Pioneering open-source R and Python FDA submissions to set a new, innovative and efficient standard.

In the current landscape of the FDA submission process, the use of SAS software plays a dominant role, while examples of using open-source tools such as R and Python are scarce. This disproportion leads to a lack of well-established practices and standards, which in turn limits the exchange of knowledge and experience between organizations. The absence of publicly available examples of using R and Python in submission procedures results in a stifling of innovation and collaboration within the industry. Organizations, lacking a solid foundation to emulate or confidence in best practices, are reluctant to take risks on their own, which from the perspective of the entire industry, makes it difficult to introduce innovative solutions. A significant issue in the current submission process is ensuring result reproducibility. For the FDA review process to be reliable, it is necessary for reviewers to be able to run analyses in exactly the same way as the submitting team. When submissions are done in an open-source language, such as R, reviewers’ might have trouble reproducing the submitter’s environment. This significantly increases the risk of discrepancies and errors, underscoring the importance of developing solutions and standards that facilitate reproducibility in the submission process.