Topical drug formulation for enhanced permeation: A comparison of Bayesian optimisation and response surface...

Topical skin products aim to address aesthetic, protective, and/or therapeutic needs through interaction with the human epidermal system. Traditionally, formulation development relies on empirical knowledge and trial-and-error experiments. In this paper, we introduced the Bayesian optimisation method and compared it with the traditional response surface methodology (RSM) for topical drug formulation. The objective was to optimise the formulation composition of ibuprofen gel-like to achieve a maximum flux through in vitro permeation tests (IVPTs). As a model system, poloxamer 407, ethanol, and propylene glycol (PG) were selected as the key excipients, whose concentrations were optimised. Strat-M membrane, serving as a surrogate for human skin, and Franz cell diffusion were employed in IVPTs. Two sets of experiments were conducted under identical conditions for 30 h. Under the RSM approach, the optimised ibuprofen gel-like formulation was identified with a poloxamer 407: ethanol: PG ratio of 20:20:10, achieving a measured permeation flux of 11.28 ± 0.35 μg cm^-2h^-1. In comparison, Bayesian optimisation, after four iterations, yielded an optimised formulation with a ratio of 20.95:19.44:12.14, resulting in a permeation flux of 14.15 ± 0.77 μg cm^-2h^-1. These findings highlight the potential of Bayesian optimisation as an effective tool for improving topical drug formulations.