Procter & Gamble has developed numerous products that interact with epithelial tissues, driving the need for innovative, non-animal testing platforms. This seminar presents two computational approaches that address this need. The first involves the creation of high-performance, multiscale, multicellular virtual skin models capable of simulating complex biological behavior and product response. The second focuses on a machine learning framework for identifying biomarkers to prioritize candidate materials in early-stage development. This approach directly informed the design of a successful human clinical trial. Time permitting, the use of quantitative imaging as a biomarker modality will also be briefly discussed.