COSMOS next generation – A public knowledge base leveraging chemical and biological data to support the regulatory assessment of chemicals

Chihae Yang ,J.V Ribeiro,J Park,J Marusczyk,Y Lan,Kirk Arvidson ,Ann M Richard ,Bruno Bienfait ,Daniel Neagu ,Vessela Vitcheva ,Kristi Muldoon-Jacobs ,Steven J Enoch ,Christof H Schwab ,Mark T.d Cronin ,A.n Richarz ,James F Rathman ,Mark Nelms ,Judith C Madden ,Katarzyna R Przybylak ,Oliver Sacher ,Tomasz Magdziarz ,Patra Volarath ,Bryan Hobocienski ,Bart Heldreth ,Aleksandra Mostrąg ,Andrew Worth

doi:10.1016/j.comtox.2021.100175

Abstract

The COSMOS Database (DB) was originally established to provide reliable data for cosmetics-related chemicals within the COSMOS Project funded as part of the SEURAT-1 Research Initiative. The database has subsequently been maintained and developed further into COSMOS Next Generation (NG), a combination of database and in silico tools, essential components of a knowledge base. COSMOS DB provided a cosmetics inventory as well as other regulatory inventories, accompanied by assessment results and in vitro and in vivo toxicity data. In addition to data content curation, much effort was dedicated to data governance – data authorisation, characterisation of quality, documentation of meta information, and control of data use. Through this effort, COSMOS DB was able to merge and fuse data of various types from different sources. Building on the previous effort, the COSMOS Minimum Inclusion (MINIS) criteria for a toxicity database were further expanded to quantify the reliability of studies. COSMOS NG features multiple fingerprints for analysing structure similarity, and new tools to calculate molecular properties and screen chemicals with endpoint-related public profilers, such as DNA and protein binders, liver alerts and genotoxic alerts. The publicly available COSMOS NG enables users to compile information and execute analyses such as category formation and read-across. This paper provides a step-by-step guided workflow for a simple read-across case, starting from a target structure and culminating in an estimation of a NOAEL confidence interval. Given its strong technical foundation, inclusion of quality-reviewed data, and provision of tools designed to facilitate communication between users, COSMOS NG is a first step towards building a toxicological knowledge hub leveraging many public data systems for chemical safety evaluation. We continue to monitor the feedback from the user community at support@mn-am.com.

Highlights

COSMOS DB as a platform for leveraging public resourcesThe European Union’s Cosmetics Regulation (EC) N◦ 1223/2009 entered into force in January 2010, maintaining the provisions of the Seventh Amendment of the European Union’s Cosmetics Directive 76/ 768/EEC, foreseeing the ultimate replacement of animal testing of cosmetic products for all endpoints, including repeated dose/repro ductive toxicity and toxicokinetics; the full EU ban on animal testing for cosmetics entered into force in March 2013 [1]
Low (Score = 1): Data are highly aggregated as summary data, but conclusion may be usable according to experts
Based on the review of existing approaches on good practice to assess quality entries, the reli ability of the toxicity data is supported by all available data from mul tiple sources based on COSMOS Minimum Inclusion (MINIS) criteria

Summary

Introduction

COSMOS DB as a platform for leveraging public resourcesThe European Union’s Cosmetics Regulation (EC) N◦ 1223/2009 entered into force in January 2010, maintaining the provisions of the Seventh Amendment of the European Union’s Cosmetics Directive 76/ 768/EEC, foreseeing the ultimate replacement of animal testing of cosmetic products for all endpoints, including repeated dose/repro ductive toxicity and toxicokinetics; the full EU ban on animal testing for cosmetics entered into force in March 2013 [1]. The COSMOS DB [6] was designed to service the work packages pertaining to non-testing and/or computational methods, including Threshold of Toxicological Concern (TTC), read-across, quantitative structure–activity relationship (QSAR) models, biokinetics, and innovative chemistry methods. To support these activities, the compilation and curation of vastly different types of data content enriched with cosmetics-related chemicals to be made publicly available in a database format were necessary. The public databases released from the two agencies were a tremendous jump start for the project

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