02783nas a2200253   4500000000100000000000100001008004100002260001500043653002600058653001900084653002800103653002100131653001700152100002100169700002100190700001700211700002200228245009700250856004700347300000600394490000700400520210800407022001402515       2025                            d  c2025-12-0510aClosed-form solutions10adrug diffusion10aInterstitial fluid flow10aModel validation10askin-on-chip1 aDeepa Chaturvedi1 aJoydeb Mukherjee1 aRatnesh Jain1 aPrajakta Dandekar00aIn silico approach for validating organ-on-chips: exemplifying through a skin-on-chip device  uhttps://doi.org/10.1007/s10404-025-02863-y  a60 v303 aThe limitations of traditional, animal-model-based preclinical drug testing methodologies have contributed to an extremely high failure rate of new drug candidates in various phases of clinical trials. Organ-on-chip (OoC) technology has emerged as a promising alternative, providing a physiologically relevant microenvironment for drug testing. However, challenges such as high costs, inadequate physiological replication, and particularly the lack of standardized validation approaches have undermined the widespread adoption of OoCs. Additionally, the need for in silico-assisted functional verification to accelerate drug development, reduce investigational expenses, and enhance ethical feasibility has been increasingly experienced by researchers. In this study, we developed and validated a microfluidic skin-on-chip (SoC) platform that supports dynamic skin co-culture for 11 days. The model was characterized by using live-dead cell staining, fluorescent cell tracking, hematoxylin and eosin (H&E) staining, and immune-histochemistry analysis. In vitro drug diffusion studies with caffeine and salicylic acid were performed and quantified using high-performance liquid chromatography. To enhance predictive accuracy, a mathematical model based on the convection–diffusion equation was developed to simulate passive drug permeation across skin layers. Analytical modeling, solved using a closed-form solution, captured diffusion kinetics and flow patterns, while numerical modeling validated the results through finite element analysis. The model exhibited strong agreement with experimental data (relative error: ±12%) for both drugs, at an initial concentration of 1 mg mL−1. Our microfluidic SoC device, functionally verified using experimental and in silico-assisted approaches, offers a reliable pre-clinical tool for testing chemicals, cosmetics, pharmaceuticals, and allergens. The investigations support a step forward in the use of new approach methodologies (NAMs) for improving predictive accuracy and standardizing drug permeability assays during the drug development process.  a1613-4990