ArticleComputational and structural biotechnology journal2025
MACRAMÉ - Advanced characterisation methodologies to assess and predict the health and environmental risks of advanced materials.
Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- ARACRA: Automated RNA-seq Analysis for Chemical Risk Assessment.Computational and structural biotechnology journal · 2026Article
- Towards test guidelines and standards for advanced materials: scientific insights and recommendations from the MACRAMÉ project.Frontiers in toxicology · 2026Article
- Going digital to boost safe and sustainable materials innovation markets. The digital safe-and-sustainability-by-design innovation approach of the PINK project.Computational and structural biotechnology journal · 2025Article
- Setting off on the right path: make your research regulatory relevant.Frontiers in research metrics and analytics · 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
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ensuring the safety and sustainability of advanced materials (AdMas) is critical for fostering innovation while protecting human health and the environment. As industries integrate AdMas into commercial products to innovate in the next stage of the value chains, there is an urgent need for robust methodologies to detect, characterize, and assess their potential risks throughout their life cycle. The MACRAMÉ Project addresses this challenge by advancing standardized testing and regulatory frameworks, supporting the EU's vision for a toxic-free environment. Through cutting-edge research and international collaboration, MACRAMÉ lays the groundwork for reliable hazard assessment, regulatory compliance, and the responsible development of next-generation materials. The MACRAMÉ Project aims to enhance the detection, characterization, and quantification of Advanced Materials (AdMas) throughout their life cycle, assessing potential human and environmental health impacts during exposure. By developing, demonstrating, and standardizing advanced methodologies, MACRAMÉ ensures their broad applicability across market-relevant AdMas-containing products. Fully aligned with EU strategies such as the Chemical Strategy for Sustainability and the European Green Deal, the project extends nanosafety approaches to the broader AdMas category, focusing on inhalable carbon-based materials - graphene-related materials, carbon nanofibers, and poly lactic-co-glycolic acid nanoparticles. Building on over 15 years of research, MACRAMÉ integrates knowledge from major European and international initiatives to establish harmonized test guidelines, guidance documents, and standards. Through five industrial Use-Cases, the project applies innovative sample preparation, detection, and toxicity assessment techniques to develop a tiered approach for AdMa safety testing. Centralized in the MACRAMÉ Information Hub, all data will support regulatory frameworks and future research. The project's outcomes - harmonization and pre-standardization proposals - will contribute to a unified European assessment framework, reinforcing the continent's leadership in safe and sustainable materials innovation.
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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 OpenQuestion graph.