We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Several human skin models employing primary cells and immortalized cell lines used as monocultures or combined to produce reconstituted 3D skin constructs have been developed. Furthermore, these models have been included in European genotoxicity and sensitization/irritation assay validation projects. In order to help interpret data, Cosmetics Europe (formerly COLIPA) facilitated research projects that measured a variety of defined phase I and II enzyme activities and created a complete proteomic profile of xenobiotic metabolizing enzymes (XMEs) in native human skin and compared them with data obtained from a number of in vitro models of human skin. Here, we have summarized our findings on the current knowledge of the metabolic capacity of native human skin and in vitro models and made an overall assessment of the metabolic capacity from gene expression, proteomic expression, and substrate metabolism data. The known low expression and function of phase I enzymes in native whole skin were reflected in the in vitro models. Some XMEs in whole skin were not detected in in vitro models and vice versa, and some major hepatic XMEs such as cytochrome P450-monooxygenases were absent or measured only at very low levels in the skin. Conversely, despite varying mRNA and protein levels of phase II enzymes, functional activity of glutathione S-transferases, N-acetyltransferase 1, and UDP-glucuronosyltransferases were all readily measurable in whole skin and in vitro skin models at activity levels similar to those measured in the liver. These projects have enabled a better understanding of the contribution of XMEs to toxicity endpoints.

The need for alternative approaches to replace the in vivo rabbit Draize eye test for evaluation of eye irritation of cosmetic ingredients has been recognised by the cosmetics industry for many years. Extensive research has lead to the development of several assays, some of which have undergone formal validation. Even though, to date, no single in vitro assay has been validated as a full replacement for the rabbit Draize eye test, organotypic assays are accepted for specific and limited regulatory purposes. Although not formally validated, several other in vitro models have been used for over a decade by the cosmetics industry as valuable tools in a weight of evidence approach for the safety assessment of ingredients and finished products. In light of the deadlines established in the EU Cosmetics Directive for cessation of animal testing for cosmetic ingredients, a COLIPA scientific meeting was held in Brussels on 30th January, 2008 to review the use of alternative approaches and to set up a decision-tree approach for their integration into tiered testing strategies for hazard and safety assessment of cosmetic ingredients and their use in products. Furthermore, recommendations are given on how remaining data gaps and research needs can be addressed.

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