Normal view MARC view ISBD view

Phase II Clinical Development of New Drugs.

By: Ting, Naitee.
Contributor(s): Chen, Ding-Geng | Ho, Shuyen | Cappelleri, Joseph C.
Material type: TextTextSeries: eBooks on Demand.ICSA Book Series in Statistics Ser: Publisher: Singapore : Springer, 2017Copyright date: ©2017Description: 1 online resource (252 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9789811041945.Subject(s): ManagementGenre/Form: Electronic books.Additional physical formats: Print version:: Phase II Clinical Development of New DrugsDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to view this ebook.
Contents:
Intro -- Preface -- Contents -- About the Authors -- 1 Introduction -- 1.1 Background -- 1.2 Non-clinical Development -- 1.2.1 Pharmacology -- 1.2.2 Toxicology/Product Safety -- 1.2.3 Formulation Development -- 1.3 Pre-marketing Clinical Development -- 1.3.1 Phase I Clinical Trials -- 1.3.2 Phase II Clinical Trials -- 1.3.3 Phase III Clinical Trials -- 1.3.4 Clinical Development for Products Treating Life-Threatening Diseases -- 1.3.5 New Drug Application/Biologics License Application -- 1.4 Clinical Development Plan -- 1.5 Patient-Centered Outcomes -- 1.5.1 Clinical Outcome Assessments -- 1.5.2 Patient-Reported Outcomes -- 1.6 Post-marketing Clinical Development -- 1.7 Product Label -- 1.8 Importance of Phase II Clinical Development -- 1.9 Highlight of Each Chapter of This Book -- References -- 2 Concept of Alpha -- 2.1 Lady Tasting Tea -- 2.2 Alpha Type I Error Rate -- 2.3 Intention-to-Treat -- 2.4 Patient Analysis Sets -- 2.5 Multiple Comparisons -- 2.5.1 Multiple Doses -- 2.5.2 Multiple Endpoints -- 2.5.2.1 Summary Measures or Summary Statistics -- 2.5.3 Other Types of Multiplicity -- 2.6 P-Value and Statistical Significance -- 2.7 Stages of a Clinical Trial -- 2.8 Subject Selection and Choice of Alpha at Phase II -- References -- 3 Confirmation and Exploration -- 3.1 Introduction -- 3.2 A Motivational Example -- 3.3 Clinical Development Plan (CDP) -- 3.4 Clinical Study Design and Sample Size Calculations -- 3.5 Statistical Analysis Plan (SAP) -- 3.6 Application Example-Another Three Group Phase III Design -- 3.7 Application Example-Dose Selection -- 3.8 Proof of Concept and Dose Ranging -- 3.9 Treatment-by-Factor Interaction -- 3.10 Evaluation of Product Safety -- 3.11 Every Clinical Trial Can Be Considered as Both Confirmatory and Exploratory -- 3.12 Conclusion -- References -- 4 Design a Proof of Concept Trial -- 4.1 Introduction.
4.2 Proof of Concept Trials -- 4.2.1 Impact of PoC Decisions -- 4.2.2 How to Communicate Risks Associated with a PoC Study -- 4.3 The Primary Endpoint in a PoC Design -- 4.4 MTD Could Be Under Estimated or Over Estimated -- 4.5 Monotonicity Assumption -- 4.5.1 Background -- 4.5.2 Strong or Weak Application of the Monotonicity Assumption -- 4.5.3 Why This Assumption Is Still Useful -- 4.6 Agreement on a Delta -- 4.7 Choice of Alpha and Beta -- 4.8 Sample Size Considerations -- References -- 5 Design of Dose-Ranging Trials -- 5.1 Background -- 5.2 Finding Minimum Effective Dose (MinED) -- 5.3 A Motivating Example -- 5.4 How Wide a Range of Doses to Study? -- 5.4.1 Definition of Dose Range in a Given Study -- 5.4.2 Binary Dose Spacing -- 5.5 Frequency of Dosing -- 5.6 Parallel Controlled Fixed Dose Designs -- 5.7 Number of Doses and Control Groups -- 5.8 MCP-Mod -- 5.9 Sample Size Considerations -- 5.10 Application Example -- 5.11 Discussion -- References -- 6 Combining Proof of Concept and Dose-Ranging Trials -- 6.1 Background -- 6.2 Considerations in Designing Combined PoC and Dose Ranging Studies -- 6.3 Concerns of Using a Dose-Response Model -- 6.4 Sample Size Allocation -- 6.4.1 Comparison of Power -- 6.5 Estimation of Dose-Response Relationship -- 6.6 Risk of Inconclusiveness -- References -- 7 Risks of Inconclusiveness -- 7.1 Introduction -- 7.2 Go/NoGo Decision in a Two-Group PoC Study -- 7.2.1 The Decision Process -- 7.2.2 The Concept of Another Delta -- 7.3 Go/NoGo Decision with Multiple Treatment Groups -- 7.4 Dose Titration Studies Cannot Be Used for Dose-Finding -- 7.5 A Practical Design to Help Finding MinED -- 7.6 Discussion -- References -- 8 Analysis of a Proof of Concept Study -- 8.1 Introduction -- 8.2 When the Primary Endpoint Is a Continuous Variable -- 8.2.1 Data Description and Hypothesis -- 8.2.2 T-Test Approach.
8.2.3 Analysis of Covariance Approach -- 8.2.4 Mixed-Effect Models to Analyze the Longitudinal Data -- 8.3 When the Primary Endpoint Is a Binary Variable -- 8.3.1 Data Description and Hypothesis -- 8.3.2 Cochran-Mantel-Haenszel Method -- 8.3.3 Logistic Regression -- 8.4 Discussion -- References -- 9 Data Analysis for Dose-Ranging Trials with Continuous Outcome -- 9.1 Introduction -- 9.2 Data and Preliminary Analysis -- 9.3 Establishing PoC with a Trend Test -- 9.4 Multiple Comparison Procedure (MCP) Approach -- 9.4.1 Fisher's Protected LSD (Fixed Sequence Test) -- 9.4.2 Bonferroni Correction -- 9.4.3 Dunnett's Test -- 9.4.4 Holm's Step-Down Procedure -- 9.4.5 Hochberg Step-Up Procedure -- 9.4.6 Gate-Keeping Procedure -- 9.5 Modeling Approach (Mod) -- 9.5.1 Dose-Response Models -- 9.5.2 R Step-by-Step Implementations -- 9.6 MCP-Mod Approach -- 9.6.1 Introduction -- 9.6.2 Step-by-Step Implementations in R Package "MCPMod" -- 9.7 Discussion -- References -- 10 Data Analysis of Dose-Ranging Trials for Binary Outcomes -- 10.1 Introduction -- 10.2 Data and Preliminary Analysis -- 10.3 Modeling Approach -- 10.3.1 Pearson's χ2-Test -- 10.3.2 Cochran-Armitage Test for Trend -- 10.3.3 Logistic Regression with Dose as Continuous Variable -- 10.3.4 Logistic Regression with Dose as Categorical Variable -- 10.4 Multiple Comparisons -- 10.4.1 The Raw p-Values -- 10.4.2 Bonferroni Adjustment -- 10.4.3 Bonferroni-Holm Procedure -- 10.4.4 Hochberg Procedure -- 10.4.5 Gatekeeping Procedure -- 10.4.6 MCP Using p-Values from Cochran-Mantel-Haenszel Test -- 10.5 Discussion -- References -- 11 Bayesian Approach -- 11.1 Introduction -- 11.1.1 An Example on Bayesian Concept -- 11.1.2 A Brief History -- 11.1.3 Bayes Theorem -- 11.1.4 Bayesian Hypothesis Testing Framework -- 11.2 Bayesian Updating -- 11.2.1 Example Continued for Bayesian Updating -- 11.3 Bayesian Inference.
11.4 Markov Chain Monte Carlo (MCMC) Method -- 11.5 Bayesian Methods for Phase II Clinical Trials -- 11.6 Example -- 11.6.1 Using Non-informative Priors -- 11.6.2 Using Informative Priors -- 11.6.3 Summary -- References -- 12 Overview of Phase III Clinical Trials -- 12.1 Introduction -- 12.2 Scope of Phase III Plans -- 12.3 Drug Label and Target Product Profile -- 12.4 Phase III Non-inferiority Trial Designs -- 12.5 Dose and Regimen Selection, Drug Formulation and Patient Populations -- 12.5.1 Dose and Regimen Selection -- 12.5.2 Drug Formulations -- 12.5.3 Patient Populations -- 12.6 Number of Phase III Trials for a Labeling Claim -- 12.7 Number of Primary Efficacy Endpoints -- 12.8 Missing Data Issues -- 12.9 Phase III Clinical Outcome Assessments -- 12.10 Multi-regional Phase III Clinical Trial Issues -- 12.11 The Trend Towards Personalized or Precision Medicines -- 12.12 Summary -- References.
Tags from this library: No tags from this library for this title. Log in to add tags.
Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
QA276-280 (Browse shelf) https://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=4840975 Available EBC4840975

Intro -- Preface -- Contents -- About the Authors -- 1 Introduction -- 1.1 Background -- 1.2 Non-clinical Development -- 1.2.1 Pharmacology -- 1.2.2 Toxicology/Product Safety -- 1.2.3 Formulation Development -- 1.3 Pre-marketing Clinical Development -- 1.3.1 Phase I Clinical Trials -- 1.3.2 Phase II Clinical Trials -- 1.3.3 Phase III Clinical Trials -- 1.3.4 Clinical Development for Products Treating Life-Threatening Diseases -- 1.3.5 New Drug Application/Biologics License Application -- 1.4 Clinical Development Plan -- 1.5 Patient-Centered Outcomes -- 1.5.1 Clinical Outcome Assessments -- 1.5.2 Patient-Reported Outcomes -- 1.6 Post-marketing Clinical Development -- 1.7 Product Label -- 1.8 Importance of Phase II Clinical Development -- 1.9 Highlight of Each Chapter of This Book -- References -- 2 Concept of Alpha -- 2.1 Lady Tasting Tea -- 2.2 Alpha Type I Error Rate -- 2.3 Intention-to-Treat -- 2.4 Patient Analysis Sets -- 2.5 Multiple Comparisons -- 2.5.1 Multiple Doses -- 2.5.2 Multiple Endpoints -- 2.5.2.1 Summary Measures or Summary Statistics -- 2.5.3 Other Types of Multiplicity -- 2.6 P-Value and Statistical Significance -- 2.7 Stages of a Clinical Trial -- 2.8 Subject Selection and Choice of Alpha at Phase II -- References -- 3 Confirmation and Exploration -- 3.1 Introduction -- 3.2 A Motivational Example -- 3.3 Clinical Development Plan (CDP) -- 3.4 Clinical Study Design and Sample Size Calculations -- 3.5 Statistical Analysis Plan (SAP) -- 3.6 Application Example-Another Three Group Phase III Design -- 3.7 Application Example-Dose Selection -- 3.8 Proof of Concept and Dose Ranging -- 3.9 Treatment-by-Factor Interaction -- 3.10 Evaluation of Product Safety -- 3.11 Every Clinical Trial Can Be Considered as Both Confirmatory and Exploratory -- 3.12 Conclusion -- References -- 4 Design a Proof of Concept Trial -- 4.1 Introduction.

4.2 Proof of Concept Trials -- 4.2.1 Impact of PoC Decisions -- 4.2.2 How to Communicate Risks Associated with a PoC Study -- 4.3 The Primary Endpoint in a PoC Design -- 4.4 MTD Could Be Under Estimated or Over Estimated -- 4.5 Monotonicity Assumption -- 4.5.1 Background -- 4.5.2 Strong or Weak Application of the Monotonicity Assumption -- 4.5.3 Why This Assumption Is Still Useful -- 4.6 Agreement on a Delta -- 4.7 Choice of Alpha and Beta -- 4.8 Sample Size Considerations -- References -- 5 Design of Dose-Ranging Trials -- 5.1 Background -- 5.2 Finding Minimum Effective Dose (MinED) -- 5.3 A Motivating Example -- 5.4 How Wide a Range of Doses to Study? -- 5.4.1 Definition of Dose Range in a Given Study -- 5.4.2 Binary Dose Spacing -- 5.5 Frequency of Dosing -- 5.6 Parallel Controlled Fixed Dose Designs -- 5.7 Number of Doses and Control Groups -- 5.8 MCP-Mod -- 5.9 Sample Size Considerations -- 5.10 Application Example -- 5.11 Discussion -- References -- 6 Combining Proof of Concept and Dose-Ranging Trials -- 6.1 Background -- 6.2 Considerations in Designing Combined PoC and Dose Ranging Studies -- 6.3 Concerns of Using a Dose-Response Model -- 6.4 Sample Size Allocation -- 6.4.1 Comparison of Power -- 6.5 Estimation of Dose-Response Relationship -- 6.6 Risk of Inconclusiveness -- References -- 7 Risks of Inconclusiveness -- 7.1 Introduction -- 7.2 Go/NoGo Decision in a Two-Group PoC Study -- 7.2.1 The Decision Process -- 7.2.2 The Concept of Another Delta -- 7.3 Go/NoGo Decision with Multiple Treatment Groups -- 7.4 Dose Titration Studies Cannot Be Used for Dose-Finding -- 7.5 A Practical Design to Help Finding MinED -- 7.6 Discussion -- References -- 8 Analysis of a Proof of Concept Study -- 8.1 Introduction -- 8.2 When the Primary Endpoint Is a Continuous Variable -- 8.2.1 Data Description and Hypothesis -- 8.2.2 T-Test Approach.

8.2.3 Analysis of Covariance Approach -- 8.2.4 Mixed-Effect Models to Analyze the Longitudinal Data -- 8.3 When the Primary Endpoint Is a Binary Variable -- 8.3.1 Data Description and Hypothesis -- 8.3.2 Cochran-Mantel-Haenszel Method -- 8.3.3 Logistic Regression -- 8.4 Discussion -- References -- 9 Data Analysis for Dose-Ranging Trials with Continuous Outcome -- 9.1 Introduction -- 9.2 Data and Preliminary Analysis -- 9.3 Establishing PoC with a Trend Test -- 9.4 Multiple Comparison Procedure (MCP) Approach -- 9.4.1 Fisher's Protected LSD (Fixed Sequence Test) -- 9.4.2 Bonferroni Correction -- 9.4.3 Dunnett's Test -- 9.4.4 Holm's Step-Down Procedure -- 9.4.5 Hochberg Step-Up Procedure -- 9.4.6 Gate-Keeping Procedure -- 9.5 Modeling Approach (Mod) -- 9.5.1 Dose-Response Models -- 9.5.2 R Step-by-Step Implementations -- 9.6 MCP-Mod Approach -- 9.6.1 Introduction -- 9.6.2 Step-by-Step Implementations in R Package "MCPMod" -- 9.7 Discussion -- References -- 10 Data Analysis of Dose-Ranging Trials for Binary Outcomes -- 10.1 Introduction -- 10.2 Data and Preliminary Analysis -- 10.3 Modeling Approach -- 10.3.1 Pearson's χ2-Test -- 10.3.2 Cochran-Armitage Test for Trend -- 10.3.3 Logistic Regression with Dose as Continuous Variable -- 10.3.4 Logistic Regression with Dose as Categorical Variable -- 10.4 Multiple Comparisons -- 10.4.1 The Raw p-Values -- 10.4.2 Bonferroni Adjustment -- 10.4.3 Bonferroni-Holm Procedure -- 10.4.4 Hochberg Procedure -- 10.4.5 Gatekeeping Procedure -- 10.4.6 MCP Using p-Values from Cochran-Mantel-Haenszel Test -- 10.5 Discussion -- References -- 11 Bayesian Approach -- 11.1 Introduction -- 11.1.1 An Example on Bayesian Concept -- 11.1.2 A Brief History -- 11.1.3 Bayes Theorem -- 11.1.4 Bayesian Hypothesis Testing Framework -- 11.2 Bayesian Updating -- 11.2.1 Example Continued for Bayesian Updating -- 11.3 Bayesian Inference.

11.4 Markov Chain Monte Carlo (MCMC) Method -- 11.5 Bayesian Methods for Phase II Clinical Trials -- 11.6 Example -- 11.6.1 Using Non-informative Priors -- 11.6.2 Using Informative Priors -- 11.6.3 Summary -- References -- 12 Overview of Phase III Clinical Trials -- 12.1 Introduction -- 12.2 Scope of Phase III Plans -- 12.3 Drug Label and Target Product Profile -- 12.4 Phase III Non-inferiority Trial Designs -- 12.5 Dose and Regimen Selection, Drug Formulation and Patient Populations -- 12.5.1 Dose and Regimen Selection -- 12.5.2 Drug Formulations -- 12.5.3 Patient Populations -- 12.6 Number of Phase III Trials for a Labeling Claim -- 12.7 Number of Primary Efficacy Endpoints -- 12.8 Missing Data Issues -- 12.9 Phase III Clinical Outcome Assessments -- 12.10 Multi-regional Phase III Clinical Trial Issues -- 12.11 The Trend Towards Personalized or Precision Medicines -- 12.12 Summary -- References.

Description based on publisher supplied metadata and other sources.

There are no comments for this item.

Log in to your account to post a comment.