Drug development is a highly complex process that involves multiple steps of preclinical and clinical pharmacological refinement and testing. Preclinical studies include assessing drug bioavailability, metabolism, and toxicity; effects on known biological targets (e.g., receptor binding); and performance in various animal models of pathology. After sufficient data are obtained in animal studies, drug testing in humans can begin. In the United States, human clinical trials are divided into four phases. Phase I involves testing multiple doses of a drug for bioavailability, pharmacokinetics, and side effects. Phase II studies are dose-finding studies in patients with a given disorder. They can be open-label or double-blind trials. Phase III generally includes pivotal double-blind trials for demonstrating efficacy and safety/tolerability. Phase IV trials, which take place after a drug has received U.S. Food and Drug Administration (FDA) approval and is on the market, are conducted to help clarify potential uses of the drug.
Generally, efficacy is established via a randomized, controlled trial (RCT) in which a test drug is compared with a so-called placebo and/or an active compound. An RCT is an experiment designed to establish the efficacy of a treatment by comparing the responses in two or more groups of patients sampled from a relevant clinical population, with one group randomly assigned to receive the treatment of interest and a second group randomly assigned to receive a control treatment, in which all subjects are enrolled, treated, and uniformly followed over the same time period (Meinert 1986). In contrast, experiments that are performed under any of the following circumstances are not RCTs:
1. Using human tissues or animals
2. For purposes other than establishing efficacy of a treatment
3. Comparing groups of patients who were selected rather than randomly assigned to receive a given treatment (observational, or quasi-randomized, clinical trials)
4. Assessing response to a treatment in absence of a control group (e.g., pre-post study designs)
5. Comparing a group of patients given a treatment versus another group given another treatment observed at different times or places (e.g., historical control subjects)
Although the basic premise underlying the RCT has remained the same over the past half century, RCTs today differ from RCTs of the 1950s. Advances have occurred not only in statistical methodology but also in research methods; studies are now better designed to promote the replicability of the results and thus to protect the validity of inferences drawn from RCTs and applied to patient populations. The basic premise underlying the RCT defines the "causal effect of treatment (T) on an individual patient" as a comparison between a patient's response to T with what the outcome in that same patient would have been if that patient had not been given T (Rubin 1974, 2004). The condition proposed to represent what would have happened if that patient had not been given T is generally called the control or comparison group (hereafter referred to as C).
Unfortunately, there is no way to assess response to any treatment for an individual patient under two conditions, T and C, simultaneously. If a treatment were given to the same patient at different times, the condition of the patient might change between the first and second time (secular trends), or the response to treatment the first time may influence the response to treatment the second time (carryover effects). Consequently, how much of any difference seen between the two responses is attributable to T per se and how much is attributable to other, extraneous influences cannot be ascertained. Thus, the causal effect of T in an individual patient cannot be assessed. However, what cannot be done with an individual patient can be done with a clinical population. Patients in a representative sample from the clinical population of interest can be randomly assigned to receive either T or C. Under optimal conditions in a rigorously controlled study, the average responses in the two groups are estimates of what the average responses to receiving T and to not receiving T would be within the entire population, and the comparison between them is an estimate of the average causal effect of T on the population sampled.
In designing an optimal RCT the following issues need to be considered, all of which we address at least briefly in this chapter:
■ Specific indications and populations to be studied
■ Drug formulation and doses to be used
■ Route and time of administration
■ Instruments to be used as outcome measures
■ What the comparison groups should be
■ Power analysis and statistical analysis tools
The question of what the comparison groups should be is especially important. The issue of whether to compare the treatment with a placebo or an active control has become a contentious social and ethical issue as well as a scientific issue, particularly regarding psychiatric patients with severe disorders such as schizophrenia, and we focus strongly on that issue in this chapter.
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