This book provides foundational and expert knowledge by building on the sequence of operations starting from the quantification in analytical sciences by defining the analyte and its link to the calibration function. It empowers the reader to apply Method Accuracy Profile(MAP) efficiently as a statistical tool in measuring uncertainty. In this respect, this book is unique as it proposes a comprehensive approach to MU (Measurement Uncertainty) estimation. It elucidates several examples and template worksheets explaining the theoretical aspects of the procedure. It also allows the reader by providing practical insights to improve decision making by accurately evaluating and comparing different analytical methods

Autorentext

*Max Feinberg has served as a research director at the National Institute of Agricultural Research (INRA). He has organized and chaired various congresses, served on the editorial boards of several journals, and coordinated various European research projects. **Serge Rudaz* is full professor at the school of pharmaceutical sciences from the University of Geneva, Switzerland. He is a specialist in the analysis of low molecular weight compounds in biological matrices and an expert in method validation.

Klappentext

Quantification, Validation and Uncertainty in Analytical Sciences Companion guide explaining all processes in measuring uncertainty in quantitative analytical results Quantification, Validation and Uncertainty in Analytical Sciences provides basic and expert knowledge by building on the sequence of operations starting from the quantification in analytical sciences by defining the analyte and linking it to the calibration function. Proposing a comprehensive approach to MU (Measurement Uncertainty) estimation, it empowers the reader to apply Method Accuracy Profile (MAP) efficiently as a statistical tool in measuring uncertainty. The text elucidates several examples and template worksheets explaining the theoretical aspects of the procedure and includes novel method validation procedures that can accurately estimate the data obtained in measurements. It also enables the reader to provide practical insights to improve decision making by accurately evaluating and comparing different analytical methods. Brings together an interdisciplinary approach with statistical tools and algorithms applied in analytical chemistry and written by two international experts with long-standing experience in the field of Analytical measurements and Uncertainty, Quantification, Validation and Uncertainty in Analytical Sciences includes information on:

• The know-how of methods in an analytical laboratory, effective usage of a spurious measurement and methods to estimate errors. Quantification, calibration, precision, trueness, MAP addons, estimating MU for analytical sciences, and uncertainty functions
• Employing measurement uncertainty, sampling uncertainty, quantification limits, and sample conformity assessment

• Decision making, uncertainty and standard addition method, and accuracy profile for method comparison Quantification, Validation and Uncertainty in Analytical Sciences is an ideal resource for every individual quantifying or studying analytes. With several chapters dedicated to MU's practical use in decision making demonstrating its advantages, the book is primarily intended for professional analysts, although researchers and students will also find it of interest.

  Inhalt
  Table of Contents
  Preface

  1. Quantification
     1.1 Define the Measurand (Analyte)
  2. Calibration
     2.1 Direct and Inverse Calibration
  3. Precision
     3.1 Outputs of Interlaboratory Studies
  4. Trueness
     4.1 Trueness and True Value
  5. Method Validation
     5.1 Review of Validation Procedures
  6. Measurement Uncertainty (MU)
     6.1 Principle of Measurement Uncertainty
  7. Measurement Uncertainty in Analytical Sciences
     7.1 Published Procedures: an evaluation
  8. Measurement Uncertainty and Decision
     8.1 Framework for decision-making
  9. MU and Quantification Limits
     9.1 Definitions and Assessment of LOQ
  10. Examples of MU Application
      10.1 Standard Addition Method and Drug Quality
  11. Conclusions
      11.1 Role of the Number of Replicates
  12. Annexes
      12.1 The 10-step MAP procedure