Chunlin Chen

The development of topical drug formulations typically requires reliable assessment of both drug release and permeation characteristics. In vitro release testing (IVRT) is routinely used for quality control and early screening, while in vitro permeation testing (IVPT) has been commonly used as the standardised approach for evaluating skin permeation performance. However, the extent to which IVRT corresponds to IVPT outcomes remains insufficiently quantified when both experiments are conducted under the same conditions. Here, using fifteen ibuprofen formulations previously characterised by IVPT on a Strat-M membrane, we performed IVRT with a nylon membrane and examined the IVRT-IVPT relationship from correlation, predictability and structural-consistency perspectives. IVRT release rate exhibited a strong positive association with IVPT steady-state flux (Pearson r = 0.95, R-2 = 0.92, p < 0.001), and largely preserved formulation ranking (five of the top six IVRT formulations were also top-ranked in IVPT). Gaussian process regression further revealed a highly aligned similarity structure between IVRT- and IVPT-based models (kernel alignment = 0.97). This suggests that the two experimental models capture closely related representations of the formulation space, even though their response variables differ. Combined with repeatability and discriminatory capability of IVRT, these results support IVRT as an initial screening tool prior to conducting more resource-intensive permeation evaluations.

Formulating effective skin products requires navigating complex chemical mixtures,skin biophysical and biochemical properties and manufacturing processes, all under budgetary and time constraints. Controlling dermal permeation, a key driver of efficacy, often presents the primary development bottleneck. Conventional development methods are slow, hampered by low-throughput, variable test assays (e.g., in vitro release and permeation testing) and limited access to biologically relevant in vitro skin models. This review argues for a shift towards autonomous, assay-aware formulation design, outlining a closed-loop framework that unifies intelligent candidate generation, automated experiment selection and robust analysis across a skin-specific multi-tiered assay strategy. The foundations of barrier transport and formulation behaviour are first synthesised. Key enabling technologies are then systematically surveyed, including automation technologies (e.g., microfluidic and modular platforms), automated analytics (e.g., chromatographic pipelines, auto-sampling for diffusion cells) and artificial intelligence (e.g., hybrid mechanistic/data-driven surrogates and constraint-aware active learning). Building upon this foundation, a practical framework is discussed that foregrounds cross-tier calibration between rapid screens and pivotal assay endpoints. Its workflow centres on model generalisation, uncertainty quantification and robust system orchestration. The goal is to provide a credible path towards faster, more reproducible and acceptance criteria-aligned decisions for skin product formulation efficacy.