This work focuses on the need for modeling and predicting adverse outcomes in immunotoxicology to improve nonclinical assessments of the safety of immunomodulatory therapies. The integrated approach includes, first, the adverse outcome pathway concept established in the toxicology field, and, second, the systems medicine disease map approach for describing molecular mechanisms involved in a particular pathology. The proposed systems immunotoxicology workflow is illustrated with chimeric antigen receptor (CAR) T cell treatment as a use case. To this end, the linear adverse outcome pathway (AOP) is expanded into a molecular interaction model in standard systems biology formats. Then it is shown how knowledge related to immunotoxic events can be integrated, encoded, managed, and explored to benefit the research community. The map is accessible online at https://imsavar.elixir-luxembourg.org via the MINERVA Platform for browsing, commenting, and data visualization. Our work transforms a graphical illustration of an AOP into a digitally structured and standardized form, featuring precise and controlled vocabulary and supporting reproducible computational analyses. Because of annotations to source literature and databases, the map can be further expanded to match the evolving knowledge and research questions.
Keywords: AOP; CAR T cells; CRS; adverse outcome pathway; chimeric antigen receptor; cytokine release syndrome; disease mechanisms; immunomodulatory therapies; systems biology.
In immunotoxicology, an adverse outcome pathway shows a sequence of molecular and cellular events that result in a toxic outcome upon treatment with a specific drug.In systems biomedicine, a disease map is a description of disease mechanisms on the levels of molecular interactions and intercellular communication for integrating prior knowledge, making sense of newly-generated data, modeling and predictions.We are applying the disease map approach to the area of immunotoxicology and offer an interactive web-based platform for expanding immune-related adverse outcome pathways to detailed representations of the underlying biology.The objective is to model adverse outcomes as a nonclinical assessment strategy by integrating our understanding of the disease complexity and knowledge on the mechanisms of the adverse outcomes of the treatment.We focus on the adverse outcome pathway of CAR T cell treatment and from a simplified linear pathway build a detailed representation of the underlying biology.