Leveraging machine learning to streamline the development of liposomal drug delivery systems.

Drug delivery systems efficiently and safely administer therapeutic agents to specific body sites. Liposomes, spherical vesicles made of phospholipid bilayers, have become a powerful tool in this field, especially with the rise of microfluidic manufacturing during the COVID-19 pandemic. Despite its efficiency, microfluidic liposomal production poses challenges, often requiring laborious, optimization on a case-by-case basis.

Microfluidic formulation, cryoprotection and long-term stability of paclitaxel-loaded π electron-stabilized polymeric micelles.

Controlled manufacturing and long-term stability are key challenges in the development and translation of nanomedicines. This is exemplified by the mRNA-nanoparticle vaccines against COVID-19, which require (ultra-)cold temperatures for storage and shipment. Various cryogenic protocols have been explored to prolong nanomedicine shelf-life.

Leveraging 3D-printed microfluidic micromixers for the continuous manufacture of melatonin loaded SNEDDS with enhanced antioxidant activity and skin permeability.

Vesicants are chemical warfare agents (CWAs) capable of causing severe skin damage and systemic toxicity. Melatonin, known for its anti-inflammatory and antioxidant properties, can mitigate the effects of these agents. Self-nano-emulsifying drug delivery systems (SNEDDS) containing a high melatonin concentration (5 %, 50 mg/g) were optimized using a quality-by-design approach from biocompatible, non-irritant excipients with a particle size of about 100 nm.