Early-phase clinical trials play a critical role in drug development, particularly in determining the right dose and combination of treatments for later-stage testing. With the increasing complexity of combination therapies, traditional trial designs often struggle to keep pace.
In our recent webinar, Dr. Pavel Mozgunov (MRC Investigator, MRC Biostatistics Unit, University of Cambridge), Weishi Chen (PhD Student, MRC Biostatistics Unit, University of Cambridge), Matt George (Senior Statistician, Phastar), and Sam Hinsley (Moderator, Statistics Manager, Phastar) shared strategies to enhance efficiency, flexibility, and decision-making in early-phase combination trials.
Below, we have summarized three takeaways from the discussion:
1. Innovative Trial Designs Can Improve Efficiency
Traditional dose-finding approaches can be slow and inefficient, but adaptive trial designs offer a solution. These innovative designs allow researchers to make real-time adjustments based on the data collected during the trial. Adaptive designs help overcome traditional limitations by offering flexibility, enabling early identification of the most effective treatment combinations. This approach accelerates the trial process, improves decision-making, and increases the likelihood of identifying safe and effective therapies.
For example, by allowing the insertion of new dose levels mid-trial according to emerging data, researchers may avoid wasting resources on less promising combinations and instead focus on the most optimal treatment regimens. Novel research by Matt George has identified an effective method for achieving this.
2. Model-Based Designs Help Guide Trial Decisions
Certain model-based designs may offer a more effective way of exploring potential treatment combinations. By evaluating the likelihood of different toxicity orderings, researchers can reduce the complexity to a one-dimensional problem, allowing us to incorporate robust single-agent strategies.
Other Bayesian approaches also enable the dynamic updating of our beliefs as new data is gathered. This helps refine the number of combinations to explore and enhance the likelihood of reaching meaningful conclusions in a shorter amount of time.
3. Collaboration is Key to Advancing Trial Design
Successful implementation of adaptive trial designs depends heavily on collaboration between academic researchers, industry professionals, and regulatory bodies. These collaborations are essential in ensuring that trial designs are both scientifically rigorous and practically feasible. By fostering collaboration between stakeholders, trials can align with industry standards and regulatory requirements, increasing their chances of progressing smoothly and efficiently.
The involvement of regulatory bodies from the early stages of trial design ensures that studies meet necessary compliance standards, helping to avoid costly delays and ensuring that the study’s design is scientifically robust. Collaboration with industry professionals further refines trial strategies, helping to navigate the complexities of early-phase trials and adapt quickly to new information.
By working together, stakeholders can provide valuable feedback, share insights, and resolve issues that may arise, leading to a more effective and efficient clinical trial process. This collaborative approach ultimately accelerates drug development and helps ensure that the most promising treatments reach the market faster. At Phastar, we specialize in advanced statistical methodologies, adaptive trial designs, and ensuring the precision, pace, and quality of your drug development process.
