Springer proceedings in mathematics & statistics ;
مشخصه جلد
volume 218
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references.
یادداشتهای مربوط به مندرجات
متن يادداشت
Intro; Contents; Contributors; Specification and Sampling Acceptance Tests; Statistical Considerations in Setting Quality Specification Limits Using Quality Data; 1 Introduction; 2 Statistical Methods for Setting Specification Criteria; 3 Relationships Between Coverage and k of PI, RI and TI; 4 Specification Determined with Pre-marketing Data; 5 Specification Determined Updated with Post-marketing Data; 6 Conclusions and Discussion; References; Counting Test and Parametric Two One-Sided Tolerance Interval Test for Content Uniformity Using Large Sample Sizes; 1 Introduction; 2 Sampling Tests
متن يادداشت
2 HPLC-NIR Calibration During Process Design3 Relative Performance Index; 4 Method Comparison Using the Relative Performance Index; 5 Case Study; 5.1 Data Description; 5.2 Statistical Model and Results; 6 Summary; References; A Further Look at the Current Equivalence Test for Analytical Similarity Assessment; 1 Introduction; 2 FDA's Tiered Approach for Analytical Similarity Assessment; 3 Assessment of the FDA Recommended Equivalence Test for Tier 1 QAs; 3.1 The Impact of SR Estimate on the Type I Error and the Power; 3.2 The Unbalanced Sample Size; 4 Summary
متن يادداشت
3 Monte Carlo Simulation Method4 Comparison of Acceptance Probabilities Between EU Option 2 and PTIT_matchUSP90; 4.1 Comparison of PTIT_matchUSP90 with EU Option 2 for Normal Variables with 100% LC Mean when n = 1000; 4.2 Comparison of PTIT_matchUSP90 with EU Option 2 for Normal Variables with 102% LC Mean when n = 1000; 4.3 Comparison of PTIT_matchUSP90 with EU Option 2 for a Mixture of Two Normal Variables with off Target Mean When n = 1000; 4.4 Comparison of PTIT_matchUSP90 with EU Option 2 for Three Extreme Cases; 5 Discussion and Conclusion; References
متن يادداشت
Analytical Biosimilar and Process ValidationSample Size Consideration for Equivalent Test of Tier-1 Quality Attributes for Analytical Biosimilarity Assessment; 1 Introduction; 2 Sample Size Requirement for the Equivalence Testing for a Single Tier 1 Quality Attribute; 3 Sample Size Requirement for the Equivalence Testings for Two Correlated Tier 1 Quality Attributes; 4 Discussion and Comments; Appendix; References; A Probability Based Equivalence Test of NIR Versus HPLC Analytical Methods in a Continuous Manufacturing Process Validation Study; 1 Introduction
متن يادداشت
Appendix 1 The Asymptotic Approximation to the Type I Error Rate for the Statistical Equivalence TestReferences; Shiny Tools for Sample Size Calculation in Process Performance Qualification of Large Molecules; 1 Introduction; 2 Sample Size Calculation Methods; 2.1 For Continuous CQAs with Acceptance Limits; 2.2 For Binary CQAs; 2.3 Illustration and Examples; 2.4 SSNormTI; 2.5 VarCompLM; 2.6 RiskBinom; 3 Discussion; References; Continuous Process; Risk Evaluation of Registered Specifications and Internal Release Limits Using a Bayesian Approach; 1 Introduction
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یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
This book presents the proceedings of the 39th annual Midwest Biopharmaceutical Statistics Workshop (MBSW), held in Muncie, Indiana on May 16-18, 2016. It consists of selected peer- reviewed and revised papers on topics ranging from statistical applications in drug discovery and CMC to biomarkers, clinical trials, and statistical programming. All contributions feature original research, and together they cover the full spectrum of pharmaceutical R & D - with a special focus on emergent topics such as biosimilarity, bioequivalence, clinical trial design, and subgroup identification. Founded in 1978, the MBSW has provided a forum for statisticians to share knowledge, research, and applications on key statistical topics in pharmaceutical R & D for almost forty years, with the 2016 conference theme being "The Power and 3 Is of Statistics: Innovation, Impact and Integrity." The papers gathered here will be of interest to all researchers whose work involves the quantitative aspects of pharmaceutical research and development, including pharmaceutical statisticians who want to keep up-to-date with the latest trends, as well as academic statistics researchers looking for areas of application.