Designed for Pharma Drug Development Research Teams
The current patent cliff, shrinking pipelines, and the impact of a global recession place heightened pressure on the clinical development landscape. As competition intensifies for investigators, sites and patients, trial costs have reached unprecedented levels, causing drugmakers to adopt a bottom-line perspective and demand greater R&D efficiency. Greater efficiency leads to cost- and time-savings that could mean the difference in beating the competition to market and adding time to a drug’s lifecycle.
Successful teams win this race by minimizing risks, eliminating trial unknowns and hitting study deadlines. Supported by ample resources, they build process improvements through performance measurement and charge ahead with new techniques to accelerate trial timelines.
Designed to benefit teams and individuals in any role in the clinical trials space, this study will help teams achieve clinical operations efficiency — and realize the significant payoffs that accompany successful pharma drug development research:
Save time through adaptive trials
Learn how leading-edge companies use adaptive design to accelerate trials and achieve the desired endpoints. Understand the FDA’s new guidance and get a real sense of where the industry stands on this new frontier.
Track the right metric at the right time
Track 26 operational, timeline and resource metrics across the five development stages using real-company data from 80-plus trials. Learn how to incorporate forecasting software into trial design and planning.
Benchmark and manage resources
Break out individual costs and compare per-patient investments across five major therapeutic areas for Phases 1 through 4. Track staffing trends and coordinate in-house and outsourced teams.
The following excerpt is taken from Chapter 2, “Clinical Trial Staffing Benchmarks.” It outlines the information contained within this section of thereport. For complete access to detailed benchmarks, please purchase the full report.
Staffing Levels for Development Phases
This section includes detailed staffing benchmarks for each of the five phases of clinical trials: Phase 1, Phase 2, Phase 3a, Phase 3b and Phase 4. In addition, the staffing data included in this section are broken down into 12 occupational categories. Each represents a unique role in the clinical development process.
Although many of these development functions are members of trial teams at most companies, not all companies analyzed for this study organize their clinical development teams in the same manner. As such, some functions — such as clinical trial supplies, chemistry manufacturing and controls (CMC), and drug safety — often play a supporting role in the clinical development process even though they may not sit on trial teams. In each category, the data tables present staffing metrics for both in-house and outsourced staff. These are the 12 categories:
Vice Presidents, Clinical Program Directors, and other such therapeutic area supervisors
Clinical Quality Assurance (QA)
Clinical Trial Supplies
Chemistry Manufacturing and Controls (CMC)
The data contained in each of the 12 categories represent peak staffing levels for the development phase, as measured in full-time equivalents (FTEs). FTEs do not always correspond to the number of people actually working on a certain task. One FTE, for example, may equate to two people spending 50% of their time each on the task.
The data tables [available in the full report] present actual staffing levels for clinical trials in each phase. Each staffing table includes the following information about each trial:
Number of patients enrolled
Number of investigator sites
These four factors act as important guides to enable readers to compare staffing trends between trials.
Clinical Trial Staffing: Phase 1
Data in the figures from Chapter 2 [available in the full report] represent nine Phase 1 clinical studies from these therapeutic areas:
Central Nervous System/Neurology
Overall, Phase 1 clinical trials employ the fewest number of FTEs and outsource the lowest percentage of staff. Figure 2.5 shows this clearly: the data show that the largest staffing categories are CRA/monitor and data management, but they still only account for an average of 3.1 FTEs and 2.5 FTEs, respectively. With an average of 3.1 CRAs per trial, Phase 1 ranks lowest among all other phases.
The following excerpt is taken from Chapter 4, “Adaptive Clinical Trial Design.” The full chapter provides a comprehensive analysis of adaptive design. It includes a detailed discussion on the FDA’s new guidance, as well as benchmarks showing adaptive design usage and its impact on time and cost.
Reaction to FDA Guidance
On its face, the guidance provides a cautious endorsement of adaptive design as a method for accelerating the development process and increasing the efficiency of clinical trials. However, the reality — as shown in Figure 4.3 [available in the full report] — is that it is used infrequently at all stages of clinical development, especially in critical Phase 3 trials. Figure 4.4 shows survey respondents’ perceptions of the likelihood of introducing adaptive design into trials at various phases of development, rating each on a scale of one to five (with five representing very likely). Respondents identified Phase 2 as the most probable place to use adaptive design, followed by Phase 3b. During interviews, industry experts noted that Phase 3b trials, typically follow-ups to already successful confirmatory studies, are ripe for adaptive design because companies are pushing to get an approval they are confident will occur, and time- and costsaving tactics are at a premium.
The question of when pharma will begin to put adaptive design to use in Phase 3a trials more frequently will hinge on the success — or failure — of some of the early adopters of the technique. Until a high-profile drug approval is won with adaptive design incorporated into the Phase 3 protocol, trepidation will remain. “I think the FDA needs to clarify what their position is. Because in spite of what is in the guidance...the reviewing divisions have made it clear that they’re still uncomfortable with anything that happens to the data that might compromise the integrity of the data or introduce bias,” said the regulatory affairs manager at Company C.
So I think frankly that a number of sponsors would entertain the idea of doing adaptive design in Phase 3 studies, particularly if you’re doing the so-called seamless Phase 2-3. They’re concerned that at the end of the day, the reviewers are going to come back and say you unblinded the data too early, the study wasn’t over, etc., so there’s a chance that bias has been introduced and you’re going to have to take either a statistical hit or do something that will compromise your ability to gain an approval easily. I think it really is a question to a certain extent of mixed messages.
The statistical review personnel at the FDA view adaptive design as a major technical advance, but long-tenured regulatory personnel have a less favorable view of the new technology and are less likely to fully support it. In response, clinical directors are reluctant to take a perceived risk with adaptive trial designs that may not serve the company’s goal of getting a drug to market as quickly as possible.