When is a study design considered to be optimal? A good design performs well not only under the ideal target scenario but even in situations where you deviate from the assumptions made by the team.
Unfortunately, the lack of time and tools prevents most of you from finding the optimal design options for your study. It is a complex endeavor and there are many factors at play including unknowns for which you have to account in design. In a recent webinar, Dr. Yannis Jemiai, Cytel’s Chief Scientific Officer, talks about a unique new solution that unifies statistics and strategy to optimize clinical trial design.
Development teams are under pressure to deliver more, faster, and with less. They are often left to explore only a few options in depth or several options superficially. Ideally, we would like to look at the full map of possibilities and find the global optimum; the best design that fits your needs, your priorities and your company's business objectives. This implies, the study team needs to align on priorities and trade-offs and understand how different designs can meet these challenges and answer their questions. Trying to do this in near real time is very challenging, given tools that are currently available. As the process is iterative, statisticians have to go back to their desks and look at various options for design within the limited time that they have in hand. Intuition combined with expertise gained over time can be a great guide. However, it is still very difficult to have confidence that you have come up with the best design for your study, considering the wide variety of possibilities that are available.
Cytel’s Solara enables exponentially larger exploration of the study design space
Solara enables the product development teams to explore millions of clinical trial options to identify optimal designs. It expands the map so that you can identify the optimal design as a team by combining statistical rigor with clinical strategy to inform business outcomes.
Study designs that have been optimized using Solara generate, on average, 10-20% savings in speed, cost, or probability of success. These improvements are driven by the identification of improved combinations of design variables that would rarely have been found through manual exploration.
How does Solara do this?
Solara empowers product development teams to align on strategies and priorities, whether that is faster time to market, reducing sample size or increasing probability of success. Your teams can select an optimal design together, confident that you have explored the full space of designs and are able to communicate trade-offs between various options in a clear and concise way.
It is a decision-support platform for development teams to improve R&D efficiency and give new therapies a better chance of getting to market. By activating the full power of biostatisticians, development teams using Solara can confidently select smarter statistical designs with the potential to benefit patients -- and your bottom line.
To learn more about the power of Solara with an example in second-line Urothelial Carcinoma, watch the on demand webinar by Yannis.
About the Author:
Mansha Sachdev specializes in content creation and knowledge management. She holds an MBA degree and has 11 years of experience in handling various facets of marketing, across industries. At Cytel, Mansha is a Content Marketing Manager and is responsible for producing informative content that is related to the pharmaceutical and medical devices industries.
