The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
The rapid pace of technology has opened up numerous avenues for advanced innovative clinical trial design, but how can we use this to propel clinical development goals like maximizing revenue, or ensuring a commercially viable product? When operational constraints are limiting, how do we achieve the best possible trial design? What should we do if a competitor is edging us out of the market?
While we know that the statistical design of clinical trials can shorten trials or set realistic enrollment goals, there is still a growing need to tie these features of trial design directly to commercial revenue. Clinical development teams would ideally know how much they are willing to spend for an incremental gain in statistical power, or the marginal financial gains in waiting a week to unblind data.
The good news is the industry is getting there. Here are 5 Questions to help you begin your journey towards the Re-imagined Clinical Trial:
When designing clinical trials, biostatisticians and clinical development teams are often faced with a conundrum. Given the parameters of their clinical study, they usually begin with five or six possible design options and begin to explore the most promising ones. The likelihood is that none of these trials will be optimal designs. Rather, they meet certain criteria that are “good enough” at which point, clinical development teams might begin to lead one way or another.
As a part of Cytel’s Advanced Design Framework, a new Framework for the statistical design of clinical trials, Cytel discovered that a specific combination of process changes and technological advances has the potential to increase clinical development productivity by 10-20%. The Framework summarizes these as Thoroughly Explore, Decide Together and Communicate Tradeoffs. Here are 7 key features of this improved strategic framework. Alternatively, watch the webinar of our Chief Scientific Officer Yannis Jemiai discussing this Advanced Design Framework.
Increasing Clinical Development Productivity Using Statistics and Cloud-Computing
The need for Re-imagining Clinical Trials: A recent survey conducted by Cytel found that only 42% of respondents reported using any complex or innovative clinical trial designs beyond the familiar group sequential approach. Although regulators respond quite favorably to such designs, sponsors have remained hesitant to use them.
A combination of technological and process advances are necessary to overcome mechanisms that contribute to stagnating statistical innovation in clinical development. Cytel responded by creating this new whitepaper that provides a new strategic framework that can help Clinical Development teams leverage cloud-computing and begin to initiate process changes, necessary to increase development productivity by 10-20%.
The current state of the clinical trials industry faces a challenge that was only hypothetical three or four years ago. Thanks to the advent of cloud-computing and advances in simulation technology, sponsors can now design hundreds of thousands of clinical trials in less than an hour. Yet how do we choose amongst all of these myriad options in a way that optimizes commercial prospects? Cytel’s Chief Scientific Officer sits down with us to discuss the Re-imagined Clinical Trial.
The widespread use of cloud-computing has altered the clinical trial design process. Whereas three or four years ago, it would take a statistician perhaps two or three days to design five clinical trial designs, a well-resourced statistician can now simulate and model well over 100,000 designs in less than 30 minutes. How does this affect the process of designing clinical trials
According to Yannis Jemiai, Chief Scientific Officer at Cytel, a combination of technology and process changes can establish the foundation for significant increases in productivity. Yannis argues that uncertainty should not be viewed as a challenge but an opportunity. Using statisticians strategically as well as tactically throughout the design process can help R&D teams drive commercial value for greater speed, savings and success.