PROCYSBI, the first drug to receive FDA approval after following an adaptive population re-assessment design, was one of Cytel's most exciting success stories. Could your drug be next?
It has become popular to rave about the many regulatory, statistical and financial benefits of adaptive designs when compared to the inflexibility of conventional trials. However, the reality is that not every trial benefits from such designs. While many trials gain considerable improvement to clinical utility with the choice of an adaptive method, others perform just as well with more conventional study designs.
When determining whether or not to adapt, many firms begin by assessing the strategic benefits of using an adaptive design within the broader context of a development program. However, securing the benefits of an adaptive design also requires an assessment of the practical capabilities necessary for trial implementation. Practical considerations of patient enrollment, drug supply, and data acquisition are just a few of the critical factors that need to play a role in the decision to adapt. It is important to keep in mind that the practicalities of trial implementation will often appear as costs that diminish the strategic benefits of an adaptive design. As a result, it is important to have a clear sense of the magnitude of this reduction.
Unfortunately, the critical factors in question are wide-ranging. Overlooking a single one of these factors can underestimate the risks or feasibility of a trial, and obfuscate its benefits. Therefore, it is necessary to have guidelines in place that can allow a design team to systematically weigh all of these considerations against each other.
In a recent Cytel whitepaper, CEO Ranganath Nayak and Senior Director and Consultant Jim Bolognese, propose the following ten step procedure to determine whether or not to adapt. According to Nayak & Bolognese, there are ‘3 gatekeepers’ in the choice to adapt: regulatory agencies, the clinical operations team, and the financial staff. Following these ten steps ensures an orderly and comprehensive response to the concerns raised by each of these groups.
Step 1: Assess whether the time between the interim observation for adaptation and the enrollment of the last patient is enough to warrant an adaptive design. Since a number of scenarios could potentially arise as a consequence of an interim look, ensure that investigators are able to make decisions for all eventualities. In some cases, computer simulations may be necessary to prepare for various trial outcomes. Feel free to contact Cytel Consulting if you need guidance on making such an assessment.
Step 3: Determine whether there are any regulatory concerns or reservations which would prohibit the use of an adaptive design. While making this assessment, we encourage consultation with those experienced in both clinical trial design as well as regulatory affairs.
Step 4: Consider how an adaptive design will affect patient enrollment. Coordination among multiple sites for the adaptations may become complicated. Make certain the communication of adaptations among sites is feasible and streamlined.
Step 5: Ascertain whether there is sufficient drug supply to support all possible adaptations. For this you will need to consult those experienced with both trial design and drug supply management. Get started by viewing these two presentations by Cytel CTO and Co-Founder, Professor Nitin Patel. (Modeling and Simulation to Improve Supply Management in Clinical Trials; The New Role of Drug Supply Planning in Adaptive Trials.)
Step 6: A related concern is whether the required drug supply can reach the necessary enrollment site under all possible scenarios. Determining this will typically require the use of simulations. (View 'Drug Supply for Adaptive Trials,' by Cytel CTO and Co-founder, Professor Nitin Patel.)
Step 7: Is data acquisition and interim analysis rapid enough for a timely completion of the trial? In an adaptive design, quite a lot rides on proper assessment of data during interim analysis. The evaluation must be thorough enough to risk the remainder of the trial, but must also be done quickly enough for timely trial completion. Are such resources available to your company?
Step 8: Ensure there is sufficient statistical expertise to:
Step 9: How can software help to inform the decision to adapt? Software can be both a help and a hindrance. If possible, find trusted and validated software for trial design, which allows you to compare designs easily and to share data intuitively with your financial team. Make sure such software is available to you.
Step 10: Given all the information above, decide whether there are sufficient improvements to cost, savings in time and resources, and benefits to the quality of the data gathered to warrant an adaptive design. There is a tradeoff among costs, time, and precision of the data. Compare this tradeoff versus a traditional non-adaptive design, and choose accordingly.
Ideally, this last assessment would be made in tandem with the construction of the entire clinical development program, since a thorough account of operational capabilities for one trial may shape the entire sequence of trials. (As a simple example, determining the feasibility of a combined Phase 2/3 adaptive design would obviously affect whether an independent confirmatory trial is necessary.) However, it is also the case that the resources expendable upon any one trial are necessarily limited by the structure of the entire development program. Therefore, developing robust clinical strategy demands negotiating a balance between an assessment of operational capabilities and the overall design of a development program. Stay tuned for a Cytel blog post on developing effective clinical strategy.
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Related Items of Interest
Cytel Whitepaper: Adaptive Clinial Trials (by CEO Ranganath Nayak and Senior Director & Consultant Jim Bolognese)
Modeling and Simulation to Improve Supply Management in Clinical Trials (Slides of Nitin Patel, Cytel CTO and Co-founder)
The New Role of Drug Supply Planning in Adaptive Trials (Slides of Nitin Patel, Cytel CTO and Co-founder)
Drug Supply for Adaptive Trials (Slides of Nitin Patel, Cytel CTO and Co-founder)
Powering Oncology Trials for Success: Adaptive Designs in East (blog by Cytel Statistician and Product Manager Charles Liu)
Adaptive Designs for Precision Medicine: A Look at Pfizer's Xalkori Trial (Cytel blog with slides by Nina Selaru of Pfizer Oncology)
5 Reasons to Invest in Adaptive Designs for Population Enrichment
