Pyrogenic synthetic amorphous silica (NM-203): Genotoxicity in rats following sub-chronic oral exposure

In vivo safety evaluation method for nanomaterials for cancer therapy

Nanomaterials are extensively used in the diagnosis and treatment of cancer and other diseases because of their distinctive physicochemical properties, including the small size and ease of modification. The approval of numerous nanomaterials for clinical treatment has led to a significant increase in human exposure to these materials. When nanomaterials enter organisms, they interact with DNA, cells, tissues, and organs, potentially causing various adverse effects, such as genotoxicity, reproductive toxicity, immunotoxicity, and damage to tissues and organs. Therefore, it is crucial to elucidate the side effects and toxicity mechanisms of nanomaterials thoroughly before their clinical applications. Although methods for in vitro safety evaluation of nanomaterials are well established, systematic methods for in vivo safety evaluation are still lacking. This review focuses on the in vivo safety evaluation of nanomaterials and explores their potential effects. In addition, the experimental methods for assessing such effects in various disciplines, including toxicology, pharmacology, physiopathology, immunology, and bioinformatics are also discussed.

Grouping of orally ingested silica nanomaterials via use of an integrated approach to testing and assessment to streamline risk assessment

BACKGROUND

Nanomaterials can exist in different nanoforms (NFs). Their grouping may be supported by the formulation of hypotheses which can be interrogated via integrated approaches to testing and assessment (IATA). IATAs are decision trees that guide the user through tiered testing strategies (TTS) to collect the required evidence needed to accept or reject a grouping hypothesis. In the present paper, we investigated the applicability of IATAs for ingested NFs using a case study that includes different silicon dioxide, SiO₂ NFs. Two oral grouping hypotheses addressing local and systemic toxicity were identified relevant for the grouping of these NFs and verified through the application of oral IATAs. Following different Tier 1 and/or Tier 2 in vitro methods of the TTS (i.e., in vitro dissolution, barrier integrity and inflammation assays), we generated the NF datasets. Furthermore, similarity algorithms (e.g., Bayesian method and Cluster analysis) were utilized to identify similarities among the NFs and establish a provisional group(s). The grouping based on Tier 1 and/or Tier 2 testing was analyzed in relation to available Tier 3 in vivo data in order to verify if the read-across was possible and therefore support a grouping decision.

RESULTS

The measurement of the dissolution rate of the silica NFs in the oro-gastrointestinal tract and in the lysosome identified them as gradually dissolving and biopersistent NFs. For the local toxicity to intestinal epithelium (e.g. cytotoxicity, membrane integrity and inflammation), the biological results of the gastrointestinal tract models indicate that all of the silica NFs were similar with respect to the lack of local toxicity and, therefore, belong to the same group; in vivo data (although limited) confirmed the lack of local toxicity of NFs. For systemic toxicity, Tier 1 data did not identify similarity across the NFs, with results across different decision nodes being inconsistent in providing homogeneous group(s). Moreover, the available Tier 3 in vivo data were also insufficient to support decisions based upon the obtained in vitro results and relating to the toxicity of the tested NFs.

CONCLUSIONS

The information generated by the tested oral IATAs can be effectively used for similarity assessment to support a grouping decision upon the application of a hypothesis related to toxicity in the gastrointestinal tract. The IATAs facilitated a structured data analysis and, by means of the expert's interpretation, supported read-across with the available in vivo data. The IATAs also supported the users in decision making, for example, reducing the testing when the grouping was well supported by the evidence and/or moving forward to advanced testing (e.g., the use of more suitable cellular models or chronic exposure) to improve the confidence level of the data and obtain more focused information.