Main description:

Drug development is the process of finding and producing therapeutically useful pharmaceuticals, turning them into safe and effective medicine, and producing reliable information regarding the appropriate dosage and dosing intervals. With regulatory authorities demanding increasingly higher standards in such developments, statistics has become an intrinsic and critical element in the design and conduct of drug development programmes.

Statistical Issues in Drug Development presents an essential and thought provoking guide to the statistical issues and controversies involved in drug development. 

This highly readable second edition has been updated to include:

• Comprehensive coverage of the design and interpretation of clinical trials.


• Expanded sections on missing data, equivalence, meta–analysis and dose finding.


• An examination of both Bayesian and frequentist methods.


• A new chapter on pharmacogenomics and expanded coverage of pharmaco–epidemiology and pharmaco–economics.


• Coverage of the ICH guidelines, in particular ICH E9, Statistical Principles for Clinical Trials.

It is hoped that the book will stimulate dialogue between statisticians and life scientists working within the pharmaceutical industry. The accessible and wide–ranging coverage make it essential reading for both statisticians and non–statisticians working in the pharmaceutical industry, regulatory bodies and medical research institutes. There is also much to benefit undergraduate and postgraduate students whose courses include a medical statistics component.

Back cover:

Drug development is the process of finding and producing therapeutically useful pharmaceuticals, turning them into safe and effective medicine, and producing reliable information regarding the appropriate dosage and dosing intervals. With regulatory authorities demanding increasingly higher standards in such developments, statistics has become an intrinsic and critical element in the design and conduct of drug development programmes.

Statistical Issues in Drug Development presents an essential and thought provoking guide to the statistical issues and controversies involved in drug development. 

This highly readable second edition has been updated to include:

• Comprehensive coverage of the design and interpretation of clinical trials.


• Expanded sections on missing data, equivalence, meta–analysis and dose finding.


• An examination of both Bayesian and frequentist methods.


• A new chapter on pharmacogenomics and expanded coverage of pharmaco–epidemiology and pharmaco–economics.


• Coverage of the ICH guidelines, in particular ICH E9, Statistical Principles for Clinical Trials.

It is hoped that the book will stimulate dialogue between statisticians and life scientists working within the pharmaceutical industry. The accessible and wide–ranging coverage make it essential reading for both statisticians and non–statisticians working in the pharmaceutical industry, regulatory bodies and medical research institutes. There is also much to benefit undergraduate and postgraduate students whose courses include a medical statistics component.

Contents:

Preface to the Second Edition.

Preface to the First Edition.

Acknowledgements.

1. Introduction.

1.1 Drug development.

1.2 The role of statistics in drug development.

1.3 The object of this book.

1.4 The author s knowledge of statistics in drug development.

1.5 The reader and his or her knowledge of statistics.

1.6 How to use the book.

Part 1: Four Views of Statistics in Drug Development: Historical, Methodological, Technical and Professional.

2. A Brief and Superficial History of Statistics for Drug Developers.

2.1 Introduction.

2.2 Early Probabilists.

2.3 James Bernoulli (1654 1705).

2.4 John Arbuthnott (1667 1753).

2.5 The mathematics of probability in the late 17th, the 18th and early 19th centuries.

2.6 Thomas Bayes (1701 1761).

2.7 Adolphe Quetelet (1796 1874).

2.8 Francis Galton (1822 1911).

2.9 Karl Pearson (1857 1936).

2.10 Student (1876 1937).

2.11 R.A. Fisher (1890 1962).

2.12 Modern mathematical statistics.

2.13 Medical statistics.

2.14 Statistics in clinical trials today.

2.15 The current debate.

2.16 A living science.

2.17 Further reading.

3. Design and Interpretation of Clinical Trials as Seen by a Statistician.

3.1 Prefatory warning.

3.2 Introduction.

3.3 Defining effects.

3.4 Practical problems in using the counterfactual argument.

3.5 Regression to the mean.

3.6 Control in clinical trials.

3.7 Randomization.

3.8 Blinding.

3.9 Using concomitant observations.

3.10 Measuring treatment effects.

3.11 Data generation models.

3.12 In conclusion.

3.13 Further reading.

4. Probability, Bayes, P–values, Tests of Hypotheses and Confidence Intervals.

4.1 Introduction.

4.2 An example.

4.3 Odds and sods.

4.4 The Bayesian solution to the example.

4.5 Why don t we regularly use the Bayesian approach in clinical trials?

4.6 A frequentist approach.

4.7 Hypothesis testing in controlled clinical trials.

4.8 Significance tests and P–values.

4.9 Confidence intervals and limits and credible intervals.

4.10 Some Bayesian criticism of the frequentist approach.

4.11 Decision theory.

4.12 Conclusion.

4.13 Further reading .

5. The Work of the Pharmaceutical Statistician.

5.1 Prefatory remarks.

5.2 Introduction.

5.3 In the beginning.

5.4 The trial protocol.

5.5 The statistician s role in planning the protocol.

5.6 Sample size determination.

5.7 Other important design issues.

5.8 Randomization.

5.9 Data collection preview.

5.10 Performing the trial.

5.11 Data analysis preview.

5.12 Analysis and reporting.

5.13 Other activities.

5.14 Statistical research.

5.15 Further reading.

Part 2: Statistical Issues: Debatable and Controversial Topics in Drug Development.

6. Allocating Treatments to Patients in Clinical Trials.

6.1 Background.

6.2 Issues.

References.

6.A Technical appendix.

7. Baselines and Covariate Information.

7.1 Background.

7.2 Issues.

7.A Technical appendix.

8. The Measurement of Treatment Effects.

8.1 Background.

8.2 Issues.

8.A Technical appendix. 

9. Demographic Subgroups: Representation and Analysis.

9.1 Background.

9.2 Issues.

9.A Technical appendix. 

10. Multiplicity.

10.1 Background.

10.2 Issues.

10.A Technical appendix.

11. Intention to Treat, Missing Data and Related Matters.

11.1 Background.

11.2 Issues.

11.A Technical appendix.

12. One–sided and Two–sided Tests and Other Issues to Do with Significance and P–values.

12.1 Background.

12.2 Issues.

13. Determining the Sample Size.

13.1 Background.

13.2 Issues.

14. Multicentre Trials.

 14.1 Background.

14.2 Issues.

14.A Technical appendix.

15. Active Control Equivalence Studies.

15.1 Background.

15.2 Issues.

15.A Technical appendix.

16. Meta–Analysis.

16.1 Background.

16.2 Issues.

16.A Technical appendix.

17. Cross–over Trials.

17.1 Background.

17.2 Issues. 

18. n–of–1 Trials.

18.1 Background.

18.2 Issues. 

19. Sequential Tr4ials.

19.1 Background.

19.2 Issues.

20. Dose–finding.

20.1 Background.

20.2 Issues.

21. Concerning Pharmacokinetics and Pharmacodynamics.

21.1 Background.

21.2 Issues.

22. Bioequivalence Studies.

22.1 Background.

22.2 Issues.

23. Safety Data, Harms, Drug Monitoring and Pharmaco–epidemiology.

23.1 Background.

23.2 Issues.

24. Pharmaco–economics and Portfolio Management.

24.1 Background.

24.2 Issues. 

25. Concerning Pharmacogenetics, Pharmacogenomics and Related Matters.

25.1 Background.

25.2 Issues.

25.A Technical appendix.

Glossary.

Index.