METADATA
last updated: 2026-03-02 RT
file_name: _context-commentary_regulatory-open-euas.md
category: regulatory
subcategory: open-euas
words: 864
tokens: 1190


CONTENT

## Context
This subcategory documents the concept of "open EUAs," the combination of open-source diagnostic protocols with open-access FDA authorization, which was central to FloodLAMP's regulatory strategy. For a comprehensive analysis of the concept, its history, regulatory mechanics, and implications, see the companion research report in this subcategory: `_AI_open-euas-open-access-diagnostics-report.md`.

The files here include:
- **FDA press release (Aug 15, 2020)** announcing the SalivaDirect EUA, which contains FDA's explicit use of "open source protocol" framing and describes the designated-laboratory model.
- **Anne Wyllie nomination letter (June 2022)** for the Reagan-Udall Foundation Innovation in Regulatory Science Award, written by FloodLAMP's founder, articulating the regulatory novelty of SalivaDirect's approach: an academic team seeking an IVD EUA without intending to manufacture kits, using CDC primers, fully disclosing ingredients, validating multiple suppliers and instruments, and working with FDA to create a designation process for CLIA labs.
- **Open EUA Consortium main document (late 2020)** recording FloodLAMP's attempt to convene multiple test developers around the open EUA model. The consortium aimed to build a suite of 5-8 open EUAs covering different sample types and technologies, with shared validation materials and supply chain coordination. It stalled quickly by end of 2020.

The "open EUA" concept, as analyzed in the AI report, is not merely about publishing protocols. It involves an institutional and legal pattern combining open-source protocols (fully disclosed, implementable with commodity components), open supply chains (multiple validated suppliers), and open-access authorization (multiple labs operating under one EUA through a steward/designation model). SalivaDirect remains the most prominent example in FDA's COVID-19 authorization corpus. FloodLAMP pursued the same approach for its LAMP-based tests and was unable to obtain authorization.

These files connect to the FDA correspondence subcategory (`regulatory/correspondence`), which documents FloodLAMP's direct engagement with the agency on its own open-source protocol EUA submissions, and to the FDA EUA submissions subcategory (`regulatory/fda-euas`), which contains FloodLAMP's submitted tests.


## Commentary
The open EUA concept was at the center of FloodLAMP's regulatory strategy, and we consider it one of the most important points of regulatory progress to emerge from the COVID-19 diagnostic response. The AI research report in this subcategory provides a thorough analysis; here we offer FloodLAMP's perspective.

SalivaDirect demonstrated that it was possible to build a scalable, supply-chain-resilient testing network under a single FDA authorization using commodity components and a steward/designation model. We modeled our own EUA submissions on this approach and nominated Anne Wyllie for the Reagan-Udall Foundation Innovation Award based on direct experience with the model and our assessment of its significance. The nomination letter in this subcategory lays out the case for why the open-source protocol EUA represented a genuine regulatory innovation, not just a scientific one.

The Open EUA Consortium was our attempt to scale the idea beyond a single test. We convened a small group of developers in late 2020, but the consortium stalled quickly. At one level,the reasons are well captured by the AI report's analysis: the HHS policy change in August 2020 reduced the regulatory incentive for open EUAs (labs could offer LDTs without an EUA), the stewardship burden was significant, and funding was not available to sustain the coordination effort. At another level, trying to coordinate this group was like herding cats. FloodLAMP founder, Randy True, decided it was just going to be easier to pursue the EUAs independently, so we validated and submitted three related tests, Colorimetric LAMP, Fluorimetric LAMP, and the Direct PCR from the same inactivated sample. The plan was to then either help other groups in the gLAMP community get their EUAs or collaborate with them to do under the FloodLAMP organization. In hindsight, this was quite overconfident.

FloodLAMP submitted multiple open-source protocol EUAs and was unable to obtain authorization, or to get meaningful engagement from FDA on these submissions (see `regulatory/correspondence`). The structural barriers identified in the AI report were real and material. The most striking is the asymmetry between government and non-government entities: the CDC was able to produce a test that any CLIA high-complexity lab in the country could run, simply by distributing reagents. No stewardship model, no lab-by-lab designation. When an academic lab (Yale/SalivaDirect) created something comparably open, the regulatory system required a full stewardship and designation infrastructure. When a small public benefit company (FloodLAMP) attempted the same, the barrier was even higher.

The AI report's analysis of the CDC test's Appendix A, the extraction-free protocol restricted to public health labs only despite being developed in response to a nationwide reagent shortage affecting all labs, captures a pattern we observed repeatedly: technical solutions existed but were constrained by institutional caution and regulatory framing rather than by scientific or safety considerations.

The "generics of diagnostics" framing from the nomination letter remains, in our assessment, directionally correct. The U.S. diagnostic regulatory system lacks a routine mechanism for deploying validated open protocols to competent laboratories without each lab filing its own submission or depending on a single steward's capacity. SalivaDirect showed one way to approximate this during an emergency. Whether the model can be institutionalized for future outbreaks is an open question, but the design patterns in the AI report, particularly the four-layer taxonomy of openness and the practical framework for future open-access diagnostics, may be a useful starting point.