“In Litero” Screening: Retrospective Evaluation of Clinical Evidence to Establish a Reference List of Human Chemical Respiratory Sensitizers

Abstract

Despite decades of investigation, test methods to identify respiratory sensitizers remain an unmet regulatory need. In order to support the evaluation of New Approach Methodologies in development, we sought to establish a reference set of low molecular weight respiratory sensitizers based on case reports of occupational asthma. In this context, we have developed an “in litero” approach to identify cases of low molecular weight chemical exposures leading to respiratory sensitization in clinical literature. We utilized the EPA-developed Abstract Sifter literature review tool to maximize the retrieval of publications relevant to respiratory effects in humans for each chemical in a list of chemicals suspected of inducing respiratory sensitization. The literature retrieved for each of these candidate chemicals was sifted to identify relevant case reports and studies, and then evaluated by applying defined selection criteria. Clinical diagnostic criteria were defined around exposure history, respiratory effects, and specific immune response to conclusively demonstrate occupational asthma as a result of sensitization, rather than irritation. This approach successfully identified 28 chemicals that can be considered as human respiratory sensitizers and used to evaluate the performance of NAMs as part of a weight of evidence approach to identify novel respiratory sensitizers. Further, these results have immediate implications for the development and refinement of predictive tools to distinguish between skin and respiratory sensitizers. A comparison of the protein binding mechanisms of our identified “in litero” clinical respiratory sensitizers shows that acylation is a prevalent protein binding mechanism, in contrast to Michael addition and Schiff base formation common to skin sensitizers. Overall, this approach provides an exemplary method to evaluate and apply human data as part of the weight of evidence when establishing reference chemical lists.

Downscaling of a Three-Dimensional Alveolar In Vitro Model for High-Throughput Screening of Inhalable Respiratory Sensitizers in the Food Industry

“…Cell surface markers CD54 and CD86 are established markers for the prediction of skin sensitizers in the human cell line activation test (h-CLAT) (OECD Guidelines for the Testing of Chemicals, 2018). Respiratory sensitizers, such as chloramine-T (Ponder et al, 2022), maleic anhydride, and ethylenediamine (Ponder et al, 2022;Sadekar et al, 2021) showed increase of at least one of the two markers in the h-CLAT assay (Ashikaga et al, 2010). TSLP is an epithelial-derived cytokine, whose receptors comprise TSLPr and IL-7Rα, which are expressed on monocytes, myeloid-derived DCs and B cells (O'Shea et al, 2019).…”

Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation

“…Literature mining can extract information from unstructured text like abstracts and articles or structured databases to define biological activities of chemicals for toxicological assessment. − Two main paradigms for identifying reference chemicals using literature mining exist; the first follows a traditional exhaustive literature review workflow ,, and the second mines databases with structured endpoint assays or chemical target data. , This first approach can use assistive search tools − to reduce the human burden, often resulting in tens to hundreds of highly vetted reference chemicals across a few targets through expert consensus. The second approach bins the most active chemicals by statistical testing and automates much of the workflow, resulting in thousands of chemicals across tens to hundreds of mined targets with less human supervision.…”