Are You Making the Most of your Observational Data? How to Create a Synthetic Control from Your Natural History Study

August 7, 2020

In this blog from Cytel, a biostatistics and operations research provider, a case study is presented showing how real world data was utilized to conduct a natural history study, followed by the development of a synthetic control arm using the same datasets to support regulatory submission for an oncology product.  The case study describes the approach undertaken with the product while it was in Phase 2.  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.

In March 2019, FDA issued Guidance highlighting the importance of natural history studies.  Former FDA Director Scott Gottlieb acknowleded that a lack of knowledge about the natural history of certain diseases is a significant obstacle in rare disease drug development.

Natural history studies are typically prospective observational in design, but small populations of patients in rare disease makes enrollment difficult and sponsors tend to “save” these patients for actual clinical trials.  In oncology, observational studies may be considered unethical. Cytel advised using Real World Data for the purposes of conducting a natural history study, and then utilized these observational datasets to develop a synthetic control arm for regulatory submission. This allowed all new patients to enroll into the treatment arm of the trial.

Read more about the process described in this case study here:

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