ReviewEnvironmental health : a global access science source2025
Human health risk assessment for microbial pesticides in the EU: challenges and perspectives.
Review in Environmental health : a global access science source, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Antimicrobial Peptides, Bacteriocins and Mycocins as Natural Antimicrobials: Applications in Food Safety, Agriculture and Healthcare.Antibiotics (Basel, Switzerland) · 2026Review
- Risk assessment of two new pesticides based on the intestinal fungal community construction and growth status of predatory insects (Frontiers in microbiology · 2025Article
- OrbiTox: a visualization platform for NAMs and read-across exploration of multi-domain data.Frontiers in pharmacology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The risk assessment of microbial pesticides in the European Union (EU) is covered by a regulatory framework based on EU Regulation 1107/2009 and 546/2011 together with the data requirements in EU Regulation 283/2013 and 284/2013, Part B, respectively (all amended in 2022). Furthermore, several guidance documents specify the data requirements for the human health assessment. As in other regulatory contexts, the assessment of hazardous properties of a microbial plant protection product (PPP) can be based on in vivo data. In order to decrease the use of test animals, support high-throughput data generation with larger repetition, and to facilitate faster testing methods, New Approach Methodologies (NAMs) for this field need to be developed. Here we focus on the assessment of the potential pathogenicity/infectivity and the presence of transferable antimicrobial resistance (AMR) genes of a microorganism when utilised as the active substance (AS) in a PPP. For the purpose of risk assessment of microbial PPPs, NAMs developed in view of the Next Generation Risk Assessment (NGRA) for chemicals can be applied. However, major drawbacks in the ability to use existing NAMs in the risk assessment of microbial pesticides are the reliability of Adverse Outcome Pathway (AOP) generated data for humans and the practicability of in vitro methods to test living microorganisms. It must be emphasised that tests for risk assessment are only useful if the test interpretation is clearly defined. Without prior definition of the possible effects and their interpretation, including the possible outcome for risk assessment, the test has limited value, as the results may raise more questions than answers. Overall, the regulatory assessment of the human health effects of microbial pesticides used in PPP needs reliable and robust data. These data should ideally be presented by an applicant based on animal-free study setups together with thorough literature searches.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.