This is another great book by Dr Chow, who is a very well-known statistician and a productive author or co-author of over 310 methodology papers and 31 books. It is so far the first and the most comprehensive book which entirely focus on rare diseases drug development from both regulatory and statistical perspectives. Particularly, it integrated all the major out-of-box innovative thinking that the author proposed in rare disease drug development in one place. This highly anticipated book will be extremely useful for statisticians who is working on rare disease and who are eager to learn about those innovative thinking in the design and analysis in this area.
This book consists of 14 chapters covering regulatory requirement, basic consideration, innovative design, as well as analysis for rare diseases drug development. In my opinion, these chapters can be categorized into three major sections which are preceded by an introductory chapter: (1) Section 1, from chapter 2 to chapter 5, is the basic considerations and some statistical issues; (2) Section 2, from chapter 6 to chapter 12, covers four major innovative thinking; (3) Section 3, which is chapter 13 and 14, provides two case studies.
Chapter 1 is introduction. It provides some background and lays out a clear roadmap of what to be discussed in this book, including the definition of rare disease, regulatory perspectives (regulatory incentives/guidance) and brief overview of the out-of-the-box innovative thinking.
In section 1, there are 4 chapters. Chapter 2 entitled “Basic considerations”, discusses some basic considerations in terms of historical data, ethical consideration, the use of biomarkers, and also gives a brief introduction on the complex innovative design together with the analysis, as well as the methods be considered for evaluation of the rare disease clinical trial to determine whether substantial evidence of safety and efficacy has been achieved. Chapter 3 entitled “hypotheses testing for the clinical evaluation”, the author first proposed to assess both safety and efficacy simultaneously for rare diseases clinical trials, then introduced general concepts and principles for multiplicity adjustment when performing composite hypotheses testing. Following this discussion, the author described analysis for testing composite hypotheses of non-inferiority in efficacy and superiority in safety, and the impact on power and sample size calculation. At the end, the author also proposed a method for determining significant digits. Chapter 4 discusses the endpoint selection in rare diseases clinical trials. In addition, the author further introduced the potential use of biomarker and development of therapeutic index, including the function and statistical evaluation of the index, as well as a numerical example. Chapter 5 is devoted to the clinical strategy for non-inferiority and equivalence margin selection based on risk assessment.
In section 2, which I believe is the most important section in this book, there are 7 chapters. The author states at chapter 1 that the out-of-the-box innovative thinking include “(i) probability monitoring procedure for sample size requirement, (ii) the concept of demonstrating not-ineffectiveness rather than demonstrating effectiveness, (iii) borrowing RWD in support of regulatory approval of rare diseases drug products, and (iv) the use of complex innovative design (CID) to shorten the process of drug development.” In this section, the author introduces these innovative thinking in detail at different chapters, respectively. Chapter 6 evaluates the probability of inclusiveness after not-ineffectiveness has been established. Chapter 7 discusses the sample size requirement for rare diseases drug development based on a newly proposed probability monitoring procedure. The author proposed two versions of probability monitoring procedures including non-adaptive version and adaptive version. Both versions can be applied to complex innovative designs discussed in this book. Chapter 8 discusses how RWD/RWE can be integrated into drug development and regulatory review for rare diseases. It first compared the fundamental difference between RWE and substantial evidence (regulatory standard), then discussed how to incorporate RWE into substantial evidence, and also includes some statistical considerations of integrity and validity of RWD, as well as the statistical methods for the assessment of RWE in support regulatory process. Chapter 9 introduced an innovative approach by first demonstrating not-ineffectiveness with limited subjects available for a rare disease and then borrowing RWD to demonstrate effectiveness using a two-stage adaptive trial design. In what follows, chapters 10–12 are devoted to those useful complex innovative trial designs in detail, including the n-of-1 trial design in chapter 10, a two-stage adaptive trial design in chapter 11, and master protocols (the platform trial design) for rare diseases drug development in chapter 12, respectively.
In section 3, there are 2 chapters, and two case studies are provided. Chapter 13 titled “Gene Therapy for Rare disease”, it reviews FDA’s guidance on gene therapy for rare diseases and describes a case study using a recent FDA-approved gene therapy regulatory submission. Chapter 14 titled “Clinical Development of NASH program”, it is dedicated to a case study on NASH (Non-Alcoholic SteatoHepatitis) for liver diseases with unmet medical need. The author described regulatory perspectives and registration pathways, endpoints selection, and the most important, the adaptive design approach.
Overall, the book is very well written and highly recommended for the following reasons: (1) It is so far the first and the most comprehensive book dedicated to discussion of rare diseases drug development; (2) The innovative study designs and statistical methods that the author proposed are inspiring and valuable for conducting clinical trials in rare diseases; (3) The statistical concepts and methodology are explained very clearly, technical details are described step-by-step, with a large number of statistical formulas and examples provided; (4) The book will be a great reference tool, given that it is well organized and easy to navigate through the chapters and quickly look up solutions for many statistical issues.
Still, the book has a few shortcomings. For example, (1) there is a lack of discussion on external control, which is also an important topic for designing in the rare disease clinical trials. The author only briefly describes Bayesian approach for data borrowing, but it would be nice if it can be extended; (2) It might cause some confusing on the following terms: two-stage adaptive trial design described in section 6.4, two-stage approach in section 9.4 and the two-stage seamless adaptive design in chapter 11. There is no clarification on whether these different terms are the same or not; (3) No code or software is provided for any of the calculation, it will pose some inconvenience for the implementation of these new design and analysis.
The very limited sample size of patients with rare disease brings a lot of challenges in both design and analysis of clinical trials as compared to the other common disease. To promote rare diseases drug development, innovative thinking is not only encouraged by FDA but also needed for the pharmaceutical companies. This book is published in a very timely manner that enable the promoting of these innovative design and analysis. I believe that it will certainly not only inspire the statisticians working in rare disease, but also could shed some light on the solutions of unique situation for clinical trials with common disease. Therefore, I strongly recommend this book to all the statisticians who work on clinical trials, not only those in rare disease but also on other indications.
Disclosure
The support for this manuscript was provided by AbbVie. AbbVie participated in the review and approval of the content. Meijing Wu is employee of AbbVie Inc. and may own AbbVie stock.