category : Mathematics
ISBN : 9780429621208

Get Book

Analysis of Incidence Rates by Peter Cummings Pdf

Incidence rates are counts divided by person-time; mortality rates are a well-known example. Analysis of Incidence Rates offers a detailed discussion of the practical aspects of analyzing incidence rates. Important pitfalls and areas of controversy are discussed. The text is aimed at graduate students, researchers, and analysts in the disciplines of epidemiology, biostatistics, social sciences, economics, and psychology. Features: Compares and contrasts incidence rates with risks, odds, and hazards. Shows stratified methods, including standardization, inverse-variance weighting, and Mantel-Haenszel methods Describes Poisson regression methods for adjusted rate ratios and rate differences. Examines linear regression for rate differences with an emphasis on common problems. Gives methods for correcting confidence intervals. Illustrates problems related to collapsibility. Explores extensions of count models for rates, including negative binomial regression, methods for clustered data, and the analysis of longitudinal data. Also, reviews controversies and limitations. Presents matched cohort methods in detail. Gives marginal methods for converting adjusted rate ratios to rate differences, and vice versa. Demonstrates instrumental variable methods. Compares Poisson regression with the Cox proportional hazards model. Also, introduces Royston-Parmar models. All data and analyses are in online Stata files which readers can download. Peter Cummings is Professor Emeritus, Department of Epidemiology, School of Public Health, University of Washington, Seattle WA. His research was primarily in the field of injuries. He used matched cohort methods to estimate how the use of seat belts and presence of airbags were related to death in a traffic crash. He is author or co-author of over 100 peer-reviewed articles.

Geospatial Health Data

Paula Moraga
Geospatial Health Data Book PDF

Author : Paula Moraga
Publisher : CRC Press
Page : 295 pages
File Size : 41,8 Mb
Release : 2019-11-21
Category : Medical
ISBN : 9781000732030

Get Book

Geospatial Health Data by Paula Moraga Pdf

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.

An Introduction to Artificial Psychology

Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi
An Introduction to Artificial Psychology Book PDF

Author : Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi
Publisher : Springer Nature
Page : 262 pages
File Size : 54,9 Mb
Release : 2023-05-18
Category : Psychology
ISBN : 9783031311727

Get Book

An Introduction to Artificial Psychology by Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi Pdf

Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software.

Statistical Methods in Biomarker and Early Clinical Development

Liang Fang,Cheng Su
Statistical Methods in Biomarker and Early Clinical Development Book PDF

Author : Liang Fang,Cheng Su
Publisher : Springer Nature
Page : 354 pages
File Size : 53,5 Mb
Release : 2019-12-26
Category : Medical
ISBN : 9783030315030

Get Book

Statistical Methods in Biomarker and Early Clinical Development by Liang Fang,Cheng Su Pdf

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.

Bayesian Analysis with R for Drug Development

Harry Yang,Steven Novick
Bayesian Analysis with R for Drug Development Book PDF

Author : Harry Yang,Steven Novick
Publisher : CRC Press
Page : 262 pages
File Size : 41,9 Mb
Release : 2019-06-26
Category : Mathematics
ISBN : 9781351585934

Get Book

Bayesian Analysis with R for Drug Development by Harry Yang,Steven Novick Pdf

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.

Clinical Trial Optimization Using R

Alex Dmitrienko,Erik Pulkstenis
Clinical Trial Optimization Using R Book PDF

Author : Alex Dmitrienko,Erik Pulkstenis
Publisher : CRC Press
Page : 319 pages
File Size : 49,5 Mb
Release : 2017-08-10
Category : Mathematics
ISBN : 9781498735087

Get Book

Clinical Trial Optimization Using R by Alex Dmitrienko,Erik Pulkstenis Pdf

Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with a powerful evaluation paradigm, as well as supportive R tools, to evaluate and select among simultaneous competing designs or analysis options. It is applicable broadly to statisticians and other quantitative clinical trialists, who have an interest in optimizing clinical trials, clinical trial programs, or associated analytics and decision making. This book presents in depth the Clinical Scenario Evaluation (CSE) framework, and discusses optimization strategies, including the quantitative assessment of tradeoffs. A variety of common development challenges are evaluated as case studies, and used to show how this framework both simplifies and optimizes strategy selection. Specific settings include optimizing adaptive designs, multiplicity and subgroup analysis strategies, and overall development decision-making criteria around Go/No-Go. After this book, the reader will be equipped to extend the CSE framework to their particular development challenges as well.