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| data management in pharmaceutical industry: Clinical Data Management Richard K. Rondel, Sheila A. Varley, Colin F. Webb, 2000-02-03 Extensively revised and updated, with the addition of new chapters and authors, this long-awaited second edition covers all aspects of clinical data management. Giving details of the efficient clinical data management procedures required to satisfy both corporate objectives and quality audits by regulatory authorities, this text is timely and an important contribution to the literature. The volume: * is written by well-known and experienced authors in this area * provides new approaches to major topics in clinical data management * contains new chapters on systems software validation, database design and performance measures. It will be invaluable to anyone in the field within the pharmaceutical industry, and to all biomedical professionals working in clinical research. |
| data management in pharmaceutical industry: Assuring Data Quality and Validity in Clinical Trials for Regulatory Decision Making Institute of Medicine, Roundtable on Research and Development of Drugs, Biologics, and Medical Devices, 1999-07-27 In an effort to increase knowledge and understanding of the process of assuring data quality and validity in clinical trials, the IOM hosted a workshop to open a dialogue on the process to identify and discuss issues of mutual concern among industry, regulators, payers, and consumers. The presenters and panelists together developed strategies that could be used to address the issues that were identified. This IOM report of the workshop summarizes the present status and highlights possible strategies for making improvements to the education of interested and affected parties as well as facilitating future planning. |
| data management in pharmaceutical industry: Careers with the Pharmaceutical Industry Peter D. Stonier, 2003-05-07 In recent years, many factors have combined to change the operating environment of the international pharmaceutical industry leading to greater specialisation and sophistication. This new edition will give an update of the different opportunities in drug discovery and development and the scientific, medical or other specialist training needed to accomplish them. The scope of this edition has been broadened to encompass all major roles, including marketing and sales. |
| data management in pharmaceutical industry: Sharing Clinical Trial Data Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Responsible Sharing of Clinical Trial Data, 2015-04-20 Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients. |
| data management in pharmaceutical industry: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. |
| data management in pharmaceutical industry: The Prevention and Treatment of Missing Data in Clinical Trials National Research Council, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Handling Missing Data in Clinical Trials, 2010-12-21 Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data. |
| data management in pharmaceutical industry: Pharmaceutical Medicine Adrian Kilcoyne, Phil Ambery, Daniel O'Connor, 2013-05-23 The breadth of the pharmaceutical medicine can be daunting, but this book is designed to navigate a path through the speciality. Providing a broad overview of all topics relevant to the discipline of pharmaceutical medicine, it gives you the facts fast, in a user-friendly format, without having to dive through page upon page of dense text. With 136 chapters spread across 8 sections, the text offers a thorough grounding in issues ranging from medicines regulation to clinical trial design and data management. This makes it a useful revision aid for exams as well as giving you a taster of areas of pharmaceutical medicine adjacent to your current role. For healthcare professionals already working in the field, this book offers a guiding hand in difficult situations as well as supplying rapid access to the latest recommendations and guidelines. Written by authors with experience in the industry and drug regulation, this comprehensive and authoritative guide provides a shoulder to lean on throughout your pharmaceutical career. |
| data management in pharmaceutical industry: Knowledge Management in the Pharmaceutical Industry Elisabeth Goodman, John Riddell, 2016-04-22 The Pharmaceutical Industry has been undergoing a major transformation since the heady days of 'big pharma' in the 1970s and 80s. Patent expiry, the rise of generics, and the decline of the blockbuster drug have all changed the landscape over the last 10-15 years. It's an environment where products can take 10 years or more to come to market, billions are spent on research and development, jobs are being shed in the western pharma homelands and regulators and the public are more demanding than ever. So what part is Knowledge Management playing and going to play in this vital international industry? Knowledge Management (KM) has many facets from providing comprehensive knowledge bases for workers, through the sharing of advice and problem solving, to providing an environment for innovation and change. This book, focusing on research and development, and manufacturing-based companies, explores how a range of techniques and approaches have been applied in the unique environment of the Pharmaceutical Industry, and examine how it can help the industry in the 21st century. Whilst the book is centered on the Pharmaceutical Industry, its objective will be to discuss and demonstrate how Knowledge Management can be applied in a variety of environments, and with a range of cultural issues. KM practitioners, and potential practitioners, both within and outside the Pharmaceutical Industry, will be able to gain valuable guidance and advice from both the examples of good practice and the lessons learned by the authors and contributors. |
| data management in pharmaceutical industry: SAS Programming in the Pharmaceutical Industry Jack Shostak, SAS Institute, 2005 This real-world reference for clinical trial SAS programming is packed with solutions that can be applied day-to-day problems. Organized to reflect the statistical programmers workflow, this user-friendly text begins with an introduction to the working environment, then presents chapters on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data. |
| data management in pharmaceutical industry: NexGen Technologies for Mining and Fuel Industries (Volume I and II) Pradeep K. Singh, V.K. Singh, A.K. Singh, D. Kumbhakar, M.P. Roy, 2017-03-06 The papers in these two volumes were presented at the International Conference on “NexGen Technologies for Mining and Fuel Industries” [NxGnMiFu-2017] in New Delhi from February 15-17, 2017, organized by CSIR-Central Institute of Mining and Fuel Research, Dhanbad, India. The proceedings include the contributions from authors across the globe on the latest research on mining and fuel technologies. The major issues focused on are: Innovative Mining Technology, Rock Mechanics and Stability Analysis, Advances in Explosives and Blasting, Mine Safety and Risk Management, Computer Simulation and Mine Automation, Natural Resource Management for Sustainable Development, Environmental Impacts and Remediation, Paste Fill Technology and Waste Utilisation, Fly Ash Management, Clean Coal Initiatives, Mineral Processing and Coal Beneficiation, Quality Coal for Power Generation and Conventional and Non-conventional Fuels and Gases. This collection of contemporary articles contains unique knowledge, case studies, ideas and insights, a must-have for researchers and engineers working in the areas of mining technologies and fuel sciences. |
| data management in pharmaceutical industry: Solid State Development and Processing of Pharmaceutical Molecules Michael Gruss, 2021-11-15 Solid State Development and Processing of Pharmaceutical Molecules A guide to the lastest industry principles for optimizing the production of solid state active pharmaceutical ingredients Solid State Development and Processing of Pharmaceutical Molecules is an authoritative guide that covers the entire pharmaceutical value chain. The authors—noted experts on the topic—examine the importance of the solid state form of chemical and biological drugs and review the development, production, quality control, formulation, and stability of medicines. The book explores the most recent trends in the digitization and automation of the pharmaceutical production processes that reflect the need for consistent high quality. It also includes information on relevant regulatory and intellectual property considerations. This resource is aimed at professionals in the pharmaceutical industry and offers an in-depth examination of the commercially relevant issues facing developers, producers and distributors of drug substances. This important book: Provides a guide for the effective development of solid drug forms Compares different characterization methods for solid state APIs Offers a resource for understanding efficient production methods for solid state forms of chemical and biological drugs Includes information on automation, process control, and machine learning as an integral part of the development and production workflows Covers in detail the regulatory and quality control aspects of drug development Written for medicinal chemists, pharmaceutical industry professionals, pharma engineers, solid state chemists, chemical engineers, Solid State Development and Processing of Pharmaceutical Molecules reviews information on the solid state of active pharmaceutical ingredients for their efficient development and production. |
| data management in pharmaceutical industry: Pharmaceutical Lifecycle Management Tony Ellery, Neal Hansen, 2012-06-05 A comprehensive guide to optimizing the lifecycle management of pharmaceutical brands The mounting challenges posed by cost containment policies and the prevalence of generic alternatives make optimizing the lifecycle management (LCM) of brand drugs essential for pharmaceutical companies looking to maximize the value of their products. Demonstrating how different measures can be combined to create winning strategies, Pharmaceutical Lifecycle Management: Making the Most of Each and Every Brand explores this increasingly important field to help readers understand what they can—and must—do to get the most out of their brands. Offering a truly immersive introduction to LCM options for pharmaceuticals, the book incorporates numerous real-life case studies that demonstrate successful and failed lifecycle management initiatives, explaining the key takeaway of each example. Filled with practical information on the process of actually writing and presenting an LCM plan, as well as how to link corporate, portfolio, and individual brand strategies, the book also offers a look ahead to predict which LCM strategies will continue to be effective in the future. While the development of new drugs designed to address unmet patient needs remains the single most important goal of any pharmaceutical company, effective LCM is invaluable for getting the greatest possible value from existing brands. Pharmaceutical Lifecycle Management walks you through the process step by step, making it indispensable reading for pharmaceutical executives and managers, as well as anyone working in the fields of drug research, development, and regulation. |
| data management in pharmaceutical industry: Risk Management Applications in Pharmaceutical and Biopharmaceutical Manufacturing Hamid Mollah, Harold Baseman, Mike Long, 2013-03-18 Sets forth tested and proven risk management practices in drug manufacturing Risk management is essential for safe and efficient pharmaceutical and biopharmaceutical manufacturing, control, and distribution. With this book as their guide, readers involved in all facets of drug manufacturing have a single, expertly written, and organized resource to guide them through all facets of risk management and analysis. It sets forth a solid foundation in risk management concepts and then explains how these concepts are applied to drug manufacturing. Risk Management Applications in Pharmaceutical and Biopharmaceutical Manufacturing features contributions from leading international experts in risk management and drug manufacturing. These contributions reflect the latest research, practices, and industry standards as well as the authors' firsthand experience. Readers can turn to the book for: Basic foundation of risk management principles, practices, and applications Tested and proven tools and methods for managing risk in pharmaceutical and biopharmaceutical product manufacturing processes Recent FDA guidelines, EU regulations, and international standards governing the application of risk management to drug manufacturing Case studies and detailed examples demonstrating the use and results of applying risk management principles to drug product manufacturing Bibliography and extensive references leading to the literature and helpful resources in the field With its unique focus on the application of risk management to biopharmaceutical and pharmaceutical manufacturing, this book is an essential resource for pharmaceutical and process engineers as well as safety and compliance professionals involved in drug manufacturing. |
| data management in pharmaceutical industry: Advances in Pharma Business Management and Research Lars Schweizer, Theodor Dingermann, Otto Quintus Russe, 2020-10-09 This open access book presents a unique collection of practical examples from the field of pharma business management and research. It covers a wide range of topics such as: 'Brexit and its Impact on pharmaceutical Law - Implications for Global Pharma Companies', 'Implementation of Measures and Sustainable Actions to Improve Employee's Engagement', 'Global Medical Clinical and Regulatory Affairs (GMCRA)', and 'A Quality Management System for R&D Project and Portfolio Management in a Pharmaceutical Company'. The chapters are summaries of master's theses by high potential Pharma MBA students from the Goethe Business School, Frankfurt/Main, Germany, with 8-10 years of work experience and are based on scientific know-how and real-world experience. The authors applied their interdisciplinary knowledge gained in 22 months of studies in the MBA program to selected practical themes drawn from their daily business. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors. |
| data management in pharmaceutical industry: Introduction to Information Systems R. Kelly Rainer, Efraim Turban, 2008-01-09 WHATS IN IT FOR ME? Information technology lives all around us-in how we communicate, how we do business, how we shop, and how we learn. Smart phones, iPods, PDAs, and wireless devices dominate our lives, and yet it's all too easy for students to take information technology for granted. Rainer and Turban's Introduction to Information Systems, 2nd edition helps make Information Technology come alive in the classroom. This text takes students where IT lives-in today's businesses and in our daily lives while helping students understand how valuable information technology is to their future careers. The new edition provides concise and accessible coverage of core IT topics while connecting these topics to Accounting, Finance, Marketing, Management, Human resources, and Operations, so students can discover how critical IT is to each functional area and every business. Also available with this edition is WileyPLUS - a powerful online tool that provides instructors and students with an integrated suite of teaching and learning resources in one easy-to-use website. The WileyPLUS course for Introduction to Information Systems, 2nd edition includes animated tutorials in Microsoft Office 2007, with iPod content and podcasts of chapter summaries provided by author Kelly Rainer. |
| data management in pharmaceutical industry: The Clinical Research Process in the Pharmaceutical Industry Gary M. Matoren, 2020-08-18 This book examines the sequence of events and methodology in the industrial clinical research process; a reference for multidisciplinary personnel. It is the conceptual framework involving the philosophical, economic, political, historical, regulatory, planning, and marketing aspects of the process. |
| data management in pharmaceutical industry: Validating Clinical Trial Data Reporting with SAS Carol I. Matthews, Brian C. Shilling, 2008 This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration. |
| data management in pharmaceutical industry: Global Supply Chains in the Pharmaceutical Industry Nozari, Hamed, Szmelter, Agnieszka, 2018-11-09 In a rapidly growing global economy, where there is a constant emergence of new business models and dynamic changes to the business ecosystem, there is a need for the integration of traditional, new, and hybrid concepts in the complex structure of supply chain management. Within the fast-paced pharmaceutical industry, product strategy, life cycles, and distribution must maintain the highest level of agility. Therefore, organizations need strong supply chain capabilities to profitably compete in the marketplace. Global Supply Chains in the Pharmaceutical Industry provides innovative insights into the efforts needed to build and maintain a strong supply chain network in order to achieve efficient fulfillment of demand, drive outstanding customer value, enhance organizational responsiveness, and build network resiliency. This publication is designed for supply chain managers, policymakers, researchers, academicians, and students, and covers topics centered on economic cycles, sustainable development, and new forces in the global economy. |
| data management in pharmaceutical industry: Research and Development in the Pharmaceutical Industry (A CBO Study) Congressional Budget Office, 2013-06-09 Perceptions that the pace of new-drug development has slowed and that the pharmaceutical industry is highly profitable have sparked concerns that significant problems loom for future drug development. This Congressional Budget Office (CBO) study-prepared at the request of the Senate Majority Leader-reviews basic facts about the drug industry's recent spending on research and development (R&D) and its output of new drugs. The study also examines issues relating to the costs of R&D, the federal government's role in pharmaceutical research, the performance of the pharmaceutical industry in developing innovative drugs, and the role of expected profits in private firms' decisions about investing in drug R&D. In keeping with CBO's mandate to provide objective, impartial analysis, the study makes no recommendations. David H. Austin prepared this report under the supervision of Joseph Kile and David Moore. Colin Baker provided valuable consultation... |
| data management in pharmaceutical industry: The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry Stephanie K. Ashenden, 2021-04-23 The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient's life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. - Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research - Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved - Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide |
| data management in pharmaceutical industry: Global Clinical Trials Richard Chin, Menghis Bairu, 2011-05-06 This book will explore the great opportunities and challenges which exist in conducting clinical trials in developing countries. By exploring the various regulations specific to the major players and providing insight into the logistical challenges including language barriers, this book provides a working tool for clinical researchers and administrators to navigate the intricacies of clinical trials in developing countries. Important topics such as ethical issues will be handled very carefully to highlight the significant differences of conducting this work in various jurisdictions. Overall, it will present a clear and comprehensive guide to the ins-and-outs of clinical trials in various countries to assist in design, development, and effectiveness of these trials. - Contributors include high-profile, respected figures who have paved the way for clinical trials in developing countries - Provides hands-on tools for regulatory and legal requirements and qualification, design, management, and reporting - Case studies outline successes, failures, lessons learned and prospects for future collaboration - Includes country-specific guidelines for the most utilized countries - Foreword by David Feigel, former Head of CDRH at FDA |
| data management in pharmaceutical industry: Data Integrity and Data Governance R. D. McDowall, 2018-11-09 This book provides practical and detailed advice on how to implement data governance and data integrity for regulated analytical laboratories working in the pharmaceutical and allied industries. |
| data management in pharmaceutical industry: Portfolio, Program, and Project Management in the Pharmaceutical and Biotechnology Industries Pete Harpum, 2011-09-20 This book describes the way that pharmaceutical projects and programs are currently managed, and offers views from many highly experienced practitioners from within the industry on future directions for drug program management. The book integrates portfolio, program, and project management processes as fundamental for effective and efficient drug product development. Contributing expert authors provide their view of how the projectization approach can be taken forward by the drug industry over the coming years. |
| data management in pharmaceutical industry: Application of Project Management Principles to the Management of Pharmaceutical R&D Projects Thomas Catalano, 2020-11-05 Dr. Catalano has for the last ten years been doing consulting for the Pharmaceutical Industry. During his consulting he discovered that small businesses such as, generic, startups, and virtual companies do not have the budget or the resources to apply the computer software utilized in project management and therefore do not apply project management principles in their business model. This reduces their effectiveness and increases their operating cost. Application of Project Management Principles to the Management of Pharmaceutical R&D Projects is presented as a paper-based system for completing all the critical activities needed apply the project management system. This will allow these small business to take advantage of the project management principles and gain all the advantages of the system. This book will be beneficial for beginners to understand the concepts of project management and for small pharmaceutical companies to apply the principles of project management to their business model. |
| data management in pharmaceutical industry: Management of Data in Clinical Trials Eleanor McFadden, 2007-12-14 A valuable new edition of the trusted, practical guide to managing data in clinical trials Regardless of size, type, or complexity, accurate results for any clinical trial are ultimately determined by the quality of the collected data. Management of Data in Clinical Trials, Second Edition explores data management and trial organization as the keys to developing an accurate and reliable clinical trial. With a focus on the traditional aspects of data collection as well as recent advances in technology, this new edition provides a complete and accessible guide to the management structure of a clinical trial, from planning and development to design and analysis. Practical approaches that result in the collection of complete and timely data are also provided. While maintaining a comprehensive overview of the knowledge and tools that are essential for the organization of a modern clinical trial, the author has expanded the topical coverage in the Second Edition to reflect the possible uses of recent advances in technology in the data collection process. In addition, the Second Edition discusses the impact of international regulations governing the conduct of clinical trials and provides guidelines on ensuring compliance with national requirements. Newly featured topics include: The growing availability of off-the-shelf solutions for clinical trials Potential models for collaboration in the conduct of clinical trials between academia and the pharmaceutical industry The increasing use of the Internet in the collection of data and management of trials Regulatory requirements worldwide and compliance with the ICH Good Clinical Practice (GCP) Guidelines Development of Standard Operating Procedures for the conduct of clinical trials Complete with chapter summaries that reinforce key points as well as over one hundred examples, Management of Data in Clinical Trials, Second Edition is an ideal resource for practitioners in the clinical research community who are involved in the development of clinical trials, including data managers, research associates, data coordinators, physicians, and statisticians. This book also serves as an excellent supplemental text for courses in clinical trials at both the undergraduate and graduate levels. |
| data management in pharmaceutical industry: Fundamentals of Clinical Data Science Pieter Kubben, Michel Dumontier, Andre Dekker, 2018-12-21 This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience. |
| data management in pharmaceutical industry: Lattice Deepayan Sarkar, 2008-02-15 Written by the author of the lattice system, this book describes lattice in considerable depth, beginning with the essentials and systematically delving into specific low levels details as necessary. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed. The book contains close to 150 figures produced with lattice. Many of the examples emphasize principles of good graphical design; almost all use real data sets that are publicly available in various R packages. All code and figures in the book are also available online, along with supplementary material covering more advanced topics. |
| data management in pharmaceutical industry: Trends and Innovations in Information Systems and Technologies Álvaro Rocha, Hojjat Adeli, Luís Paulo Reis, Sandra Costanzo, Irena Orovic, Fernando Moreira, 2020-05-18 This book gathers selected papers presented at the 2020 World Conference on Information Systems and Technologies (WorldCIST’20), held in Budva, Montenegro, from April 7 to 10, 2020. WorldCIST provides a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences with and challenges regarding various aspects of modern information systems and technologies. The main topics covered are A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications. |
| data management in pharmaceutical industry: Pharmaceutical Operations Management Pankaj Mohan, Jarka Glassey, Gary A. Montague, 2006-03-16 Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. This book brings together a winning team of international operations experts to set the framework for building a world-class manufacturing organization. Pharmaceutical Operations Management focuses on key concepts such as: Policy Execution, Risk Management, Supply chain modeling, Advance process control and Six Sigma for the pharmaceutical industry: critical techniques which will offset cost, increase efficiency and turn any manufacture into financial winner. |
| data management in pharmaceutical industry: Open Source Software in Life Science Research Lee Harland, Mark Forster, 2012-10-31 The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an 'omics' platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems |
| data management in pharmaceutical industry: Improving and Accelerating Therapeutic Development for Nervous System Disorders Institute of Medicine, Board on Health Sciences Policy, Forum on Neuroscience and Nervous System Disorders, 2014-02-06 Improving and Accelerating Therapeutic Development for Nervous System Disorders is the summary of a workshop convened by the IOM Forum on Neuroscience and Nervous System Disorders to examine opportunities to accelerate early phases of drug development for nervous system drug discovery. Workshop participants discussed challenges in neuroscience research for enabling faster entry of potential treatments into first-in-human trials, explored how new and emerging tools and technologies may improve the efficiency of research, and considered mechanisms to facilitate a more effective and efficient development pipeline. There are several challenges to the current drug development pipeline for nervous system disorders. The fundamental etiology and pathophysiology of many nervous system disorders are unknown and the brain is inaccessible to study, making it difficult to develop accurate models. Patient heterogeneity is high, disease pathology can occur years to decades before becoming clinically apparent, and diagnostic and treatment biomarkers are lacking. In addition, the lack of validated targets, limitations related to the predictive validity of animal models - the extent to which the model predicts clinical efficacy - and regulatory barriers can also impede translation and drug development for nervous system disorders. Improving and Accelerating Therapeutic Development for Nervous System Disorders identifies avenues for moving directly from cellular models to human trials, minimizing the need for animal models to test efficacy, and discusses the potential benefits and risks of such an approach. This report is a timely discussion of opportunities to improve early drug development with a focus toward preclinical trials. |
| data management in pharmaceutical industry: Drug Safety Data: How to Analyze, Summarize and Interpret to Determine Risk Michael J. Klepper, Barton Cobert, 2010-09-15 Drug Safety Data: How to Analyze, Summarize and Interpret to Determine Risk was selected for The First Clinical Research Bookshelf - Essential reading for clinical research professionals by the Journal of Clinical Research Best Practices. Drug Safety Data: How to Analyze, Summarize and Interpret to Determine Risk provides drug safety/pharmacovogilance professionals, pharmaceutical and clinical research scientists, statisticians, programmers, medical writers, and technicians with an accessible, practical framework for the analysis, summary and interpretation of drug safety data. The only guide of its kind, Drug Safety Data: How to Analyze, Summarize and Interpret to Determine Risk is an invaluable reference for pre- and post-marketing risk assessment. With decades of pharmaceutical research and drug safety expertise, authors Dr. Klepper and Dr. Cobert discuss how quality planning, safety training, and data standardization result in significant cost, time, and resource savings. Through illustrative, step-by-step instruction, Drug Safety Data: How to Analyze, Summarize and Interpret to Determine Risk is the definitive guide to drug safety data analysis and reporting. Key features include: * Step-by-step instruction on how to analyze, summarize and interpret safety data for mandatory governmental safety reports * Pragmatic tips...and mistakes to avoid * Simple explanations of what safety data are collected, and what the data mean * Practical approaches to determining a drug effect and understanding its clinical significance * Guidance for determining risk throughout the lifecycle of a drug, biologic or nutraceutical * Examples of user-friendly data displays that enhance safety signal identification * Ways to improve data quality and reduce the time, resources and costs involved in mandatory safety reporting * Relevant material for the required training of drug safety/pharmacovigilance professionals * SPECIAL FEATURE: Actual examples of an Integrated Analysis of Safety (IAS) -used in the preparation of the Integrated Summary of Safety (ISS) and the Summary of Clinical Safety (SCS) reports -, and the Periodic Safety Update Report (PSUR) |
| data management in pharmaceutical industry: Designing Sustainable Technologies, Products and Policies Enrico Benetto, Kilian Gericke, Mélanie Guiton, 2018-07-03 This open access book provides insight into the implementation of Life Cycle approaches along the entire business value chain, supporting environmental, social and economic sustainability related to the development of industrial technologies, products, services and policies; and the development and management of smart agricultural systems, smart mobility systems, urban infrastructures and energy for the built environment. The book is based on papers presented at the 8th International Life Cycle Management Conference that took place from September 3-6, 2017 in Luxembourg, and which was organized by the Luxembourg Institute of Science and Technology (LIST) and the University of Luxembourg in the framework of the LCM Conference Series. |
| data management in pharmaceutical industry: Feature Papers Michael Henson, 2018-10-04 This book is a printed edition of the Special Issue Feature Papers that was published in Processes |
| data management in pharmaceutical industry: Data Integrity and Data Governance R D McDowall, 2018-11-06 Data integrity is the hottest topic in the pharmaceutical industry. Global regulatory agencies have issued guidance, after guidance after guidance in the past few years, most of which does not offer practical advice on how to implement policies, procedures and processes to ensure integrity. These guidances state what but not how. Additionally, key stages of analysis that impact data integrity are omitted entirely. The aim of this book is to provide practical and detailed help on how to implement data integrity and data governance for regulated analytical laboratories working in or for the pharmaceutical industry. It provides clarification of the regulatory issues and trends, and gives practical methods for meeting regulatory requirements and guidance. Using a data integrity model as a basis, the principles of data integrity and data governance are expanded into practical steps for regulated laboratories to implement. The author uses case study examples to illustrate his points and provides instructions for applying the principles of data integrity and data governance to individual laboratory needs. This book is a useful reference for analytical chemists and scientists, management and senior management working in regulated laboratories requiring either an understanding about data integrity or help in implementing practical solutions. Consultants will also benefit from the practical guidance provided. |
| data management in pharmaceutical industry: Good Research Practice in Non-Clinical Pharmacology and Biomedicine Anton Bespalov, Martin C. Michel, Thomas Steckler, 2020-01-01 This open access book, published under a CC BY 4.0 license in the Pubmed indexed book series Handbook of Experimental Pharmacology, provides up-to-date information on best practice to improve experimental design and quality of research in non-clinical pharmacology and biomedicine. |
| data management in pharmaceutical industry: An Industrial IoT Approach for Pharmaceutical Industry Growth Valentina Emilia Balas, Vijender Kumar Solanki, Raghvendra Kumar, 2020-05-15 An Industrial IoT Approach for Pharmaceutical Industry Growth, Volume Two uses an innovative approach to explore how the Internet of Things (IoT) and big data can improve approaches and make discoveries. Rapid growth of the IoT has encouraged many companies in the manufacturing sector to make use of this technology to unlock its potential. Using clear language and real-world case studies, this book discusses systems level from both a human-factors point-of-view and the perspective of networking, databases, privacy and anti-spoofing. The wide variety in topics presented offers multiple perspectives on how to integrate the Internet of Things into pharmaceutical manufacturing.This book represents a useful resource for researchers in pharmaceutical sciences, information and communication technologies, and those who specialize in healthcare and pharmacovigilance. - Emphasizes efficiency in pharmaceutical manufacturing through an IoT/Big Data approach - Explores cutting-edge technologies through sensor enabled environments in the pharmaceutical industry - Discusses system levels from both a human-factors point-of-view and the perspective of networking, databases, privacy and anti-spoofing |
| data management in pharmaceutical industry: Business Chemistry Jens Leker, Carsten Gelhard, Stephan von Delft, 2018-02-20 Business Chemistry: How to Build and Sustain Thriving Businesses in the Chemical Industry is a concise text aimed at chemists, other natural scientists, and engineers who want to develop essential management skills. Written in an accessible style with the needs of managers in mind, this book provides an introduction to essential management theory, models, and practical tools relevant to the chemical industry and associated branches such as pharmaceuticals and consumer goods. Drawing on first-hand management experience and in-depth research projects, the authors of this book outline the key topics to build and sustain businesses in the chemical industry. The book addresses important topics such as strategy and new business development, describes global trends that shape chemical companies, and looks at recent issues such as business model innovation. Features of this practitioner-oriented book include: Eight chapters covering all the management topics relevant to chemists, other natural scientists and engineers. Chapters co-authored by experienced practitioners from companies such as Altana, A.T. Kearney, and Evonik Industries. Featured examples and cases from the chemical industry and associated branches throughout chapters to illustrate the practical relevance of the topics covered. Contemporary issues such as business model design, customer and supplier integration, and business co-operation. |
| data management in pharmaceutical industry: Sharing Clinical Research Data Institute of Medicine, Board on Health Care Services, Board on Health Sciences Policy, Roundtable on Translating Genomic-Based Research for Health, National Cancer Policy Forum, Forum on Neuroscience and Nervous System Disorders, Forum on Drug Discovery, Development, and Translation, 2013-06-07 Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and low-hanging fruit opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances. |
| data management in pharmaceutical industry: Statistics In the Pharmaceutical Industry C. Ralph Buncher, Jia-Yeong Tsay, 2019-03-07 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. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a T…
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, …
Belmont Forum Adopts Open Data Principles for Environment…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management …
Belmont Forum Data Accessibility Statement and …
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to …
