Drug development is an inefficient and expensive process, in which a drug can fail late in phase 3 clinical trials or due to the unanticipated manifestation of severe side-effects after release onto the market. For example, Dupilumab, an Interleukin-4 receptor antagonist for , atopic dermatitis (AD), often causes adverse reactions such as keratitis, eye pruritus and dry eyes and nasopharyngitis. AD is one of the most common chronic inflammatory skin diseases, affecting 15-20% of children and 1-3% of adults worldwide. AD is a complex and multifactorial disease, and AD pathogenesis is driven by genetic factors, as well as by environmental cues. The filaggrin (FLG) gene is believed to play a crucial role in the pathophysiology of AD. Moreover, there is a link between AD lesions and Staphylococcus Aureus (S. Aureus) colonization, since it is observed that ~90% of AD patients are colonized with S. aureus in lesional skin, and increased S. Aureus loads correlate with disease flares in the affected skin. Animal models have been developed to delineate AD pathogenesis and for preclinical drug testing, however, these models fall short of faithfully recapitulating the pleiotropic disease phenotypes since mice do not spontaneously develop AD. Likewise, in vitro models of AD do not recapitulate the crosstalk between different organs involved in AD. In this project, we will establish a functional network of three tissue systems comprised of skin, cornea and nasal tissues, as well as circulating T cells and microbiota (Sk-Co-Na-T-MB) to model AD. This platform will enable a multi- factorial approach to delineating AD pathogenesis, as well as provide unprecedented predictive power to detect drug toxicity/efficacy in a genetically-defined cohort of AD patients iPSCs. We will validate the platform by examining the efficacy/toxicity of several FDA-approved and emerging AD drugs, including Dupilumab (an Interleukin-4 receptor antagonist), Apremilast (a PDE4 inhibitor) and Tofacitinib (a pan-JAK inhibitor). Finally, we will also investigate the compounding effects of genetic and environmental risk factors (microbiota and FLG mutations), and our AD patient cohort will reflect the gender and ethnic diversity of patient populations receiving AD drugs, allowing us to perform clinically- relevant and patient-specific Clinical Trials in a Dish for Atopic Dermatitis.
Atopic Dermatitis (AD) is one of the most common chronic inflammatory skin diseases, affecting 15-20% of children and 1-3% of adults worldwide, in which disease pathogenesis is driven by genetic factors as well as by environmental cues. Animal models have been developed to delineate AD pathogenesis and for preclinical drug testing, however, these models fall short of faithfully recapitulating the disease, since mice do not spontaneously develop AD, and simplified in vitro models of AD do not recapitulate the crosstalk between different organs involved in AD. In this project, we will establish a functional network of three tissue systems comprised of skin, cornea and nasal tissues, as well as circulating T cells and microbiota (Sk-Co-Na-T- MB) to model AD, which will provide unprecedented predictive power to detect drug toxicity/efficacy in a genetically-defined cohort of AD patient iPSCs, and allow us to perform clinically-relevant and patient-specific Clinical Trials in a Dish.
