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.
ABSTRACT
ABSTRACT Genetic toxicity data from various sources were integrated into a rigorously designed database using the ToxML schema. The public database sources include the U.S. Food and Drug Administration (FDA) submission data from approved new drug applications, food contact notifications, generally recognized as safe food ingredients, and chemicals from the NTP and CCRIS databases. The data from public sources were then combined with data from private industry according to ToxML criteria. The resulting "integrated" database, enriched in pharmaceuticals, was used for data mining analysis. Structural features describing the database were used to differentiate the chemical spaces of drugs/candidates, food ingredients, and industrial chemicals. In general, structures for drugs/candidates and food ingredients are associated with lower frequencies of mutagenicity and clastogenicity, whereas industrial chemicals as a group contain a much higher proportion of positives. Structural features were selected to analyze endpoint outcomes of the genetic toxicity studies. Although most of the well-known genotoxic carcinogenic alerts were identified, some discrepancies from the classic Ashby-Tennant alerts were observed. Using these influential features as the independent variables, the results of four types of genotoxicity studies were correlated. High Pearson correlations were found between the results of Salmonella mutagenicity and mouse lymphoma assay testing as well as those from in vitro chromosome aberration studies. This paper demonstrates the usefulness of representing a chemical by its structural features and the use of these features to profile a battery of tests rather than relying on a single toxicity test of a given chemical. This paper presents data mining/profiling methods applied in a weight-of-evidence approach to assess potential for genetic toxicity, and to guide the development of intelligent testing strategies.
ABSTRACT
Cell damage has been observed in suspension cell cultures with air sparging, especially in the absence of any protective additives. This damage is associated with cells adhering to bubbles, and it has been shown that if this adhesion is prevented, cell damage is prevented. This article presents a thermodynamic approach for predicting cell adhesion at the air-medium interface. With this relationship it can be shown that cell-gas adhesion can be prevented by lowering the surface tension of the liquid growth medium through the addition of surface-active protective additives. The thermodynamic relationship describes the change in free energy as a function of the interfacial tensions between the (i) gas and liquid phases, (ii) gas and cell phases, and (iii) liquid and cell phases. Experimental data, along with theoretical and empirical equations, are used to quantify the changes in free energy that predict the process of cell-gas adhesion. The thermodynamic model is nonspecific in nature and, consequently, results are equally valid for all types of cells. (c) 1995 John Wiley & Sons, Inc.
ABSTRACT
A significant degree of cell damage is observed during suspension cell culture with air sparging. Protective agents can be added to the culture medium to protect the cells from damage. It has been observed that cells tend to adhere to air-medium interfaces and cell damage is mainly due to this cell-bubble interaction; protective additives have been found to prevent this cell adhesion to the bubble surfaces. In this article, it is demonstrated that the interfacial tension between the air and medium is related to the effectiveness of the protective additives to prevent adhesion of cells to this interface. Five different types of additives (Pluronic F-68, Methocels, dextran, Polyvinyl alcohol, and polyethylene glycols) were studied in an effort to determine their protective characteristics. Liquid-vapor interfacial tensions of the culture medium, with and without the additives, were measured by two different techniques (maximum bubble pressure method and Wilhelmy plate method). In addition, visualization techniques showed that in the presence of certain protective additives cells do not adhere to the bubble surface. Results obtained from these experiments indicate that the additives which rapidly lower the liquid-vapor interfacial tension of the culture medium also prevent adhesion of cells to the bubble surface. Experiments have also been conducted to determine the number of cells killed due to bubble rupture, and it was observed that this number is related to the amount of cells adhering to the bubble surface.
