Evidence map›Paper›PMID 35350133›Full record

ArticleJAC-antimicrobial resistance2022

Improved non-redundant species screening panels for benchmarking the performance of new investigational antibacterial candidates against Category A and B priority pathogens.

Jason E Cummings, Zaid Abdo, Richard A Slayden

Abstract read
In one paragraph

Article in JAC-antimicrobial resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. RapidAntimicrobial agents and chemotherapy · 2024
    Article
  3. Article
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.

Jason E CummingsDepartment of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, 80523-2025 CO, USA.
Zaid AbdoDepartment of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, 80523-2025 CO, USA.
Richard A SlaydenDepartment of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, 80523-2025 CO, USA.ORCID https://orcid.org/0000-0001-6857-7277

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: NIAID has a programme for testing drug candidates against biodefense and emerging bacterial pathogens that uses defined strain panels consisting of standard laboratory reference strains and strains of clinical origin. Objectives: The current studies were performed to assess the activity of standard-of-care drugs, determine benchmark criteria for new investigational antibacterial candidate prioritization and identify reduced non-redundant strain panels for candidate performance classification. Methods: The susceptibilities of each strain in the screening panels to 40 standard-of-care drugs and clinical drug combinations were determined by percentage growth inhibition using multiple concentrations, a method commonly used in efficient high-throughput screening efforts. The drug susceptibility of each strain was categorized based on interpretive criteria to benchmark the activity of each standard-of-care drug and drug combination, followed by confirmation of select active drugs. Exact match and clustering analyses defined focused non-redundant species and pan-species screening panels. Results: This process revealed a broad spectrum of susceptibilities among strains in each species, with important differences between the standard laboratory reference strains and strains of clinical origin. Exact match and clustering analyses identified subsets of non-redundant strains that can more efficiently classify drug activity resulting in individual species screening panels, a pan-species screening panel and a pan-species maximum resistance panel. Conclusions: This study resulted in improved non-redundant species screening panels for benchmarking the performance of new investigational antibacterial candidates with the greatest potential for efficacy against clinically relevant Category A and B priority and emerging pathogens.

Identifiers

PMID35350133
PMCPMC8947225

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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.