The eSTAR 510k

by | May 21, 2023 | 510k, FDA, Regulatory

The voluntary eSTAR (electronic Submission Template And Resource) is a fillable portable document format (PDF) document that seeks to make 510(k) and De Novo submissions quicker and easier due to its automation from its form construction and autofill capability [1]. It is a free single PDF document that can be easily downloaded, edited, and saved for future work progress. Its simplicity has led to the speed up in the submission process as well as the review processes as it is automatically verified and is not subject to the Refuse to Accept (RTA) review. It is accepted at both the Center for Devices and Radiological Health (CDRH) and the Center for Biologics Evaluation and Resarch (CBER). The only caveat is that Adobe Pro is required to edit and save the eSTAR.

Health Canada (HC) has just finished a trial with the eSTAR and hopes to eventually deploy it just like the United States has. This adaptation would allow for a standardization of the protocol for 510(k)’s and De NoVo’s between the FDA and HC. A single submission of the eSTAR would push it to both the FDA and HC, if requested, and would not require the current double submission. This would allow for the streamlining of 510(k) and De Novo requests which would ultimately speed up the process of getting the medical device to market.

Starting October 1, 2023, all 510(k) submissions will have to take the form of an eSTAR, while de Novo requests will remain voluntary until further notice [1]. This implementation of the eSTAR does make 510(k) and De Novo submissions substantially easier as well as quicker. Eventually, we might even see the eSTAR being deployed for 513(g) requests.

If you need help identifying whether your medical device needs a 510(k) or De Novo submission to the FDA, the team of experts at EMMA International can help! Contact us today at or by calling 248-987-4497.

[1] FDA. (2018, June 29). Voluntary eSTAR Program. U.S. Food and Drug Administration.

Chris Powell

Chris Powell

Chris is a highly skilled research scientist with a focus on bioinformatics, ecological modeling, big data analysis, genomics/proteomics, phylogenomics, and molecular clock analyses. He holds a PhD in Biology from Oakland University, specializing in Bioinformatics, Genomics, and Phylogenetics. Additionally, he has a Master of Science degree in Biology, where he worked in ecology and specialized in ecological data analyses using various techniques, such as timeseries analyses, statistical inference, survival modeling, and stochastic processes modeling. Chris has a strong background in Linux, computer hardware, mathematical modeling, and programming languages, including HTML, CSS, JavaScript, Perl, and R Programming Language. He brings 5+ years of teaching experience and over 12 years of research experience to EMMA International, showcasing a keen interest in data sciences that utilize big data to answer pressing questions and further our understanding of the world.

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