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Immunoassay

A Practical Guide

1st Edition - September 16, 1987

Author: Bozzano G Luisa

eBook ISBN:

9 7 8 - 0 - 3 2 3 - 1 3 7 8 2 - 9

During the last few years, immunoassay has gained tremendous popularity in clinical and research laboratories and has been applied to determine hormone, enzyme, protein, drug, and… Read more

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During the last few years, immunoassay has gained tremendous popularity in clinical and research laboratories and has been applied to determine hormone, enzyme, protein, drug, and infectious agents. The aim of this book is to provide clinical laboratory personnel and students with an understanding of the principle of immunoassay and the production of reagents for immunoassay.

Preface

1. General Principle of Immunoassay

I. Introduction

II. Theoretical Basis of Immunoassay

III. Optimization of Immunoassay

IV. Heterogeneous Immunoassay Systems

V. Homogeneous Immunoassay Systems

References

2. Production of Immunoassay Reagents

I. Introduction

II. Receptors or Binders

III. Unlabeled Ligands—Calibrators

IV. Labeled Ligands and Receptors

V. Separation Techniques

VI. Buffers

References

3. Practical Guide to Immunoassay Method Evaluation

I. Introduction

II. Protocol Outline

III. Establishing Objectives and Preparation

IV. Evaluation of Precision

V. Standard Curves

VI. Tracer

VII. Sensitivity

VIII. Evaluation of Accuracy

IX. Antibody Characteristics

X. Monitoring Reaction Conditions

XI. Clinical Validation

XII. Protocol Development: Summary

References

4. Clinical Validation of Immunoassays: A Well-Designed Approach to a Clinical Study

I. Introduction

II. Elements of a Well-Designed Study

III. Choosing Decision Levels to Minimize Costs

IV. Relation of New Tests to Existing Tests

V. A Word about Normal Ranges

VI. Summary

VII. Illustrative Example: Apolipoprotein A-I

Appendix: Preparation of ROC Curves

References

Selected Literature

5. Data Reduction Techniques for Immunoassay

I. Purpose of Chapter

II. Introduction

III. Interpolation Techniques of Data Reduction

IV. Models and Statistical Approaches to Data Reduction

V. Nonlinear Models in Immunoassay

VI. Summary

Appendix A: BASIC Program to Fit Four Parameter Model to Data by Nonlinear Least Squares

Appendix B: BASIC Program for Point-to-Point Linear Interpolation

References

6. Immunoassays: Quality Control and Troubleshooting

Part A: Quality Control: A Simple, Cost-Effective Approach

I. Introduction

II. Implementing a QC Program

III. Selection of Appropriate Curve Fits for Immunoassay Data

IV. Equipment

V. Reagents

VI. Assay Conditions

VII. Technique

VIII. Patient Samples

IX. Conclusion

Part B: Troubleshooting Immunoassays: Where the Practical and Theoretical Meet

I. Introduction

II. Parallelism

III. Reciprocal Plot

IV. Scatchard Analysis

Index