Muutke küpsiste eelistusi

Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach [Kõva köide]

, , (Hemoglobin Oxygen Therapeutics LLC, Souderton, Pennsylvania, USA)
  • Formaat: Hardback, 220 pages, kõrgus x laius: 234x156 mm, kaal: 504 g
  • Ilmumisaeg: 16-Jul-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1498769799
  • ISBN-13: 9781498769792
Teised raamatud teemal:
  • Formaat: Hardback, 220 pages, kõrgus x laius: 234x156 mm, kaal: 504 g
  • Ilmumisaeg: 16-Jul-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1498769799
  • ISBN-13: 9781498769792
Teised raamatud teemal:
Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach describes a philosophy of efficient problem solving showcased using examples pertinent to the biostatistics function in clinical drug development. It was written to share a quintessence of the authors experiences acquired during many years of relevant work in the biopharmaceutical industry. The book will be useful will be useful for biopharmaceutical industry statisticians at different seniority levels and for graduate students who consider a biostatistics-related career in this industry.

Features:











Describes a system of principles for pragmatic problem solving in clinical drug development. Discusses differences in the work of a biostatistician in small pharma and big pharma. Explains the importance/relevance of statistical programming and data management for biostatistics and necessity for integration on various levels. Describes some useful statistical background that can be capitalized upon in the drug development enterprise. Explains some hot topics and current trends in biostatistics in simple, non-technical terms. Discusses incompleteness of any system of standard operating procedures, rules and regulations. Provides a classification of scoring systems and proposes a novel approach for evaluation of the safety outcome for a completed randomized clinical trial. Presents applications of the problem solving philosophy in a highly problematic transfusion field where many investigational compounds have failed. Discusses realistic planning of open-ended projects.

Arvustused

"This is a highly original, extremely interesting, and in many ways impressive book. Its matter is largely about what it entails to be a professional biostatistician (in the widest sense of the word): what skills and attitudes you need to solve the problems encountered in exercising your profession. It is clear that the authors have thought long and hard about the problems they present. The case-studies are real, complex, interesting, and instructive. The book could only have been written by skilled scientists with long experience of working in the pharmaceutical industry. The reader benefits from the authors experience. The reader can be in no doubt that he or she is in the hands of experts. I learned a lot from the book." ~Stephen Senn, Retired, Honorary Professor, University of Sheffield

" . . . the book is extremely well written in an accessible and entertaining style, while being informative at the same time. It can wholeheartedly be recommended to every early career biostatistician and PhD student in (bio)statistics, who is considering going into pharmaceutical research, or conducting research in clinical trials." ~Diane Uschner, ISCB News

"The book is based on the authors cumulative experience in the biopharmaceutical industry and wisdom gained from a myriad of challenging problems. Further, given the diverse set of covered topics, we feel that this book would benefit those new to the industry (e.g., graduate students), as well as experienced professionals. Through detailed case studies, the book covers the broad skill set that is needed in the biopharmaceutical industry. Covered clinical drug development topics include: the early stage (e.g., pharmacology, toxicology, pharmacokinetics), the late stage (e.g., trial management and analysis, investigational new drug or new drug applications, communications with regulatory), strategic planning, the functional role of biostatisticians within a biopharmaceutical company, and the many functional roles that a biostatistician must interact with.

"The whole reading journey turned out to be a pleasant and educational oneFor readers who are interested or are already in the biopharmaceutical industry, this book can provide a framework that helps you build a successful career in this dynamic and exciting industry." ~American Statistician

Preface xi
Authors xvii
List of Abbreviations
xix
1 Background and Motivation
1(26)
1.1 Pragmatic approach to problem solving
1(1)
1.2 Problem solving skills
2(3)
1.3 Mathematics versus statistics
5(3)
1.4 A look at modern drug development
8(7)
1.4.1 Stages of drug development
11(3)
1.4.2 Factors that have had an impact on drug development
14(1)
1.5 Statistics and evidence-based science
15(5)
1.6 In summary: what this book is all about
20(5)
Introduction to
Chapters 2, 3, and 4
25(2)
2 Statistical Programming
27(16)
2.1 Introduction
27(1)
2.2 Asking the right questions
28(2)
2.3 Choice of statistical and presentation software
30(1)
2.4 "95/5" rule
31(2)
2.4.1 The sources
32(1)
2.4.2 SAS Certification---Is it worth the time and efforts?
32(1)
2.5 Data access, data creation and data storage
33(2)
2.6 Getting data from external files
35(2)
2.7 Data handling
37(2)
2.7.1 The DATA step
37(1)
2.7.2 Loops and arrays
38(1)
2.7.3 Going from vertical to horizontal datasets and vice versa
39(1)
2.8 Why do we need basic knowledge of the Macro language?
39(3)
2.8.1 Open code vs. DATA step
40(1)
2.8.2 Loops in the open code (inside macros) and nested macros
40(1)
2.8.3 Use of pre-written (by others) macro code
41(1)
2.9 Summary
42(1)
3 Data Management
43(24)
3.1 Introduction
43(2)
3.2 Design of data collection
45(1)
3.3 Organization of data collection
46(2)
3.4 Data cleaning or verification
48(2)
3.5 Re-structuring of the data
50(1)
3.6 First case study
50(2)
3.7 Second case study
52(13)
3.8 Summary
65(2)
4 Biostatistics
67(48)
4.1 Introduction
67(4)
4.2 The biostatistician's role
71(7)
4.3 Background assessment: what do we start with?
78(6)
4.4 A minimal sufficient set of tools for the biostatistician
84(13)
4.4.1 Knowledge of the disease area
85(1)
4.4.2 Knowledge of the regulatory landscape
86(1)
4.4.3 Understanding of the clinical trial protocol
87(3)
4.4.4 Knowledge of statistical methodologies for protocol development
90(3)
4.4.5 Statistical software
93(2)
4.4.6 Communication skills
95(1)
4.4.7 Knowledge of processes
96(1)
4.5 Advanced biostatistics toolkit
97(12)
4.5.1 Adaptive designs
98(2)
4.5.2 Basket, umbrella, platform trials and master protocols
100(2)
4.5.3 Dose-finding methods
102(1)
4.5.4 Multiplicity issues
103(1)
4.5.5 Estimands
104(2)
4.5.6 Quantitative decision-making support
106(1)
4.5.7 Digital development
107(2)
4.6 Summary
109(2)
Introduction to
Chapters 5, 6, and 7
111(4)
5 Development of New Validated Scoring Systems
115(18)
5.1 Introduction
115(1)
5.2 Recognition of problem existence
116(1)
5.3 Study of available methods and tools with consequent realization that they are insufficient
117(4)
5.4 Clear formulation and formalization of the main task to be solved
121(3)
5.5 A solution itself
124(5)
5.6 Are we finished? Not in the regulatory setting!
129(2)
5.7 Assessment of created by-products as potentially new tools, skills and methods
131(1)
5.8 Generalization of all achievements and evaluation of potential applications in the real world
131(2)
6 Resurrecting a Failed Clinical Program
133(26)
6.1 Preamble: what we are dealing with
133(2)
6.2 Problems solved
135(23)
6.2.1 Studying drugs with dosage that depends on needs
138(1)
6.2.2 Separation of toxicity and efficacy effects in safety outcome misbalance
139(3)
6.2.3 Creation of a PK model for the transfusion field
142(7)
6.2.4 Mystery of the transfusion trigger
149(4)
6.2.5 The rise and fall of the HBOC field
153(5)
6.3 Summary
158(1)
7 Can One Predict Unpredictable?
159(30)
7.1 Personal disclaimer/preamble
159(1)
7.2 First, what can we do?
160(1)
7.3 Problems in planning of the open-ended projects
161(15)
7.3.1 Extraneous vs. overlooked parts in preliminary planning
162(4)
7.3.2 Level of uncertainty of elementary tasks
166(6)
7.3.3 Terminology and definitions
172(4)
7.4 Estimating distribution of time to completion of an open-ended project
176(11)
7.4.1 Surprising results of first test runs of the algorithm
177(3)
7.4.2 The nature of estimates for elementary tasks
180(3)
7.4.3 Estimation for a single branch
183(3)
7.4.4 How to analyze the results?
186(1)
7.5 Summary
187(2)
Appendix A Relativistic and Probabilistic Functions 189(4)
Appendix B Manual for Successful Crusade in Defense of Patients' Rights 193(4)
Afterword 197(4)
Final Remark 201(2)
Bibliography 203(10)
Index 213
Arkadiy Pitman, MSc is senior director of biostatistics and data management at HBO2 Therapeutics. His experience includes over 20 years of teaching mathematics, logic, statistics, and computer science, as well as over 20 years of work in US small pharma environment, covering data management, statistical programming, biostatistics, regulatory, and medical writing.

Oleksandr Sverdlov, PhD is neuroscience disease area lead statistician in early clinical development at Novartis Pharmaceuticals. He has been actively involved in research on adaptive designs for clinical trials and edited a monograph Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects (CRC Press).

L. Bruce Pearce, PhD has background in pharmacology and toxicology. Since 2009 he has served as a consultant to very early and late stage biotechnology and pharmaceutical companies for the development of small molecule-based drugs, biotechnology-derived natural and recombinant biotherapeutics, and medical devices.