Evidence map›Paper›PMID 39858356›Full record

ArticleAntibiotics (Basel, Switzerland)2025

Chemometric Methods-A Valuable Tool for Investigating the Interactions Between Antifungal Drugs (Including Antifungal Antibiotics) and Food.

Agnieszka Wiesner-Kiełczewska, Paweł Zagrodzki, Alicja Gawalska, Paweł Paśko

Abstract read
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. A Comprehensive Overview ofJournal of fungi (Basel, Switzerland) · 2025
    Review
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

4 authors.

Agnieszka Wiesner-KiełczewskaDoctoral School of Medical and Health Sciences, Jagiellonian University Medical College, 31-008 Cracow, Poland.ORCID 0000-0002-4926-6120
Paweł ZagrodzkiDepartment of Food Chemistry and Nutrition, Faculty of Pharmacy, Jagiellonian University Medical College, 31-008 Cracow, Poland.ORCID 0000-0002-5101-036X
Alicja GawalskaDepartment of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, 31-008 Cracow, Poland.ORCID 0000-0002-3131-9300
Paweł PaśkoDepartment of Food Chemistry and Nutrition, Faculty of Pharmacy, Jagiellonian University Medical College, 31-008 Cracow, Poland.ORCID 0000-0002-4821-4492

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesDeveloping antifungal drugs with lower potential for interactions with food may help to optimize treatment and reduce the risk of antimicrobial resistance. Chemometrics uses statistical and mathematical methods to analyze multivariate chemical data, enabling the identification of key correlations and simplifying data interpretation. We used the partial least squares (PLS) approach to explore the correlations between various characteristics of oral antifungal drugs (including antifungal antibiotics) and dietary interventions, aiming to identify patterns that could inform the optimization of antifungal therapy.

methodsWe analyzed 15 oral antifungal drugs, including azoles (8), antifungal antibiotics (4), antifungal antimetabolites (1), squalene epoxidase inhibitors (1), and glucan synthase inhibitors (1). The input dataset comprised information from published clinical trials, chemical records, and calculations. We constructed PLS models with changes in the pharmacokinetic parameters (∆AUC, area under the curve; ∆C

resultsIn the final PLS model with food as an intervention, we effectively reduced the dimensionality of the dataset while retaining a substantial percentage of the original information (variance), as significant components explained 69.8% and 17.5% of the predictor and response parameter variances, respectively. The PLS model was significant because its components met the cross-validation criteria. We obtained six significant positive and negative correlations between the descriptors related to atoms and the postprandial ∆T

conclusionsThe PLS method is valuable for investigating interactions between antifungal drugs (including antifungal antibiotics) and food. The correlations obtained can be used in drug modeling to predict interactions with dietary interventions based on the antifungal drug's chemical structure. Incorporating chemometric techniques into the early drug development stages could facilitate the design of antifungal antibiotics and other antifungal agents with optimized absorption in the presence of dietary components.

Indexed as

antifungal antibioticsantifungalsantimicrobial resistancechemometricsfoodfood–drug interactioninteractionpartial least square

Identifiers

PMID39858356
PMCPMC11761243

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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.