A Non-Technical Guide to Statistically-Informed Clinical Strategy
Clinical trial sponsors are more likely than ever to use the power of simulation and forecasting to evaluate the performance of many potential clinical trial designs. The result is that they have thousands of designs across millions of environmental scenarios from which to choose.
Often such forecasting might reveal new statistical designs that were previously not considered, with the promise of greater study power, smaller sample size, accelerated timelines and other desirable features. As the number of innovative trial designs grow, the specific adaptations suitable for a trial will warrant tactical deliberation on necessary tradeoffs between these parameters. Without a strategy for tackling these tradeoffs, many will experience missed opportunities to accelerate trials and channel critical new medicines towards the patients who need them most.
A common challenge in understanding these tradeoffs involves determining which set of clinical trial designs to evaluate, when making strategic decisions about timelines, resources, upfront costs, and study power. Every statistical design will provide a specific measure for each of these parameters. Yet, if there are thousands or millions of trial designs and environmental scenarios, evaluating every single design on a case by case basis will not be an option.
A new Cytel position paper shows sponsors how to quickly identify the set of trial designs to evaluate, and then deliberate and optimize using quantitative decision tools. The paper provides a brief, non-technical introduction to common business principles like Pareto Frontiers and scoring algorithms. Using these concepts, Cytel then demonstrates how a clinical strategy platform like SolaraTM can quickly identify the set of designs that have been optimized for speed or power, and then rank ordered in accordance with a range of sponsor goals from anticipated return on investment to proof of therapeutic value.
A comprehensive approach to clinical strategy requires a nuanced understanding of both biomedicine and essential business principles like optimization and valuation. Strategic deliberation must therefore find a way to integrate findings from both fields. The paper serves as an easy guide to statistically-informed clinical strategy.
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 Society for Women in Philosophy's Eastern Division, which is responsible for awarding the Distinguished Woman in Philosophy Award.