Toxic effects of nanomaterials for health applications: How automation can support a systematic review of the literature?

J Appl Toxicol. 2022 Jan;42(1):41-51. doi: 10.1002/jat.4204. Epub 2021 May 29.

Abstract

Systematic reviews of the scientific literature can be an important source of information supporting the daily work of the regulators in their decision making, particularly in areas of innovative technologies where the regulatory experience is still limited. Significant research activities in the field of nanotechnology resulted in a huge number of publications in the last decades. However, even if the published data can provide relevant information, scientific articles are often of diverse quality, and it is nearly impossible to manually process and evaluate such amount of data in a systematic manner. In this feasibility study, we investigated to what extent open-access automation tools can support a systematic review of toxic effects of nanomaterials for health applications reported in the scientific literature. In this study, we used a battery of available tools to perform the initial steps of a systematic review such as targeted searches, data curation and abstract screening. This work was complemented with an in-house developed tool that allowed us to extract specific sections of the articles such as the materials and methods part or the results section where we could perform subsequent text analysis. We ranked the articles according to quality criteria based on the reported nanomaterial characterisation and extracted most frequently described toxic effects induced by different types of nanomaterials. Even if further demonstration of the reliability and applicability of automation tools is necessary, this study demonstrated the potential to leverage information from the scientific literature by using automation systems in a tiered strategy.

Keywords: automation tools; knowledge management; nanomedicines; quality evaluation; systematic review automation; toxicity of nanomaterials.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Automation*
  • Humans
  • Mass Screening / instrumentation*
  • Nanostructures / toxicity*
  • Public Health / statistics & numerical data*
  • Reproducibility of Results