Interface Between Regulation And Statistics In Drug Development
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Interface Between Regulation And Statistics In Drug Development
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Author : Demissie Alemayehu
language : en
Publisher: CRC Press
Release Date : 2020-11-11
Interface Between Regulation And Statistics In Drug Development written by Demissie Alemayehu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-11 with Mathematics categories.
With the critical role of statistics in the design, conduct, analysis and reporting of clinical trials or observational studies intended for regulatory purposes, numerous guidelines have been issued by regulatory authorities around the world focusing on statistical issues related to drug development. However, the available literature on this important topic is sporadic, and often not readily accessible to drug developers or regulatory personnel. This book provides a systematic exposition of the interplay between the two disciplines, including emerging themes pertaining to the acceleration of the development of pharmaceutical medicines to serve patients with unmet needs. Features: Regulatory and statistical interactions throughout the drug development continuum The critical role of the statistician in relation to the changing regulatory and healthcare landscapes Statistical issues that commonly arise in the course of drug development and regulatory interactions Trending topics in drug development, with emphasis on current regulatory thinking and the associated challenges and opportunities The book is designed to be accessible to readers with an intermediate knowledge of statistics, and can be a useful resource to statisticians, medical researchers, and regulatory personnel in drug development, as well as graduate students in the health sciences. The authors’ decades of experience in the pharmaceutical industry and academia, and extensive regulatory experience, comes through in the many examples throughout the book.
Real World Evidence In Drug Development And Evaluation
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Author : Harry Yang
language : en
Publisher: CRC Press
Release Date : 2021-01-11
Real World Evidence In Drug Development And Evaluation 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 2021-01-11 with Mathematics categories.
Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field. Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions. Features Provides the first book and a single source of information on RWE in drug development Covers a broad array of topics on outcomes- and value-based RWE assessments Demonstrates proper Bayesian application and causal inference for real-world data (RWD) Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise
Advanced Statistics In Regulatory Critical Clinical Initiatives
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Author : Wei Zhang
language : en
Publisher: CRC Press
Release Date : 2022-05-25
Advanced Statistics In Regulatory Critical Clinical Initiatives written by Wei Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-25 with Mathematics categories.
Advanced Statistics in Regulatory Critical Clinical Initiatives is focused on the critical clinical initiatives introduced by the 21st Century Cure Act passed by the United States Congress in December 2016. The book covers everything from the outline of the initiatives to analysis on the effect on biopharmaceutical research and development. Advanced Statistics in Regulatory Critical Clinical Initiatives provides innovative ways to resolve common challenges in statistical research of rare diseases such small sample sizes and provides guidance for combined use of data. With analysis from regulatory and scientific perspectives this book is an ideal companion for researchers in biostatistics, pharmaceutical development, and policy makers in related fields. Key Features: Provides better understanding of innovative design and analysis of each critical clinical initiatives which may be used in regulatory review/approval of drug development. Makes recommendations to evaluate submissions accurately and reliably. Proposes innovative study designs and statistical methods for oncology and/or rare disease drug development. Provides insight regarding current regulatory guidance on drug development such as gene therapy and rare diseases.
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.
Dose Finding In Drug Development
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Author : Naitee Ting
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-12-29
Dose Finding In Drug Development written by Naitee Ting 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 2006-12-29 with Medical categories.
If you have ever wondered when visiting the pharmacy how the dosage of your prescription is determined this book will answer your questions. Dosing information on drug labels is based on discussion between the pharmaceutical manufacturer and the drug regulatory agency, and the label is a summary of results obtained from many scientific experiments. The book introduces the drug development process, the design and the analysis of clinical trials. Many of the discussions are based on applications of statistical methods in the design and analysis of dose response studies. Important procedural steps from a pharmaceutical industry perspective are also examined.
Statistics In The Pharmaceutical Industry
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Author : C. Ralph Buncher
language : en
Publisher: CRC Press
Release Date : 2019-03-07
Statistics In The Pharmaceutical Industry written by C. Ralph Buncher and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-07 with Mathematics categories.
The growth of the pharmaceutical industry over the past decade is astounding, but the impact of this growth on statistics is somewhat confusing. While software has made analysis easier and more efficient, regulatory bodies now demand deeper and more complex analyses, and pharmacogenetic/genomic studies serve up an entirely new set of challenges. For more than two decades, Statistics in the Pharmaceutical Industry has been the definitive guide to sorting through the challenges in the industry, and this Third Edition continues that tradition. Updated and expanded to reflect the most recent trends and developments in the field, Statistics in the Pharmaceutical Industry, Third Edition presents chapters written by experts from both regulatory agencies and pharmaceutical companies who discuss everything from experimental design to post-marketing studies. This approach sheds light on what regulators consider acceptable methodologies and what methods have proven successful for industrial statisticians. Both new and revised chapters reflect the increasingly global nature of the industry as represented by authors from Japan and Europe, the increasing trend toward non-inferiority/equivalence testing, adaptive design in clinical trials, global harmonization of regulatory standards, and multiple comparison studies. The book also examines the latest considerations in anti-cancer studies. Statistics in the Pharmaceutical Industry, Third Edition demystifies the approval process by combining regulatory and industrial points of view, making it a must-read for anyone performing statistical analysis at any point in the drug approval process.
Statistical Thinking For Non Statisticians In Drug Regulation
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Author : Richard Kay
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-29
Statistical Thinking For Non Statisticians In Drug Regulation written by Richard Kay 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 2022-11-29 with Medical categories.
STATISTICAL THINKING FOR NON-STATISTICIANS IN DRUG REGULATION Statistical methods in the pharmaceutical industry are accepted as a key element in the design and analysis of clinical studies. Increasingly, the medical and scientific community are aligning with the regulatory authorities and recognizing that correct statistical methodology is essential as the basis for valid conclusions. In order for those correct and robust methods to be successfully employed there needs to be effective communication across disciplines at all stages of the planning, conducting, analyzing and reporting of clinical studies associated with the development and evaluation of new drugs and devices. Statistical Thinking for Non-Statisticians in Drug Regulation provides a comprehensive in-depth guide to statistical methodology for pharmaceutical industry professionals, including physicians, investigators, medical science liaisons, clinical research scientists, medical writers, regulatory personnel, statistical programmers, senior data managers and those working in pharmacovigilance. The author’s years of experience and up-to-date familiarity with pharmaceutical regulations and statistical practice within the wider clinical community make this an essential guide for the those working in and with the industry. The third edition of Statistical Thinking for Non-Statisticians in Drug Regulation includes: A detailed new chapter on Estimands in line with the 2019 Addendum to ICH E9 Major new sections on topics including Combining Hierarchical Testing and Alpha Adjustment, Biosimilars, Restricted Mean Survival Time, Composite Endpoints and Cumulative Incidence Functions, Adjusting for Cross-Over in Oncology, Inverse Propensity Score Weighting, and Network Meta-Analysis Updated coverage of many existing topics to reflect new and revised guidance from regulatory authorities and author experience Statistical Thinking for Non-Statisticians in Drug Regulation is a valuable guide for pharmaceutical and medical device industry professionals, as well as statisticians joining the pharmaceutical industry and students and teachers of drug development.
Simultaneous Global New Drug Development
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Author : Gang Li
language : en
Publisher: CRC Press
Release Date : 2024-01-29
Simultaneous Global New Drug Development written by Gang Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-29 with Mathematics categories.
Global simultaneous development is becoming more necessary as the cost of developing medical products continues to grow. The strategy of using multiregional clinical trials (MRCTs) has become the preferred method for developing new medicines. Implementing the same protocol to include subjects from many geographical regions around the world, MRCTs can speed up the patient enrolment, thus resulting in quicker drug development and obtaining faster approval of the drug globally. After the publication of the editors' first volume on this topic, there have been new developments on MRCTs. The International Council for Harmonisation (ICH) issued ICH E17, a guideline document on MRCTs, in November 2017, laying out principles on MRCTs. Beyond E17, new methodologies have been developed as well. Simultaneous Global New Drug Development: Multi-Regional Clinical Trials after ICH E17 collects chapters providing interpretations of principles in ICH E17 and new ideas of implementing MRCTs. Authors are from different regions, and from academia and industry. In addition, in contrast to the first book, new perspectives are brought to MRCT from regulatory agencies. This book will be of particular interest to biostatisticians working in late stage clinical development of medical products. It will also be especially helpful for statisticians in regulatory agencies, and medical research institutes. This book is comprehensive across the MRCT topic spectrum, including Issues regarding ICH E17 Implementation MRCT Design and Analysis Methodologies Perspectives from authorities in regulatory agencies, as well as statisticians practicing in the medical product industry Many examples of real-life applications based on actual MRCTs.
Statistics In Drug Research
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Author : Shein-Chung Chow
language : en
Publisher: CRC Press
Release Date : 2002-02-20
Statistics In Drug Research written by Shein-Chung Chow and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-02-20 with Mathematics categories.
Emphasizing the role of good statistical practices (GSP) in drug research and formulation, this book outlines important statistics applications for each stage of pharmaceutical development to ensure the valid design, analysis, and assessment of drug products under investigation and establish the safety and efficacy of pharmaceutical compounds. Cove
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.