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Pareto Optimization for Clinical Trial Development



To continue our Summer Weekend Reads series, Cytel presents “Identifying Choice Trial Designs Using Pareto” by CSO Yannis Jemiai, PhD; Associate Director of Content Marketing Esha Senchaudhuri, PhD; and Cytel Co-Founder Nitin Patel, PhD. Please click below to access the full publication.

When designing a clinical trial, there are many factors to balance, such as cost and speed; for example, shortening a trial may save on time, but it also may increase the cost to unacceptable levels. So how can you be sure that your trial design is not only feasible, but optimal as well?

Pareto Optimal Design

Pareto Optimal designs are those constructed in such a way that there is no way to improve on any one design parameter without worsening another. Any trial design that does not meet this definition is thus either not feasible given the constraints of the trial sponsor or has a feature that is not optimized. Identifying Pareto Optimal designs can be used for the strategic selection of trial designs that best align with an organization’s business goals, such as speed-to-market or savings in development costs.

And to better understand the nuanced trade-offs in speed, savings, and success, trials sponsors must utilize the Pareto Frontier.


The Pareto Frontier


The Pareto Frontier refers to a set of Pareto Optimal designs that, when combined with a Scoring Algorithm, can be evaluated on how well these designs align with previously determined values. These values are then weighted and scored, enabling the trial sponsor to not only select the optimal design, but to avoid overlooking a clear gain at zero cost.

The use of Pareto Optimization for the rapid identification of strategic design options and the ranking of those designs through a Scoring Algorithm is a method available with Solara®.

Click below to learn more about Pareto Optimization:


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