Introduction

The rapidly escalating costs and increasing failure rate in drug development

decrease willingness and ability to bring many candidates forward into the

clinic. There are multiple reasons: (1) Those “low-hanging fruit” in the chem-

ical compound space have already been picked, (2) due to ethical considera-

tions, a pivotal clinical trial cannot be a placebo-controlled trial when a drug

for the disease is available; however, an active-controlled, in which the test

drug is compared against the best drug in the market, makes the efficacy mar-

gin much smaller than in a placebo-controlled trial. However, the regulatory

agencies in general still require type-I error rates of at most 5%, although

the meaning of the type-I error is completely different: one is compared to

placebo and the other is compared to active drug. Thus a diminished margin

for improvement escalates the level of difficulty in statistically proving drug

benefits or the sample size must increase, as must the cost and time. To stay in

competition, many pharmaceutical companies adopt different strategies, such

as company mergers or acquisitions, late phase outsourcing, reducing work-

force in the early research but buying promising compounds that are ready for

clinical trials. In addition to implementations of strategies in business, there

is also a significant change in the technological side: a paradigm shift from

classical statistic clinical trial designs to adaptive designs, which can lead to

a reduction in cost and time, and an increase in success rate in drug devel-

opment. In this chapter, we will review commonly used adaptive designs and

questions and answers that a newcomer may have.