563 Mechanistic Modeling Facilitates Identification of Key Pathways Involved in Dermal Aging and Potential New Targets for Anti-Aging Intervention

Despite progress clarifying mechanisms of skin aging, identification of targets to improve skin appearance remains a challenge. Combining molecular biology, gene expression, clinical data with computational mechanistic modeling provides a novel approach to support target identification and evaluation. To increase the scientific understanding of pathways involved in skin aging and evaluate anti-aging technologies, Rosa and P&G developed a PhysioPD Research Platform, a quantitative physiological model of the aged skin and the visible effects of anti-aging products. The Platform represents key processes involved in aging of normal human skin and begins to illuminate the mechanisms of anti-aging appearance benefits. Published and proprietary data was used in the Platform development and qualification: responses to standard of care and novel technologies were investigated in Virtual Consumers (VCs) representing various phenotypes of aged skin. Simulated outcomes of SOP therapies, e.g., topical retinoic acid, estrogen (E2) agree with the published data. New protocols were simulated on all VCs, and the predicted effects on skin appearance improvements were analyzed, leading to insights supporting prioritization of technologies. Simulations revealed that, given specific application onset and duration, topical E2 may lead to improvements in the appearance of photoaged skin. Positive effects of E2 treatment include stimulation of hyaluronic acid (HA) related pathways and that could result in increased skin viscoelasticity according to published data. A sensitivity analysis identified the most important drivers of improvements in aged skin appearance pointed to ECM components, including HA, as promising targets. On-going research using the Platform is expected to continue to enhance P&G's ability to make informed development decisions.