Evidence map›Paper›PMID 39204172›Full record

ReviewPharmaceuticals (Basel, Switzerland)2024

In Vitro Resistance-Predicting Studies and In Vitro Resistance-Related Parameters-A Hit-to-Lead Perspective.

Joanna Krajewska, Stefan Tyski, Agnieszka E Laudy

Abstract readReview
In one paragraph

Review in Pharmaceuticals (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Joanna KrajewskaDepartment of Environmental Health and Safety, National Institute of Public Health NIH-National Research Institute, 00-791 Warsaw, Poland.ORCID 0000-0002-4963-9521
Stefan TyskiDepartment of Pharmaceutical Microbiology and Laboratory Diagnostic, National Medicines Institute, 00-725 Warsaw, Poland.ORCID 0000-0003-3352-038X
Agnieszka E LaudyDepartment of Pharmaceutical Microbiology and Bioanalysis, Medical University of Warsaw, 02-097 Warsaw, Poland.ORCID 0000-0002-5989-4462

Funding

National Science Center UMO-2018/31/B/ST5/00210
6 · The paper itself

Abstract

Despite the urgent need for new antibiotics, very few innovative antibiotics have recently entered clinics or clinical trials. To provide a constant supply of new drug candidates optimized in terms of their potential to select for resistance in natural settings, in vitro resistance-predicting studies need to be improved and scaled up. In this review, the following in vitro parameters are presented: frequency of spontaneous mutant selection (FSMS), mutant prevention concentration (MPC), dominant mutant prevention concentration (MPC-D), inferior-mutant prevention concentration (MPC-F), and minimal selective concentration (MSC). The utility of various adaptive laboratory evolution (ALE) approaches (serial transfer, continuous culture, and evolution in spatiotemporal microenvironments) for comparing hits in terms of the level and time required for multistep resistance to emerge is discussed. We also consider how the hit-to-lead stage can benefit from high-throughput ALE setups based on robotic workstations, do-it-yourself (DIY) continuous cultivation systems, microbial evolution and growth arena (MEGA) plates, soft agar gradient evolution (SAGE) plates, microfluidic chips, or microdroplet technology. Finally, approaches for evaluating the fitness of in vitro-generated resistant mutants are presented. This review aims to draw attention to newly emerged ideas on how to improve the in vitro forecasting of the potential of compounds to select for resistance in natural settings.

Indexed as

ALEantimicrobial agentsantimicrobial resistancehit-to-lead stageMPCmutant selectionresistance-related parameters

Identifiers

PMID39204172
PMCPMC11357384

What Socratic holds

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Registered trials

None linked

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 Socratic graph.