# From simulation to application: enhancing preclinical evaluation of dissolvable microarray patches through PBPK modelling

## TL;DR

This paper introduces a PBPK model optimized for dissolvable microarray patches to improve drug delivery predictions and preclinical evaluation.

## Contribution

The study presents a novel PBPK model adaptation for dissolvable microarray patches using drug-specific release profiles and skin parameters.

## Key findings

- The optimized PBPK model accurately predicted drug kinetics for dissolvable microarray patches in vitro and in vivo.
- The model incorporated microneedle geometry and drug release profiles for loratadine, chlorpheniramine maleate, and itraconazole.
- Validation showed robust performance across different drug molecules and experimental conditions.

## Abstract

Dissolvable microarray patches (MAP) represent a promising drug delivery platform; however, the absence of standardised protocols for their preclinical evaluation poses a significant barrier to regulatory approval and clinical translation. Physiologically Based Pharmacokinetic (PBPK) modelling is a powerful tool for predicting drug kinetics following MAP application, addressing key challenges associated with in vitro and in vivo studies such as experimental variability, complex study design, and data extrapolating across different populations. However, adapting PBPK models for dissolvable MAP is inherently complex due to the interplay between microneedle geometry, drug release kinetics, and skin physiology. In this study, an existing dermal PBPK model in MoBi® was optimised for dissolvable MAP by incorporating microneedle geometry and in vitro release profiles of MAP formulations containing the antihistamines loratadine (LOR) and chlorpheniramine maleate (CPM), as well as the antifungal drug itraconazole (ITZ). Model refinement involved systematically optimising input parameters related to skin thickness and drug-skin diffusion, partitioning and binding, to enhance predictive accuracy. Validation was performed using in vitro permeation testing with porcine skin for CPM and LOR MAP, alongside in vivo preclinical studies in pigs for ITZ MAP. The optimised model demonstrated robust predictive performance across the diverse drug molecules and experimental conditions investigated, highlighting its value as a powerful tool to accelerate preclinical MAP development.

The online version contains supplementary material available at 10.1007/s13346-025-01974-x.