Synthetic Control Arm®

When a concurrent control arm isn’t feasible or appropriate, results are harder to interpret, slowing decisions and increasing risk.

An external control arm (ECA) uses patient data from outside the trial as a scientifically rigorous comparator. Medidata Synthetic Control Arm® delivers that evidence using validated, patient-level clinical trial data, so you can move forward with confidence when randomization isn’t an option.

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Video transcript: Glioblastoma is by far one of the most aggressive forms of brain cancer. In most cases, you're expecting survival outcomes of these patients to be a few weeks to a few months at the most. If you look at very recent past few phase three clinical trials with different therapies that are being used for recurrent GBM, you see that they show good data in a phase one clinical trial. They might show you some good data in phase two clinical trials, but eventually when you get to the registration trial, the pivotal phase three clinical trial, that's where these drugs end up failing when you conduct a phase three registration trial. The big challenge is that patients know that there is an equal chance that half of them will end up in a control arm where they'll get the standard of care and the other half will get the experimental therapy. These patients know, the families know that there is a finite time period. And if they are then assigned to a standard of care arm which has not improved outcomes for patients, they quickly move away. And that makes it very difficult for a company like us to do a successful or to conduct a successful phase three clinical trial without having so many patients dropping out from your study. And this is where the external control arm or the synthetic control arm plays a big role. This is where Medidata Acorn AI came into play for medicine. They had this incredible, ability to generate a synthetic control arm. Instead of relying on literature data, we would be able to collect data from patients that have been matched, nearly equivalent to the patients that were treated in our clinical trial. We are substantially de risking what we might do in a phase three clinical trial by making sure that the patients that we treated in our treatment arm, were identical to the patients that would have received standard of care. Very quickly, we got the full team from Medidata contributing and making suggestions that literally rolled up their sleeves and got into all our data and guided us carefully in terms of not only how we were to analyze our data, but also suggesting ways to improve a clinical trial design. They were essentially part of our statistical group, not only from the very beginning, but all the way to our meeting with the FDA, preparing our package to submission to the FDA. What we were able to get from the FDA was, in fact, the very first design of a phase three registration trial, where the majority of patients would come from a synthetic control arm or an external control arm. So that was a big accomplishment for us. And when you talk about dealing with the impossible, this is basically what we were able to accomplish. Suddenly, the odds of patients being allocated to a control arm is dramatically reduced, and therefore, allows companies like us to conduct a clinical trial efficiently, quickly, faster, and of course at a lower cost, eventually getting the drug to the patient much more sooner, particularly in these kind of diseases which are life threatening. The reason they come into a clinical trial is the hope that they will get something better out there. We end up creating a situation which is satisfying for the patient, but more importantly, we set the stage for the next therapeutic approach, next combination approach, or for another kind of disease instead of GBM. Perhaps we can open the door to other companies pursuing these challenging diseases and take our route. And hopefully they'll learn from it if that's what makes you wake up first in the morning and go and do this.

Advance Your Trials with Clinical-grade Evidence

38 K+ clinical trials

Validated, patient-level data from controlled studies

12 M+ patients

With endpoints and covariates captured as originally collected

Built for scientific credibility

Not reconstructed from fragmented real-world data

Turn Data into Decisive Advantage

Regulatory Confidence

Strengthen Your Regulatory Submission

Support single-arm Phase II studies, accelerated approvals, and select confirmatory Phase III trials with credible external comparators.

Medidata Synthetic Control Arm® enables direct outcome comparisons against standard of care, helping you justify next-phase decisions, augment or replace control arms, and engage regulators with confidence.

Our team brings deep regulatory, biostatistics, data science, and oncology expertise, including former FDA, pharma, and academic leaders.

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AWARDS

2023 Best in Real-world Evidence

INDUSTRY RECOGNITION

2021 Best AI-based Solution for Healthcare

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FAQ

Medidata Synthetic Control Arm® is the only external control arm created using cross-industry historical clinical trial data from over 38,000 clinical trials and 12 million patients. Unlike real-world data (RWD) from electronic health records, this solution uses de-identified patient-level data complete with covariates and endpoints exactly as they were captured in clinical protocols, providing a standard of data quality that accurately reflects control groups for your specific patient subpopulation.

Yes. The solution is designed to support regulatory interactions, such as enhancing single-arm Phase II trials, supporting accelerated approval submissions, and aiding confirmatory Phase III trials in certain indications.

Medidata’s team includes former FDA officials and regulatory experts who work as an extension of your team to ensure the external control group is scientifically rigorous and fit for regulatory purpose.

By reducing or eliminating the need to recruit a concurrent control group, SCA significantly eases patient recruitment and retention challenges, especially in rare or life-threatening diseases where standard-of-care treatments are inadequate.

This approach can drastically reduce enrollment requirements; for example, Medidata Synthetic Control Arm® helped Medicenna reduce their Phase III registration trial enrollment by two-thirds.

Unlike relying on aggregate data from medical literature, Medidata Synthetic Control Arm® leverages patient-level data to precisely choose matching control patients. Statistical methods are applied in a dynamic matching process using baseline demographics and disease characteristics to generate a historical patient group that closely matches the experimentally treated patients, ensuring a more scientifically valid comparison.

Yes. Medidata offers a variety of training options for our clients and partners, including both self-paced and instructor-led courses. To learn more about available courses and to access our resources, please visit the Medidata Global Education and Training section.