Mathematical Methods for Clinical Trial Financial Strategy
When Cyrus Mehta introduced the Promising Zone Design over a decade ago, the new statistical method not only transformed the allocation of scarce resources within a clinical trial setting. The design also reconceptualized how sponsors could increase investment in their trials. By specifying various eventualities that could occur during an interim look, potential investors were better positioned to tie their investment strategy to the financial risk profile of the success of the new medicine or biologic. This ensured that risks taken by investors reflected expected gains.
Since the introduction of the promising zone, the propulsion of simulation technology and the power of new forecasting engines has generated even more methods to align clinical development with financial strategy.
Pareto Frontier and Statistical Performance
The performance characteristics of a clinical trial – power, speed, sample size – are not only critical for proving statistical rigor. They are also the primary source of risk and reward within the financial dimensions of clinical trial development. Put slightly differently, while many sponsors wait until after a clinical trial is over to consider market strategy, clinical trial design can give sponsors an unexpected benefit when planning market strategy by positioning a new drug or biologic for success, generating evidence with strong study power, and ensuring operational efficiencies.
The Pareto Frontier is a mathematical concept borrowed from economic theory, to refer to the set of options where it is impossible to improve along one desirable parameter without sacrificing something on another. For example, some clinical trial designs enable sponsors to increase power without sacrificing speed or cost of a trial. These trial designs then cause the sponsor to leave something on the table – the extra power that could have generated evidence, that would provide a strategic benefit during regulatory submission or even market strategy.
One of the most important strategic tools for those financing a clinical trial would then be to quickly identify those trial designs that do not leave something on the table; that is, those trial designs that are on the Pareto Frontier. This is easier said than done, with hundreds of thousands of potential clinical trial designs for consideration. New technology like Cytel’s Solara can take the resource limitations facing clinical development teams and quickly compute a Pareto Frontier, selecting dozens of Pareto optimized clinical trials from the millions under consideration.
Customized Scoring Functions
When it comes to the commercial prospects of a new drug or therapy, every clinical trial sponsor faces a constantly evolving landscape. Some must manage population samples, others must accelerate timelines, still others aim for a solid evidence package to elucidate the full value of a new therapy. While the primary goal of a clinical trial design will always be to reveal the safety and efficacy of a new medicine or biologic, the statistical design can often be built to accommodate secondary considerations that give a new product a strategic edge, without cost to scientific rigor.
A Scoring Function is a mathematical tool constructed to take all the trial designs that satisfy statistical requirements and resource limitations, and rank them in accordance with these objectives. Clinical trial sponsors can deliberate on what these objectives are, and weight them accordingly. A Scoring Function then scans all the eligible trial designs, and gives each a weighted score. They are then rank-ordered to ensure an objective measure of how well a clinical trial design satisfies strategic financial targets.
Convex Hulls are a geometric concept that refers to the smallest possible polygon that can be created from a set of points, say on a two-dimensional map. Cytel co-founder Professor Nitin Patel, recently presented a new line of research in which he investigates how this idea can be applied to optimized trial selection. He begins with the set of points on the Pareto Frontier, and reveals how principles that apply to Convex Hulls can be used along with customized scoring rules, for the easy selection of optimal statistical designs that also produce optimal net present value.
New Promising Zone Design
Finally, the Promising Zone Design mentioned earlier in this article refers to the basic design published a decade ago. Since then Cytel co-founder Cyrus Mehta has refined the Promising Zone to make it more suitable for investors and venture capitalists, seeking to build strong portfolios of assets. His recent presentation at the PSI Conference reveals new directions in his research.
About the Author of Blog:
Dr. Esha Senchaudhuri is a research and communications specialist, committed to helping scholars and scientists translate their research findings to public and private sector executives. At Cytel Esha leads content strategy and content production across the company's five business units. She received a doctorate from the London School of Economics in philosophy, and is a former early-career policy fellow of the American Academy of Arts and Sciences. She has taught medical ethics at the Harvard School of Public Health (TH Chan School), and sits on the Steering Committee of the Eastern Division of the Society for Women in Philosophy which is responsible for awarding the Distinguished Woman Philosopher Award.