Advancing Clinical Trials to Streamline Drug Development

Abstract

The last decade in oncology has been marked by the identification of numerous new potential cancer targets and even more agents designed to inhibit them. The matrix of new targets, new agents, and the companion diagnostics required to identify the right patient for the right drug has created a major challenge for the clinical trial process. This has been compounded by the addition of new immunomodulators targeting the host immune system rather than the tumor. Recognizing the need for new approaches, industry, investigators, and regulators have responded to this challenge. New clinical trial designs are being evaluated to incorporate the genomic sequence data being obtained almost routinely after cancer diagnosis. New dose-finding approaches are being proposed to identify the maximum effective dose rather than the maximum tolerated dose. The FDA is involved in the drug approval process from points early in development and has accepted registration quality data from expansion cohorts in support of drug approval. Despite progress on several fronts, many challenges remain, including the lack of predictability of preclinical data for clinical results and phase II data for phase III results, an infrastructure that can be an obstacle to clinical trial development and implementation, and the increasing use of contracted clinical research organizations that limit a fit-for-purpose approach to clinical trial execution. Perhaps most challenging and important of all are the difficulties with clinical trial accrual that can prevent study completion. Both the innovations and the challenges highlight the important role of process in progress in clinical oncology.

Figure 1

Information used to select dose throughout escalation The blue circles denote required information that is necessary to know how to (or when not to) escalate beyond certain dose levels. The orange circles denote nonrequired information that allows dosing decisions to be driven by other endpoints collected within the study (e.g., using PK data to assess whether a change of schedule is needed). AE, adverse event; DLT, dose-limiting toxicity; PD, pharmacodynamic; PK, pharmacokinetic; QTc, QT corrected interval; RDI, relative dose intensity; SAE, serious adverse event.

Figure 2

Regulatory timelines then (A) and now (B).

Figure 2

Regulatory timelines then (A) and now (B).