METADATA
last updated: 2026-03-22 RT
file_name: _context-commentary_regulatory-open-euas.md
category: regulatory
subcategory: open-euas
gfile_url: https://docs.google.com/document/d/1ysH5-xFHTdvN6e2LJ5IjFgOlP7Kjb7GZZomspeV4hQg 
words: 1507
tokens: 2033


CONTENT

## Context
This subcategory `regulatory/open-euas` documents the concept of "open EUAs," the combination of open-source diagnostic protocols with a new designation-granting FDA authorization. The Open EUA approach 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`.

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 the 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 is the most prominent example in FDA's COVID-19 set of EUAs. FloodLAMP pursued the same approach for its colorimetric LAMP and PCR tests but was unable to obtain authorization.

A related mechanism documented in this subcategory is the FDA "right of reference," which allows a new test developer to rely on validation data that FDA already reviewed for another EUA submission. During the COVID-19 emergency, a small number of these rights of reference were granted broadly and publicly — most notably by the CDC for its assay data, and by Quantigen Biosciences for specimen-collection swab-stability data supported by the Gates Foundation. The companion report `_AI_COVID_Rights_of_Reference_Report` analyzes the public, broad, and private rights of reference used across the EUA ecosystem and documents how the Quantigen RoR was reused by multiple unrelated sponsors.

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


## 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.

The FDA called SalivaDirect's EUA in mid-2020 "the most unusual submission they had ever received." Dr. Wyllie had worked with two former FDA reviewers to craft a multifaceted creative approach to an "open-source protocol" EUA. When the agency issued the authorization, its own press release called SalivaDirect a "game changer" and highlighted it as an example of "the FDA working with test developers to bring the most innovative technology to market." The FDA Commissioner explicitly encouraged other test developers to "work with the agency to create innovative, effective products to help address the COVID-19 pandemic." We took that invitation at face value and brought forward our own open-source protocol EUAs. We got nowhere with the FDA.

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. 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 challenging. FloodLAMP founder, Randy True, decided to just pursue the open EUAs ourselves first, so we then validated and submitted three related tests, Colorimetric LAMP, Fluorimetric LAMP, and Direct PCR from the same inactivated sample. The plan was to then help other groups in the gLAMP community obtain their own EUAs or collaborate with them under the FloodLAMP organization. In hindsight, this was quite overconfident.

One step we took that went beyond even SalivaDirect was committing to a blanket, open right of reference. In our March 2021 EUA cover letter, we stated that FloodLAMP would "offer a blanket right of reference to the LAMP primer validation data for any IVD test developer or CLIA lab," modeled on what the CDC had done for PCR primers (see `regulatory/fl-fda-correspondence`). We reiterated that commitment in our October 2021 correspondence with Tim Stenzel. A right of reference is a meaningful legal commitment: it allows any qualifying developer to rely on FDA-reviewed validation data without obtaining a separate permission letter, effectively functioning as a broad, open license over the underlying regulatory data. The CDC and Quantigen Biosciences are the clearest COVID-era precedents for this kind of blanket RoR, as documented in `_AI_COVID_Rights_of_Reference_Report`. SalivaDirect, by contrast, operated through a designation model — labs ran the test under Yale's EUA — rather than through an open right of reference enabling other developers to build on its validation data for their own EUAs. That said, by openly disclosing their chemical compositions, validated suppliers, and full protocol, the SalivaDirect team achieved something of enormous practical significance: many CLIA labs built their own LDTs directly from the published SalivaDirect protocol during the period when HHS had removed FDA oversight of LDTs, and it would not surprise us if the volume of tests run outside the SalivaDirect EUA exceeded the volume run under it by an order of magnitude or more. The designation process itself was, to our understanding, offered at no or minimal charge to labs, making SalivaDirect a massive and impactful public good. It is possible that the SalivaDirect team also granted open rights of reference in one or more of their 24 EUA amendments, but the original EUA Summary in this subcategory does not mention a right of reference, and we are not aware of such a grant.

It is worth underscoring why an open EUA is so much more valuable than simply publishing a protocol and expecting labs to develop their own LDTs. Developing and validating an LDT requires substantial expertise such as in silico bioinformatic analysis, wet-lab analytical and clinical performance characterization, cross-reactivity and interference testing. Only a small, single-digit percentage of moderate and high-complexity CLIA laboratories have the resources and personnel to undertake an LDT. A test that has gone through an EUA, whether sold commercially as a kit or provided as an open protocol, arrives at the clinical lab already validated with FDA-reviewed performance data, making it relatively straightforward for any qualified lab to implement. The open EUA model is the mechanism that bridges the gap between a published protocol and a test that the broad base of clinical laboratories can actually run.

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/fl-fda-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.

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 accomplish 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.