Therapeutic confirmatory trials

Having considered these and other issues, what is a suitable dosing regimen for therapeutic exploratory and therapeutic confirmatory trials ... 

Safety analyses are not typically prespecified in the study protocol and/or the study analysis plan. Studies are typically powered on efficacy outcomes (the primary objective in therapeutic confirmatory trials see Chapter 9), and the sample size that results from this sample-size estimation may be considerably smaller than would be needed for a thorough investigation of safety data. 

In addition to having an acceptable safety profile, an investigational drug needs to display beneficial therapeutic effects. This takes us into the realm of therapeutic exploratory and therapeutic confirmatory trials. The statistical approaches discussed in this chapter are characteristic of those employed in these trials. 

All of the studies that are performed before a therapeutic confirmatory trial is started collect information that facilitates a logical scientific progression from FTIH studies to the point where the therapeutic confirmatory trial is appropriate. In a real sense, all of these studies, and all of the information gained to date, have had one purpose to allow the primary objective in the therapeutic confirmatory trial to be stated as simply as possible. In this context, the word simple is not pejorative. To the contrary, a primary objective that can be stated simply can be tested simply, i.e., in a straightforward and unambiguous manner. This is a highly desirable attribute in a primary objective. 

By the time a therapeutic confirmatory trial is appropriate, it should be possible to state a single primary objective (or perhaps two if the sponsor really feels that this is appropriate) that is clinically relevant and biologically plausible. One primary objective also means that sample-size estimation can be based on that objective and the associated estimated treatment effect of interest (recall the discussions in Chapter 9). 

If all goes well in the therapeutic confirmatory trials and the drug is approved, successful commercialization of the approved drug has its own demands. Of relevance in this chapter is the sponsor s ability to manufacture sufficient quantities of the drug in a form that can be readily transported from the manufacturing plant to the pharmacy and in a form that demonstrates stability and therefore has a suitably long shelf-life. 

While the nature of the analyses of data from therapeutic confirmatory clinical trials is relatively straightforward compared with those undertaken in earlier stages of clinical development, supreme care should again be taken in all aspects of design, methodology, and analysis, since only then can optimum quality data be used to provide optimum answers to well-constructed research questions. Chapter 10 noted that safety data are typically presented descriptively at this time but that this may change in due course. By the time that therapeutic confirmatory trials are conducted, there should be a small number of precisely asked research questions that address the efficacy of the drug. 

The requirement to show statistical significance in therapeutic confirmatory trials places a certain importance on a priori hypothesis testing. However, as we have seen, there is much more to clinical research than p-values. Piantadosi (2005) commented on this issue as follows ... 

Tight experimental control is an extremely important goal in all experimental trials. Consequently, we talk a lot about how to maximize such control in these trials. However, it is simply a realistic consequence of the way that therapeutic confirmatory trials have to be conducted that the experimental control cannot be quite as tight in these trials as it is in human pharmacology trials and therapeutic exploratory trials. 

The null hypothesis is the crux of hypothesis testing. (It is important to note that the form of the null hypothesis varies in different statistical approaches. As the main type of clinical trial discussed in this book is the therapeutic confirmatory trial, we talk about this first. We then talk briefly about the forms of the null hypothesis that are used in other types of trials in Section 3.10.) As noted earlier, therapeutic confirmatory trials are comparative in nature. We want to evaluate the efficacy of the investi-... 

At this point it is worth considering the length of time it takes to run a therapeutic confirmatory clinical trial. Such trials are often conducted as multicenter trials. Although the total numbers of individuals who participate in trials vary, we noted earlier that a typical number for a therapeutic confirmatory trial is 3000-5000 individuals. Each of these individuals needs to have the... 

The following are some of the fundamental components in a study protocol for a therapeutic confirmatory trial for an investigational antihypertensive drug ... 

The view of the US Food and Drug Administration (FDA) concerning safety reviews is presented in their guidance document on the safety review of new drug applications (US FDA, 2005, p 5). As this guidance states, most therapeutic exploratory and therapeutic confirmatory trials are carefully designed to establish that a... 

Safety monitoring in clinical studies can be both data and labor intensive. In the context of later-stage therapeutic exploratory and therapeutic confirmatory trials, the collection of laboratory data is no exception. Typically, participants in clinical trials provide blood or urine samples at every clinic visit. There is an expansive range of clinical chemistry tests that can be conducted using these samples. 

Table 10.1 Taxonomy of therapeutic confirmatory trial objectives...

The term "responders analysis" was first introduced in Chapter 9 with regard to clinical laboratory data. A responders analysis approach can be used in the context of efficacy data, as well. Consider a double-blind, placebo-controlled, therapeutic confirmatory trial of an investigational antihypertensive ("test drug"). Based on earlier experience, a period of 12 weeks is considered sufficient to observe a clinically meaningful treatment effect that can be sustained for many months. In this study, a participant whose SBP is reduced by at least 1 0 mmHg after 1 2 weeks... 

The previous chapters have provided you with an introduction to statistical methods and analyses that are commonly used in pharmaceutical clinical trials, with an emphasis on therapeutic confirmatory trials. Although we certainly have not covered all of the analyses that can be conducted in these trials, those that we have discussed have given you a solid foundation that will also enable you to understand the basics of other analyses. 

In this chapter we highlight additional statistical considerations relevant to therapeutic confirmatory trials, and other study designs that also provide important information upon which to base decision-making. These additional insights and information build upon the material presented so far. As this chapter is largely conceptual rather than computational, we have included a number of references to guide your further reading. 

It is also appropriate to note that not all clinical trials utilize formal sample size estimation methods. In many instances (for example, FTIH studies) the sample size is determined on the basis of logistical constraints and the size of the study thought to be necessary to gather sufficient evidence (for example, pharmacokinetic profiles) to rule out unwanted effects. However, when the objective of the clinical trial (for example, a superiority trial) is to claim that a true treatment effect exists while at the same time limiting the probability of committing type I or II errors (a and P), there are computational methods used to estimate the required sample size. The use of formal sample size estimation is required in therapeutic confirmatory trials, this book s major focus, and strongly suggested in therapeutic exploratory trials. 

We have seen that relatively small numbers of participants are recruited for early phase trials (perhaps 20-80 in FTIH studies and 200-300 in early Phase II studies), and relatively larger numbers are recruited for therapeutic confirmatory trials (perhaps 3000-5000). It is relatively easy to recruit between 20 and 80 participants at... 

In therapeutic confirmatory trial efficacy, the same analyses are typically conducted twice, using data from the ITT population and data from the per-protocol population (see Turner, 2007). The analyses conducted using the ITT population are considered to be the primary analyses because ITT analysis provides a conservative strategy in the sense that it tends to bias against finding the results that the researcher... 

By the time a therapeutic confirmatory trial is appropriate it should be possible to state a single... 

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