Regulators in both the United States and Europe have responded positively to the use of synthetic control arms (SCA)s in clinical development. The desire to speed up and lower the cost of drug development, coupled with increased availability of rich real-world data, contributed to the increased willingness towards using SCAs as supplementary evidence to accompany regulatory submissions using single arm trial data only.
As with any sophisticated statistical method, deciding on the optimal SCA approach is a necessary condition to ensure robustness of findings. Cytel’s new audiobook "Demystifying synthetic control arms", explains the concept of synthetic controls and offers insights on some common quantitative strategies for trial design and regulatory submission. Continue reading this blog to learn more and get access to the audiobook.
SCAs are best suited for situations when a single arm trial is run in a patient population which is molecularly defined, allowing for a clearly defined historical or real-world control group to be created. They are also useful in situations where Randomized Control Trials opt to enroll some, but fewer patients into the control arm. The use of SCA has enabled investigators to leverage combined data from uncontrolled single-arm trials and post-market studies to create much smaller trials.
The use of SCA enables optimization of datasets across different studies. For example, Cytel recently supported a biotech with a Phase 2 Study in oncology where the Regulators had requested a natural history of disease study, which tracks disease progression in the absence of any form intervention. These studies are used to build disease-models that can then inform a range of development opportunities within a drug development program. Natural history studies can be prospective observational studies, but given the limited patients available for enrolment, sponsors often prefer to save them for the actual clinical trial. For oncology patients, designing such observational studies might also be unethical.
Cytel advised using Real World Data for the purposes of conducting a natural history study, and then building a synthetic control arm using the same datasets to support regulatory submission. This allowed all new patients to enroll into the treatment arm of the trial.
Just as various adaptations suit different needs in adaptive trial design, the types of data available to sponsors, the desired sample size, and the anticipated length of a trial might determine the right approach to designing an SCA. There is a need for continuing education to understand the various ways SCAs are constructed. Cytel’s new audiobook is an effort to explain common strategies for the construction of SCAs, and to give a high-level overview of how statisticians think through challenges encountered during trial design.