Evidence map›Paper›PMID 40657161›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Trimming tiers - Motivations and means for de-risking select agents.

Elizabeth Wells, Christopher Grisham, Michael T Parker

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elizabeth WellsDepartment of Biology, Georgetown University, Washington, DC, United States.
Christopher GrishamDepartment of Biology, Georgetown University, Washington, DC, United States.
Michael T ParkerCollege of Arts & Sciences, Georgetown University, Washington, DC, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the United States, pathogens and toxins that pose a significant threat to public health are regulated via the Select Agents and Toxins list (SATL). Of those on the list, biological select agents and toxins (BSAT) deemed especially dangerous are designated "Tier 1", and are subject to more stringent regulations. While general criteria for the addition of BSAT to the SATL have been published, along with criteria for Tier 1 designation, there are no clearly defined, publicly available steps for de-tiering or de-listing BSAT, making it difficult to decipher paths to risk reduction. We set out to better understand how the government has historically chosen to list and tier BSAT, to create a generalized profile of Tier 1 and non-Tier 1 BSAT, and to design a methodology that the government can utilize in efforts of de-risking BSAT. To these ends, we conducted a literature review compiling key information on all BSAT, with a specific focus on development and availability of vaccines and therapeutics, as well as evidence and/or reports of prior weaponization efforts. We then performed statistical analyses to compare Tier 1 BSAT to non-Tier 1 BSAT, allowing us to develop a "prototype" that describes the characteristics that are typical of each. Finally, we used these results to design a set of "priority" experiments and threshold goals for perceived risk criteria, the results of which enable clearer avenues to de-risking, and potentially also de-tiering and de-listing, of BSAT. Our results represent a call to action to bolster biosecurity through the utilization of BSAT prototyping, key experiments, and threshold implementation, all in an effort to enable evidence-based risk reduction of select agents.

Indexed as

biological weaponsbiosecuritypolicyregulationselect agents

Identifiers

PMID40657161
PMCPMC12246755

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.