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.
- 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.
Table of Contents
1. Background and Motivation
Pragmatic approach to problem solving
Problem solving skills
Mathematics versus statistics
A look at the modern drug development
Stages of drug development
Factors that have had an impact on drug development
Statistics and evidence-based science
In summary: what this book is all about
Introduction to Chapters 2, 3, and 4
2 Statistical Programming
Asking the right questions
Choice of statistical and presentation software
SAS Certification | Is it worth time and efforts?
Data access, data creation and data storage
Getting data from external files
The DATA step
Loops and arrays
Going from vertical to horizontal datasets and vice versa
Why do we need basic knowledge of the Macro language?
Open code vs. DATA step
Loops in the open code (inside macros) and nested macros
Use of pre-written (by others) macro code
3 Data Management
Design of data collection
Organization of data collection
Data cleaning or verification
Re-structuring of the data
First case study
Second case study
The biostatistician's role
Background assessment: what do we start with?
A minimal sufficient set of tools for the biostatistician
Knowledge of the disease area
Knowledge of the regulatory landscape
Understanding of the clinical trial protocol
Knowledge of statistical methodologies for protocol development
Knowledge of processes
Advanced biostatistics toolkit
Basket, umbrella, platform trials and master protocols
Quantitative decision-making support
Introduction to Chapters 5, 6, and 7
5 Development of New Validated Scoring Systems
Recognition of problem existence
Study of available methods and tools with consequent realization that they are insufficient
Clear formulation and formalization of the main task to be solved
A solution itself
Are we finished? Not in the regulatory setting!
Assessment of created by-products as potentially new tools, skills and methods
Generalization of all achievements and evaluation of potential applications in real world
6 Resurrecting a Failed Clinical Program
Preamble: what we are dealing with
Studying drugs with dosage that depends on needs
Separation of toxicity and efficacy effects in safety outcome misbalance
Creation of a PK model for the transfusion field
Mystery of the transfusion trigger
The rise and fall of the HBOC field
7 Can One Predict Unpredictable?
First, what can we do?
Problems in planning of the open-ended projects
Extraneous vs. overlooked parts in preliminary planning
Level of uncertainty of elementary tasks
Terminology and definitions
Estimating distribution of time to completion of an open-ended project
Surprising results of first test runs of the algorithm
The nature of estimates for elementary tasks
Estimation for a single branch
How to analyze the results?
Appendix A: Relativistic and Probabilistic Functions
Appendix B: Manual for Successful Crusade in Defence of Patients' Rights
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.
Featured Author Profiles
"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