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Even with current trial management systems, steps can be taken right now to greatly increase efficiency.
Despite the on-going revolution in biomedical science, modern drug discovery's true potential to alleviate suffering goes unfulfilled. Disturbingly, the rate of promising medications and treatments actually reaching patients is slowing. The pharmaceutical industry confronts both a decrease in trial applications and rapidly increasing development costs. Clinical trial miscalculations and inefficiencies come at an alarmingly high price. The FDA reports one out of every two Phase III trials ends in failure. Clearly, traditional trial methods are inadequate to keep pace with today's increasing flow of therapeutic candidates.
Xiao-Wei Zhu, PhD
In response, the FDA has taken a bold step toward addressing the pipeline problem with the Critical Path Initiative (CPI). The CPI encourages cooperation between government, research institutions, and the pharmaceutical industry to solve procedural bottleneck problems and accelerate time to market. In essence, the CPI mandates re-inventing the clinical trial process through re-evaluating current clinical practices, improving standards definitions, and developing and adopting new trial technologies.
The CPI advocates the creation of a far more capable clinical system to better manage trial complexities. Such a system would require more powerful computational methods to better identify risks, and simulate and predict results. Specifically, the FDA cites innovations in clinical trial design technology as the most promising way to shorten the duration of a clinical study and greatly increase its chances of success.
The CPI recommends solving clinical trial bottleneck problems by implementing a new generation of standards and predictive tools. Yet even with current trial management systems, effective steps can be taken right now to greatly increase efficiency and effectiveness. In fact, many of the innovations envisioned by the FDA already exist today. In the past decade academic and industry researchers have developed new statistical methodologies to enable significant advancements in flexible trial design, simulation, and monitoring.
Traditional fixed sample size designs tie up resources and delay crucial trial progress. In contrast, recently introduced group sequential and adaptive clinical trials are flexible, allowing variable sample sizes and time commitments. These flexible clinical designs employ the latest computational methods to permit interim looks at the data. As a result, midcourse trial improvements are easily implemented, while preserving type I error rate and maintaining the studies' intended power.
Flexible trials allow investigators to terminate futile studies earlier, fast track winning treatments, and make data-dependent changes to sample size, drug dose or other key design parameters. Faster evaluation of trial evidence enables precise resource management and increased efficiencies.
By introducing the possibility of interim analyses and early stopping, these new designs help ensure patient safety and more efficient use of resources. Sponsors, data safety monitoring boards, and government regulators can make better-informed, more accurate decisions about trials. This means fewer "failed" trials of treatments that do work, less time and money on treatments that don't, and fast-tracking treatments that do. These innovations significantly cut drug development costs and speed time-to-market.
Designing studies with planned interim looks at the data is a non-trivial task requiring intimate familiarity with complex statistical and mathematical methodologies. It's a daunting task for those unfamiliar with such disciplines.
Cytel's latest software East 4 overcomes this hurdle by making these complex techniques available in a powerful, yet easy-to-understand system. Now investigators can devote more time evaluating design options and trial data, instead of programming and learning difficult and unfamiliar concepts.
As a world leader in clinical trial optimization through advanced computational statistical methods, Cytel wholeheartedly endorses the FDA's Critical Path Initiative. We look forward to continuing our central role by providing trial system advancements that bridge the gap between science and humanity.
Xiao-Wei Zhu, PhD, Vice President, Cytel Inc.