Pharmaceutical Research Methodology & Bio-Statistics
Pharmaceutical Research Methodology & Bio-Statistics

Author: Subba Bayya Rao

Publisher: Pharmamed Press

Published: 2023-05

Total Pages: 0

ISBN-13: 9789395039345

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"Pharmaceutical Research Methodology and Bio-Statistics: Theory and Practice" is aimed in understanding the fundamental concepts of developing a research bent of mind by careful planning, execution, collection of data and analyzing for statistical significance. The book is aimed at B. Pharm, Pharm D, Pharm D (PB), M. Pharm, allied course students, researchers at the academic and industry levels, Ph. D scholars, policy makers, regulators etc. Key Features: - Distinguishing statistics and bio-statistics - How to identify a problem, plan for research and execute the idea - Chemical abstract literature search - Anatomy of a research paper - Compare and contrast of research proposal, research report, research paper, patent document, synopsis - Concept of meta-analysis to resolve research ambiguities - Data collection, cleansing, presenting - How to overcome missing data - Introduction to Probability, Permutations and Combinations - Parametric distributions - binomial, poisson, normal, chi-square, student 't', F distributions - Extra information on Bernoulli Distribution and Chebyshev's Theorem - Role of Type I and Type II errors, Power, sample size, confidence level, confidence interval, confidence limits - How to judge whether data upon analysis is statistical significant or not - Developing hypothesis as null, alternate and how to draw conclusion after conducting suitable statistical test - Non-parametric statistical test - Run, Sign, Wilcoxon Signed rank, Wilcoxon rank sum tests - Parametric, Non-parametric ANOVAs (1-way with multiple comparisons, 2-way, cross over, 3-way) - Step wise Parametric and non-parametric problem solving - Applications of linear regression and correlation coef ficient relating to pharmaceuticals - Appended with Multi-linear Regression Analysis (Mathematical and Excel Calculation)

Statistical Methodology in the Pharmaceutical Sciences
Statistical Methodology in the Pharmaceutical Sciences

Author: D. A. Berry

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 592

ISBN-13: 1482276860

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A state-of-the-art handbook of statistical analysis for use in the pharmaceutical industry. Areas covered in this reference/text include: bioavailability, repeated-measures designs, dose-response, population models, multicenter trials, handling dropouts, survival analysis, robust data analysis, cate

Statistics in Drug Research
Statistics in Drug Research

Author: Shein-Chung Chow

Publisher: CRC Press

Published: 2002-02-20

Total Pages: 412

ISBN-13: 9780203910146

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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

INTRODUCTION TO BIOSTATISTICS AND RESEARCH METHODS
INTRODUCTION TO BIOSTATISTICS AND RESEARCH METHODS

Author: P. S. S. SUNDAR RAO

Publisher: PHI Learning Pvt. Ltd.

Published: 2012-01-09

Total Pages: 279

ISBN-13: 8120345207

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The last decade has produced many textbooks on Biostatistics, with varying emphasis and degrees of mathematical complexity. This book has stood the test of time and continues to enjoy wide acceptance among students of all health and allied professions, other students and even qualified health investigators, who find it practical, simple and yet precise. This fully updated and thoroughly revised Fifth Edition, while retaining the fundamental concepts, acquaints the reader with the advances in the subject. The book explains the concepts involved in arriving at the sample size and also a quick solution to the estimation of sample size. Survival analysis and log-rank test are illustrated with examples. The essentials of Chi square tests are simplified and presented. Two-way analysis of variance (ANOVA) is explained with two examples, with and without interaction term. The chapters on Research Methods, Interventional Studies and Observational Studies provide step-by-step guide to plan and carry out quality research. Questions given in each chapter will help the learner to gauge the level of understanding of the principles and applications. Clues to the use of computer packages are provided whenever necessary. Intended for undergraduate and postgraduate medical students as well as for nursing and paramedical students, the book will also be immensely useful to medical/health faculty and researchers in the field of Biostatistics. KEY FEATURES : A new chapter on Sample Size Determination Several new sections Extensive revision of practically all chapters Provision of new examples Chapter-end exercises

Bayesian Methods in Pharmaceutical Research
Bayesian Methods in Pharmaceutical Research

Author: Emmanuel Lesaffre

Publisher: CRC Press

Published: 2020-04-15

Total Pages: 547

ISBN-13: 1351718673

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

Modern Issues and Methods in Biostatistics
Modern Issues and Methods in Biostatistics

Author: Mark Chang

Publisher: Springer Science & Business Media

Published: 2011-07-15

Total Pages: 316

ISBN-13: 144199842X

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Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.

Introduction to Statistics in Pharmaceutical Clinical Trials
Introduction to Statistics in Pharmaceutical Clinical Trials

Author: Todd A. Durham

Publisher:

Published: 2008-01-01

Total Pages: 226

ISBN-13: 9780853697145

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All students of pharmaceutical sciences and clinical research need a solid knowledge and understanding of the nature, methods, application, and importance of statistics. Introduction to Statistics in Pharmaceutical Clinical Trials is an ideal introduction to statistics presented in the context of clinical trials conducted during pharmaceutical drug development. This novel approach both teaches the computational steps needed to conduct analyses and provides a conceptual understanding of how these analyses provide information that forms the rational basis for decision making throughout the drug development process.

Quantitative Methods in Pharmaceutical Research and Development
Quantitative Methods in Pharmaceutical Research and Development

Author: Olga V. Marchenko

Publisher: Springer Nature

Published: 2020-09-24

Total Pages: 445

ISBN-13: 3030485552

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This contributed volume presents an overview of concepts, methods, and applications used in several quantitative areas of drug research, development, and marketing. Chapters bring together the theories and applications of various disciplines, allowing readers to learn more about quantitative fields, and to better recognize the differences between them. Because it provides a thorough overview, this will serve as a self-contained resource for readers interested in the pharmaceutical industry, and the quantitative methods that serve as its foundation. Specific disciplines covered include: Biostatistics Pharmacometrics Genomics Bioinformatics Pharmacoepidemiology Commercial analytics Operational analytics Quantitative Methods in Pharmaceutical Research and Development is ideal for undergraduate students interested in learning about real-world applications of quantitative methods, and the potential career options open to them. It will also be of interest to experts working in these areas.

Statistical Methods for Pharmaceutical Research Planning
Statistical Methods for Pharmaceutical Research Planning

Author: S. W. Bergman

Publisher: CRC Press

Published: 2020-10-28

Total Pages: 270

ISBN-13: 1000105520

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This book focuses on statistical methods which impinge more or less directly on the decisions that are made during the course of pharmaceutical and agro-chemical research, considering the four decision-making areas.

Essential Statistical Methods for Medical Statistics
Essential Statistical Methods for Medical Statistics

Author: J. Philip Miller

Publisher: Elsevier

Published: 2010-11-08

Total Pages: 363

ISBN-13: 0444537384

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Essential Statistical Methods for Medical Statistics presents only key contributions which have been selected from the volume in the Handbook of Statistics: Medical Statistics, Volume 27 (2009). While the use of statistics in these fields has a long and rich history, the explosive growth of science in general, and of clinical and epidemiological sciences in particular, has led to the development of new methods and innovative adaptations of standard methods. This volume is appropriately focused for individuals working in these fields. Contributors are internationally renowned experts in their respective areas. - Contributors are internationally renowned experts in their respective areas - Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research - Methods for assessing Biomarkers, analysis of competing risks - Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs - Structural equations modelling and longitudinal data analysis