Rational Method Development of In Vitro Release Methodologies for Nanomedicines

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Nanomedicines have been researched and developed over the last decades because their small size provides attractive properties for the delivery of drugs, such as the ability to pass certain biological barriers or bypass certain elimination processes within the body. The umbrella term nanomedicines includes a range of different drug formulation methodologies such as polymeric nanoparticles, lipid vesicles and dendrimers. Despite the considerable body of work on the manufacture and physicochemical properties of nanomedicine formulations, standardised and regulatory approved procedures to characterise drug release from nanomedicines are still lacking. Compared to other formulation routes such as oral formulations, the lack of established drug release procedures is a main gap for the development and regulatory approval of nanomedicines. We believe that this gap originates in parts from a lack of fundamental and, if possible, universal understanding of key parameters that affect drug release from nanomedicines. This is likely linked to the complexity of the different nanomedicine formulations and the diversity of drug release methodologies that have been used. In this project, we therefore propose a rational and systematic approach to curate and acquire drug release data from three classes of nanomedicine formulations; polymeric nanoparticles, lipid vesicles and dendrimers. We will first establish suitable analytical pipelines for characterising drug release from these formulations, followed by a computational approach to identifying key physicochemical properties of these formulations that can be used to categorise the drug release profile from these formulations. A machine learning approach will be used to establish a predictive tool to connect nanomedicine properties with drug release profiles. The final outcome of the project will be a recommendation for a universal workflow for the classification and drug release characterisation from nanoparticle-based formulations.