Encyclopedia of Biopharmaceutical Statistics, Third Edition / Edition 3

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Overview

In recent years, there has been an explosive growth of biopharmaceutical and clinical research, including the development of new medicines for treating severe or life-threatening diseases. Biopharmaceutical statistics plays an extremely important role in ensuring not only the efficacy and safety of the medicine under investigation, but also that the pharmaceutical product possesses good drug characteristics, such as identity, strength, purity, quality, stability, and reproducibility. Widely used by pharmaceutical scientists, clinical researchers, and biostatistics, the Encyclopedia of Biopharmaceutical Statistics, Third Edition is an essential resource on the evolving state of this important field.

New to the Third Edition

  • 89 new chapters, bringing the total number of chapters to 230
  • Updated information on changes in regulatory requirements for drug review/approval processes
  • Recent developments in statistical design and methodology
  • Important topics, including adaptive design in clinical research, translational medicine, statistical genetics, biomarker development, target clinical trials, follow-on biologics, and traditional Chinese medicine
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Editorial Reviews

From The Critics
Reviewer: Rahmat M. Talukder, PhD, RPh (West Coast University School of Pharmacy)
Description: This two-volume compendium focuses on the application of statistical principles to clinical research and design and development of biopharmaceutical products. This edition is considerably revised and updated in the area of regulatory requirements pertaining to the drug approval process. The 230 self-contained chapters, with more than 600 tables and figures, are arranged alphabetically to provide ready access to the respective topics.
Purpose: The essential objectives are to elucidate recent developments in statistical analysis and show how statistical designs and methodologies can be applied in demonstrating safety, efficacy, and quality of drug products. Development of a new drug product and optimization of its processing, manufacturing, quality control, and therapeutic efficacy is often a challenging and complex task. Undoubtedly the use of a suitable statistical design and methodology, at least in part, can help reduce the overall time and cost of the drug development process. In that respect, this is an excellent resource for anyone interested in learning the application of statistical concepts, tests, and analytical methods to pharmaceutical research projects. The second edition was well received by pharmaceutical scientists, and this updated edition will be as well.
Audience: This is an excellent reference for researchers and scientists working in the pharmaceutical industry, clinical sciences, and academia. Members of regulatory agencies who are actively involved in the drug review and approval process also will find this an extremely helpful resource. The editor is well known for his expertise in pharmaceutical statistics, and over 280 scholars, scientists, and statisticians from academia, industry, and regulatory agencies, some of whom are internationally recognized experts in their fields, have contributed to this compendium.
Features: This edition adds many new chapters to reflect current regulatory requirements in the drug approval process and the development of new statistical methods and their applications in pharmaceutical sciences. Chapters of particular interest to pharmaceutical scientists cover topics such as adaptive design methods in clinical trials, adaptive survival tests, stability analysis for frozen drug products, equivalence trials, statistical genetics, targeted clinical trials, and USP tests. Moreover, applications of statistical principles to pharmaceutical product development are illustrated with examples that readers with a moderate statistical background should have no difficulty comprehending.
Assessment: This is a comprehensive reference source of statistical principles, design, and methodology applicable to translational medicine, clinical research, and pharmaceutical research. This is an important resource for pharmaceutical product development scientists and members of regulatory agencies who apply statistical principles in their work. There are other references on statistical sciences in the marketplace, but none provides relevant information, especially on the application of statistical principles to the pharmaceutical sciences, as concisely as this one does.
Doody Reviews
Reviewer: Rahmat M Talukder, Ph.D. (Southwestern Oklahoma State University College of Pharmacy)
Description: This two-volume compendium focuses on the application of statistical principles to clinical research and design and development of biopharmaceutical products. This edition is considerably revised and updated in the area of regulatory requirements pertaining to the drug approval process. The 230 self-contained chapters, with more than 600 tables and figures, are arranged alphabetically to provide ready access to the respective topics.
Purpose: The essential objectives are to elucidate recent developments in statistical analysis and show how statistical designs and methodologies can be applied in demonstrating safety, efficacy, and quality of drug products. Development of a new drug product and optimization of its processing, manufacturing, quality control, and therapeutic efficacy is often a challenging and complex task. Undoubtedly the use of a suitable statistical design and methodology, at least in part, can help reduce the overall time and cost of the drug development process. In that respect, this is an excellent resource for anyone interested in learning the application of statistical concepts, tests, and analytical methods to pharmaceutical research projects. The second edition was well received by pharmaceutical scientists, and this updated edition will be as well.
Audience: This is an excellent reference for researchers and scientists working in the pharmaceutical industry, clinical sciences, and academia. Members of regulatory agencies who are actively involved in the drug review and approval process also will find this an extremely helpful resource. The editor is well known for his expertise in pharmaceutical statistics, and over 280 scholars, scientists, and statisticians from academia, industry, and regulatory agencies, some of whom are internationally recognized experts in their fields, have contributed to this compendium.
Features: This edition adds many new chapters to reflect current regulatory requirements in the drug approval process and the development of new statistical methods and their applications in pharmaceutical sciences. Chapters of particular interest to pharmaceutical scientists cover topics such as adaptive design methods in clinical trials, adaptive survival tests, stability analysis for frozen drug products, equivalence trials, statistical genetics, targeted clinical trials, and USP tests. Moreover, applications of statistical principles to pharmaceutical product development are illustrated with examples that readers with a moderate statistical background should have no difficulty comprehending.
Assessment: This is a comprehensive reference source of statistical principles, design, and methodology applicable to translational medicine, clinical research, and pharmaceutical research. This is an important resource for pharmaceutical product development scientists and members of regulatory agencies who apply statistical principles in their work. There are other references on statistical sciences in the marketplace, but none provides relevant information, especially on the application of statistical principles to the pharmaceutical sciences, as concisely as this one does.
From The Critics
Reviewer: Rahmat M Talukder, PhD (Pharmaceu, BS in Pharmacy(West Coast University School of Pharmacy)
Description: This two-volume compendium focuses on the application of statistical principles to clinical research and design and development of biopharmaceutical products. This edition is considerably revised and updated in the area of regulatory requirements pertaining to the drug approval process. The 230 self-contained chapters, with more than 600 tables and figures, are arranged alphabetically to provide ready access to the respective topics.
Purpose: The essential objectives are to elucidate recent developments in statistical analysis and show how statistical designs and methodologies can be applied in demonstrating safety, efficacy, and quality of drug products. Development of a new drug product and optimization of its processing, manufacturing, quality control, and therapeutic efficacy is often a challenging and complex task. Undoubtedly the use of a suitable statistical design and methodology, at least in part, can help reduce the overall time and cost of the drug development process. In that respect, this is an excellent resource for anyone interested in learning the application of statistical concepts, tests, and analytical methods to pharmaceutical research projects. The second edition was well received by pharmaceutical scientists, and this updated edition will be as well.
Audience: This is an excellent reference for researchers and scientists working in the pharmaceutical industry, clinical sciences, and academia. Members of regulatory agencies who are actively involved in the drug review and approval process also will find this an extremely helpful resource. The editor is well known for his expertise in pharmaceutical statistics, and over 280 scholars, scientists, and statisticians from academia, industry, and regulatory agencies, some of whom are internationally recognized experts in their fields, have contributed to this compendium.
Features: This edition adds many new chapters to reflect current regulatory requirements in the drug approval process and the development of new statistical methods and their applications in pharmaceutical sciences. Chapters of particular interest to pharmaceutical scientists cover topics such as adaptive design methods in clinical trials, adaptive survival tests, stability analysis for frozen drug products, equivalence trials, statistical genetics, targeted clinical trials, and USP tests. Moreover, applications of statistical principles to pharmaceutical product development are illustrated with examples that readers with a moderate statistical background should have no difficulty comprehending.
Assessment: This is a comprehensive reference source of statistical principles, design, and methodology applicable to translational medicine, clinical research, and pharmaceutical research. This is an important resource for pharmaceutical product development scientists and members of regulatory agencies who apply statistical principles in their work. There are other references on statistical sciences in the marketplace, but none provides relevant information, especially on the application of statistical principles to the pharmaceutical sciences, as concisely as this one does.
Read More Show Less

Product Details

  • ISBN-13: 9781439822456
  • Publisher: Taylor & Francis
  • Publication date: 4/15/2010
  • Edition number: 3
  • Pages: 1504
  • Product dimensions: 8.80 (w) x 11.30 (h) x 3.50 (d)

Table of Contents

Acceptance Sampling

Active Control Trials

Adaptive Design Methods in Clinical Trials

Adaptive Survival Trials

Adjustment for Covariates

Adverse Event Reporting

Alpha Spending Function

Ames Test

Analysis of 2 K Tables

Analysis of Clustered Binary Data

Analysis of Clustered Categorical Data

Analysis of Heritability

Analysis of Repeated Measures Data with Missing Values: An Overview of Methods

Analysis of Variance

ANCOVA Approach for Premarketing Shelf Life Determination with Multiple Factors

Assay Development

Assay Validation

Bayesian Approach to Stability Analysis

Bayesian Methods in Meta-Analysis

Bayesian Statistics

Bayesian Designs for Phase II Oncology Clinical Trials

Binary 2 × 2 Crossover Trials

Bioassay

Bioavailability and Bioequivalence

Bioinformatics

Biologics

Biomarker in Clinical Trials

Biopharmaceutics

Biosimilarity of Follow-On Biologics

Blinding

Bootstrap, The

Bracketing Design

Bridging Studies

Calibration

Canadian Health Products and Food Branch (HPFB) and Therapeutic Products Directorate (TPD)

Cancer Trials

Carcinogenicity Studies of Pharmaceuticals

Carry‐Forward Analysis

Case-Control Studies, Inference in

Center Weighting in Multicenter Trials

Clinical Data Management

Clinical Endpoint

Clinical Pharmacology

Clinical Trial Process

Clinical Trial Simulation

Clinical Trial Simulations for Earlier Development Phases

Clinical Trial Simulations for Later Development Phases

Clinical Trials

Cluster Trials

Clustered Study Designs: Power Analysis

Combination Drug Clinical Trial

Comparing Variabilities in Clinical Research

Confidence Interval and Hypothesis Testing

Confounding and Interaction

Content Uniformity

Contract Research Organization (CRO)

Correlated Probit Model

Cost-Effectiveness Analysis

Covariate-Adjusted Adaptive Dose-Finding in Early Phase Clinical Trials

Crossover Design

Cutoff Designs

Data Mining and Biopharmaceutical Research

Data Monitoring Committees (DMC)

Design and Analysis for Demonstrating Disease Modification Effects

Diagnostic Imaging

Dose Proportionality

Dose Response Analysis in Clinical Trials

Dose Response Study Design

Dropout

Drug Development

Ecologic Inference

ED50/ED90

Enrichment Design

Equivalence Trials

Ethnic Factors

Evaluation of Linearity in Assay Validation

Expiration Dating Period

Exploratory Factor Analysis

Extra Variation Models

Factor Analysis

Factorial Designs

Failure‐Time Model

False Discovery Rate (FDR)

Food and Drug Administration

Generalizability Probability in Clinical Research

Generalized Estimating Equation

Generalized Estimating Equations (GEE) Method: Sample Size Estimation

Generalized Inference

Genetic Linkage and Linkage Disequilibrium Analysis

Global Database and System

Good Clinical Practice

Good Programming Practice

Good Statistics Practice

Group Sequential Methods

Group Sequential Tests and Variance Heterogeneity in Clinical Trials

Hypotheses and False Positive Rate in Active ControlNon-Inferiority Trials

Hypothesis Testing

Imputation in Clinical Research

Imputation with Item Nonrespondents

In Vitro Bioequivalence Testing

In Vitro Dissolution Profile Comparison

In Vitro Micronucleus Test

Individual Bioequivalence

Instrument Development and Validation

Integrated Summary Report

Intention‐to‐Treat Analyses (ITT)

Interim Analysis

International Conference on Harmonization (ICH)

Investigating Quality‐of‐Life in Clinical Trials

IVRS/IWRS for Randomization

Kaplan–Meier Estimator

Kappa Coefficients in Medical Research

Kullback–Leibler Divergence for Evaluating Equivalence

Laboratory Analyses

Latent Class Analysis

Lilly Reference Ranges

Local Influence Analysis

Logistic Regression

Logistic Regression in Three‐Point Designs

Maximum Tolerable Dose for Cancer Chemotherapy

McNemar's Test

Measuring Agreement

MedDRA and Its Impact on Pharmaceutical Development

Medical Devices

Meta-Analysis of Therapeutic Trials

Microarray Gene Expression

Minimization Procedure

Minimum Effective Dose

Ministry of Health, Labour and Welfare and Pharmaceutical Administration in Japan

Missing Values in Repeated Measurement Designs

Mixed Effects Models

Mixed-Outcome Data

MMRM with Missing Data

Modified Large Sample Method

Multicenter Trials

Multicollinearity

Multidimensional Data Analysis: An Overview of Penalized Regression Methods

Multinational Clinical Trial

Multiple Comparisons

Multiple‐Dose Bioequivalence Studies

Multiple Endpoints

Multiple-Stage Designs for Phase II Cancer Trials

Multiplicity in Clinical Trials

Multivariate Meta-Analysis

Noninferiority Analysis in Active Controlled Clinical Trials

Non-Parametric Regression

Odds Ratio

Onset of Action

Ordered Multiple Class Receiver Operating Characteristic (ROC) Analysis

Outlier Detection in Clinical Research

P-Values

P-Values, Evidence, and Multiplicity Considerations for Controlled Clinical Trials

Parallel Design

Patient Compliance

Percentile Charts on Correlated Measures

Pharmacodynamic Issues

Pharmacodynamics with Covariates

Pharmacodynamics with No Covariates

Pharmacoeconomics

Phase I Cancer Clinical Trials

Placebo Effect

Population Bioequivalence

Population PK/PD Analysis

Postmarketing Adverse Drug Event Signaling

Postmarketing Surveillance

Power

Prediction Trees

Principal Component Analysis

Prior Effective Sample Size of a Bayesian Model

Process Validation

Profile Analysis

Propensity Score Analysis and Its Application in Regulatory Settings

Proportion of Treatment Effect

Proportional Hazards Regression Model

Protocol Development

QT Analysis

Randomization

Rank-Based Robust Analysis for Crossover Design

Rank Regression in Stability Analysis

Release Targets

Reliability

Reproducibility Probability in Clinical Research

Reproductive/Developmental Studies

Response-Adaptive Designs

Response-Adaptive Repeated Measurement Designs for Clinical Trials

Response Surface Methodology

Risk Ratio Analysis

ROC Curve

Sample Size Calculation Based on Nonparametric Statistics

Sample Size Calculation for Survival Data

Sample Size Determination

Sample Size Re‐Estimation Based on Observed Treatment Difference

Screening Design

Selection of Control in Clinical Trials

Semi-Parametric Time-Varying Regression Models

Sequential Estimation for the Additive Hazards Rate Model with Staggered Entry

Slope Approach for Assessment of Dose Proportionality/Linearity under a Crossover Design

Spatio-Temporal Modeling

Specifications

SROC Curve

Stability Analysis for Frozen Drug Products

Stability Matrix Designs

Statistical Genetics

Statistical Principles for Clinical Trials

Statistical Process Control

Statistical Significance

Statistical Tests for Biomarker Development with Applications to Genetics Data

Structural Equation Model

Stuart–Maxwell Test

Subgroup Analysis

Subject-Treatment Interaction

Surrogate Endpoint

Survival Analysis

Targeted Clinical Trials

Test for Ordered Categorical Data

Testing for Qualitative Interaction

Therapeutic Equivalence

Titration Design

Toxicological Studies

Traditional Chinese Medicine—General Consideration

Translational Medicine: Concepts, Statistical Methods, and Related Issues

Trend Estimation

Two-Stage Design: Phase II Cancer Clinical Trials

USP Tests

Vaccine Clinical Trials

Validation of Quantitative and Qualitative Assays

Validity of LOCF

Z-Score

Zero-Inflated Poisson Distribution

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