Randomized, controlled trials (RCTs) can measure the efficacy of a single treatment in a single disease indication with maximum rigor and minimum bias. However, RCTs are often impractical for rare and ultra-rare diseases: only a small number of patients are available, the condition may be highly variable or poorly understood, and using placebo controls for rapidly progressive fatal illnesses is not ethical.
By contrast, a complex, innovative trial design (CID) can answer multiple questions about one or more compounds in one or more conditions or patient subgroups. Prespecified, “adaptive” modifications of the trial protocol can allow changes during the study based on interim data analyses. These adaptations can include sample size adjustments, dropping arms because of futility or safety findings, or enriching the target population.
CIDs are well suited to rare diseases. They are efficient (enroll patients quickly), informative (yield more data about a treatment’s effects), and ethical (patients may be less likely to receive a placebo). They are also more complicated, costly, logistically challenging, and at greater risk of operational and analytical bias.
At Parexel, we’ve found that innovative trial designs with adaptive elements are a demanding team sport. They require tight collaboration between biostatisticians, clinical operations, data management, medical experts, and project leadership. We’ve conducted dozens of CIDs, including more than 30 “basket” trials (which test one drug in multiple conditions), and we’ve learned from experience what works and what doesn’t. While some of our advice is common sense, many companies and clinical research organizations (CROs) struggle to execute these best practices with consistency and discipline. Here are five of them:
