P125 Improving bench-to-clinic transition with novel psoriasis-on-a-chip fluidics

Abstract Topical drug development bears a 50× higher cost of failure compared with oral therapies. Adverse skin reactions account for 2% of drug attrition. Current pre-clinical skin models do not fully replicate in vivo skin physiology which impacts bench-to-clinic translation. In psoriasis, no new topical therapeutics has been introduced into the NHS for over 10 years. Thus, there is an urgent need to revolutionise and improve pre-clinical testing to ensure new, effective and safe therapies can reach patients. We present new fluidic skin-on-chip technology that maintains healthy human skin tissue in culture with full barrier function, resident immune cells and viability. By reconsidering environmental control and cell culture media chemistry, full skin barrier function was maintained for 5 days. This enabled novel extended 5-day repeat-dose permeation studies with simultaneous functional and toxicology analysis. The skin-on-chip technology was found to improve the accuracy of skin irritation assessment, due to the ability to include analysis of skin barrier disruption as well as impact on viability, superseding 3D skin models which can only assess skin irritation by loss of viability. This new technology was assessed with topical application of Tapinarof (formulated as VTAMA, an FDA approved therapeutic for psoriasis). We demonstrated a reduction of CD4+ and CD8+ immune cells by FACS analysis in cultured ex vivo skin. VTAMA-treated psoriasis biopsies displayed remarkably improved histology with reduced acanthosis of rete ridges. Recovery of skin barrier function, measured by trans-epidermal water loss, was confirmed after 3 days of culture. Further analysis of the skin-on-chip technology using cultured ex vivo psoriasis biopsies showed the system was able to retain histological features of psoriasis in untreated samples. Overall, our data indicates the skin-on-chip technology provides superior preclinical analysis which better replicates clinical responses compared with current methods. This has the potential to drastically reduce failure rates at clinical testing phases and ensure effective and safe therapies can reach patients faster.