Transitioning the production of lipidic mesophase-based delivery systems from lab-scale to robust industrial manufacturing following a risk-based quality by design approach augmented by artificial intelligence

Lipidic mesophase drug carriers have demonstrated the capacity to host and effectively deliver a wide range of active pharmaceutical ingredients, yet they have not been as extensively commercialized as other lipid-based products, such as liposomal delivery systems. Indeed, scientists are primarily focused on investigating the physics of these systems, especially in biological environments. Meanwhile, the production methods remain less advanced, and researchers are still uncertain about how the manufacturing process might affect the quality of formulations. Bringing these products to the market will require an industrial translation process. In this scenario, we have developed a robust strategy to produce lipidic mesophase-based drug delivery systems using a dual-syringe setup. We identified four critical process parameters in the newly developed method (dual-syringe method), in comparison to eight in the standard production method (gold standard), and we defined their optimal limits following a Quality by Design approach. The robustness and versatility of the proposed method were assessed experimentally by incorporating drugs with diverse physicochemical properties and augmented by machine learning which, by predicting the drug release from lipidic mesophases, reduces the formulation development time and costs.