• Establishment of single-donor human whole blood and blood fraction models of internal blood vessels for early phase drug safety assessments • Application of the models in both 2D plate-based and 3D vascular structure formats for tailoring of data output to research requirements Following previous failures to predict drug-induced adverse immune reactions in clinical trials, for example in cases with preclinical species differences or poorly indicative in vitro assays, there has been an emphasis on developing improved preclinical hazard identification tools. Concurrently, there is a regulatory-backed responsibility to reduce reliance on preclinical animal models, highlighted by the FDA Modernization Act 2.0 and their 2025 announcement to phase out animal testing for specific compounds. Traditional in vitro cytokine release assays utilise plastic-based formats of antibody presentation to blood cell fractions and, while biologically simple to run, they do not accurately recapitulate in vivo blood vessel physiology. Including endothelial cells improves physiological relevance by representing the internal vascular wall, enabling cell-cell interactions, compound presentation and cellular responses from endothelial cells alongside blood cells. Here, endothelial cells outgrown from healthy donors are co-cultured with their blood cells to model the immune response to compounds. Building on existing endothelial assays co-cultured with blood cell fractions, we establish the model using whole blood as an alternative format. We then transfer both formats from 2D 96-well plates into a 3D microfluidics system, further mimicking the dynamics and structural microenvironment of a blood vessel. We use these human vasculature models to recapitulate the expected cytokine response to existing compounds and highlight the additional preclinical safety endpoints that can be investigated by using a 3D vessel, such as vascular leak. This proof-of-concept study demonstrates foundations for a scalable, physiologically relevant method for preclinical testing whilst reducing reliance on animal models.
Lund et al. (Sun,) studied this question.