The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring
Background: In 2017, the World Health Organization (WHO) issued a global alert identifying 12 bacteria in urgent need of new treatments. Main body: This study assesses the scientific community’s response to this alert by analyzing original research publications using LLMzCor, an AI-based tool de...
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2025
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| Acceso en línea: | https://repositorio.umaza.edu.ar/handle/00261/3591 |
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I56-R162-00261-35912025-09-17T14:36:55Z The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring Almonacid, Juan Eduardo Robledo Lombardo, Christian Romano, Mariana Quiroga, Agustina Cambuli Bianchi, Paula Hualpa, Mauricio Giai, Constanza Oviedo, Xiomara María Salgado Mansur, Ramiro Alejo Vallejo, Mariana Guadalupe Quintero, Cristián Andrés antibiotic antibiotic resistance automatic classifier treatment WHO Background: In 2017, the World Health Organization (WHO) issued a global alert identifying 12 bacteria in urgent need of new treatments. Main body: This study assesses the scientific community’s response to this alert by analyzing original research publications using LLMzCor, an AI-based tool developed and validated by our group. To compare trends, we focused on publications from 5 years before and after the alert, specifically on three bacteria listed in the WHO alert, sorted by priority level: Acinetobacter baumannii (Critical), Shigella spp (High), and Neisseria gonorrhoeae (Medium) and three non-listed as controls (Rickettsia spp., C. trachomatis, and C. difficile). Articles were classified into three categories: (i) identification of Resistant strains, (ii) development of New treatments, and (iii) Immunization strategies. Results: Although overall publications increased after the WHO alert, no statistically significant changes were found in the reports of Resistant strains over time. The development of New treatments for the listed bacteria showed a slight increase, between 2% and 10%. Furthermore, Immunization strategies remained relatively unchanged, with less than 2%. Meanwhile, LLMzCor demonstrated robust performance across categories, F1-scores ranging from 0.65 to 0.72 in key classifications, while recall peaked at 0.75, indicating a high capacity to identify relevant articles. These results support the model’s reliability for large-scale automated classification of scientific abstracts. Conclusion: These findings, supported by LLMzCor, underscore the urgency of a stronger WHO alert and action plans to develop new strategies against bacterial resistance. 2025-09-11T14:39:19Z 2025-09-11T14:39:19Z 2025 Artículo Científico Robledo Almonacid JE, Lombardo C, Romano M, Quiroga A, Cambuli Bianchi P, Hualpa M, Giai C, Oviedo XMA, Salgado Mansur RA, Vallejo MG and Quintero CA (2025) The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AIbased tool for its monitoring. Front. Pharmacol. 16:1633382. doi: 10.3389/fphar.2025.1633382 https://repositorio.umaza.edu.ar/handle/00261/3591 eng info:eu-repo/semantics/altIdentifier/url/10.3389/fphar.2025.1633382 application/pdf |
| institution |
Universidad Juan Agustín MAZA |
| institution_str |
I-56 |
| repository_str |
R-162 |
| collection |
UMAZA Digital (Universidad MAZA - Mendoza) |
| language |
Inglés |
| orig_language_str_mv |
eng |
| topic |
antibiotic antibiotic resistance automatic classifier treatment WHO |
| spellingShingle |
antibiotic antibiotic resistance automatic classifier treatment WHO Almonacid, Juan Eduardo Robledo Lombardo, Christian Romano, Mariana Quiroga, Agustina Cambuli Bianchi, Paula Hualpa, Mauricio Giai, Constanza Oviedo, Xiomara María Salgado Mansur, Ramiro Alejo Vallejo, Mariana Guadalupe Quintero, Cristián Andrés The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| topic_facet |
antibiotic antibiotic resistance automatic classifier treatment WHO |
| description |
Background: In 2017, the World Health Organization (WHO) issued a global alert
identifying 12 bacteria in urgent need of new treatments.
Main body: This study assesses the scientific community’s response to this alert
by analyzing original research publications using LLMzCor, an AI-based tool
developed and validated by our group. To compare trends, we focused on
publications from 5 years before and after the alert, specifically on three
bacteria listed in the WHO alert, sorted by priority level: Acinetobacter
baumannii (Critical), Shigella spp (High), and Neisseria gonorrhoeae (Medium)
and three non-listed as controls (Rickettsia spp., C. trachomatis, and C. difficile).
Articles were classified into three categories: (i) identification of Resistant strains,
(ii) development of New treatments, and (iii) Immunization strategies.
Results: Although overall publications increased after the WHO alert, no
statistically significant changes were found in the reports of Resistant strains
over time. The development of New treatments for the listed bacteria showed a
slight increase, between 2% and 10%. Furthermore, Immunization strategies
remained relatively unchanged, with less than 2%. Meanwhile, LLMzCor
demonstrated robust performance across categories, F1-scores ranging from
0.65 to 0.72 in key classifications, while recall peaked at 0.75, indicating a high
capacity to identify relevant articles. These results support the model’s reliability
for large-scale automated classification of scientific abstracts.
Conclusion: These findings, supported by LLMzCor, underscore the urgency of a
stronger WHO alert and action plans to develop new strategies against bacterial
resistance. |
| format |
Artículo Científico |
| author |
Almonacid, Juan Eduardo Robledo Lombardo, Christian Romano, Mariana Quiroga, Agustina Cambuli Bianchi, Paula Hualpa, Mauricio Giai, Constanza Oviedo, Xiomara María Salgado Mansur, Ramiro Alejo Vallejo, Mariana Guadalupe Quintero, Cristián Andrés |
| author_facet |
Almonacid, Juan Eduardo Robledo Lombardo, Christian Romano, Mariana Quiroga, Agustina Cambuli Bianchi, Paula Hualpa, Mauricio Giai, Constanza Oviedo, Xiomara María Salgado Mansur, Ramiro Alejo Vallejo, Mariana Guadalupe Quintero, Cristián Andrés |
| author_sort |
Almonacid, Juan Eduardo Robledo |
| title |
The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| title_short |
The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| title_full |
The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| title_fullStr |
The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| title_full_unstemmed |
The WHO’s critical bacteria list: scientific response eight years after its implementation and development of an AI-based tool for its monitoring |
| title_sort |
who’s critical bacteria list: scientific response eight years after its implementation and development of an ai-based tool for its monitoring |
| publishDate |
2025 |
| url |
https://repositorio.umaza.edu.ar/handle/00261/3591 |
| work_keys_str_mv |
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