Adding more power to Phase 2 clinical trials with our latest TwinRCT update
By Rachel Kalmar, Principal Product Manager
In the world of drug development, Phase 2 trials are crucial. They give us an early peek at whether a new treatment might work for a specific disease indication. The goal? To make these trials as powerful as possible, ensuring that if there's a real benefit, we don't miss it. The more highly powered the trial, the more likely we can detect a treatment effect. This step is vital because it decides whether we proceed to Phase 3, which involves a significant investment in time and resources, with trials expanding from 300 to potentially 3000+ participants over one to four years1. By optimizing Phase 2 trials, we streamline the decision-making process, saving valuable time and resources as we move closer to potential breakthroughs.
TwinRCTsTM add Power to Phase 2 Trials
Seeking more power in Phase 2 trials is a common approach to quickly and accurately understand a new drug's potential benefits. Traditionally, increasing the number of participants could help, but it's a slow and expensive approach.
Enter a smarter solution: Unlearn's TwinRCTsTM. TwinRCTs are randomized controlled trials (RCTs) that utilize digital twins of individual trial participants to enhance the study's power and efficiency. In the context of TwinRCTs, a digital twin is a comprehensive forecast of a participant's future clinical outcomes and is generated with our AI models trained on patient-level data. Prognostic scores derived from these digital twins are used in our PROCOVATM method. PROCOVA incorporates the scores into the analysis of clinical trial data as 'super covariates.' It's a way to adjust for individual differences more accurately, making the estimation of treatment effects more nuanced and precise. Since these prognostic scores closely correlate with actual outcomes, they enhance the reliability of treatment effect estimations.
PROCOVA is qualified by the European Medicines Agency and fully aligns with FDA guidance for either reducing trial size or effectively enhancing its power. This is crucial for Phase 2 trials, where the aim is to gauge a drug's effectiveness efficiently.
Get Even More Power from TwinRCTs
Our updated TwinRCT 3.0 solution improves decision-making in Phase 2 clinical trials by adding more power. It does so by leveraging additional data from prior clinical trials, making it even more powerful for evaluating treatments more efficiently. This means we can now offer even stronger evidence for decision-making in Phase 2 trials, ensuring that new therapies are assessed with the highest accuracy and more quickly.
Unlearn’s new cutting-edge clinical methodologies will be especially beneficial for trials focusing on efficacy and for conducting interim analyses. For those eager to dive deeper into the science, our recent publication outlines the innovative clinical method we have incorporated into our TwinRCTs.
The table below shows the results of a case study reanalyzing a completed clinical trial in mild to moderate Alzheimer’s Disease2. This was an 18-month study with CDR-Sum of Boxes as the co-primary endpoint. To achieve the same power as TwinRCT 3.0, an ANOVA analysis would require 23% more trial participants, adding up to an estimated five months of enrollment. This highlights the efficiency and precision our updated TwinRCTs bring to the table, marking a substantial step forward in clinical trial design and analysis.
* The prior in our Phase 2 solution was selected to control maximum Type I error rate.
https://www.fda.gov/patients/drug-development-process/step-3-clinical-research
This trial was not included in Unlearn’s model training data