Dosing extracellular vesicles

Extracellular vesicles (EVs) are natural nanoparticles containing biologically active molecules. They are important mediators of intercellular communication and can be exploited therapeutically by various bioengineering approaches. To accurately determine the therapeutic potential of EVs in pre-clinical and clinical settings, dependable dosing strategies are of utmost importance. However, the field suffers from inconsistencies comprising all areas of EV production and characterisation. Therefore, a standardised and well-defined process in EV quantification, key to reliable therapeutic EV dosing, remains to be established. Here, we examined 64 pre-clinical studies for EV-based therapeutics with respect to their applied EV dosing strategies. We identified variations in effective dosing strategies irrespective of the applied EV purification method and cell source. Moreover, we found dose discrepancies depending on the disease model, where EV doses were selected without accounting for published EV pharmacokinetics or biodistribution patterns. We therefore propose to focus on qualitative aspects when dosing EV-based therapeutics, such as the potency of the therapeutic cargo entity. This will ensure batch-to-batch reliability and enhance reproducibility between applications. Furthermore, it will allow for the successful benchmarking of EV-based therapeutics compared to other nanoparticle drug delivery systems, such as viral vector based or lipid-based nanoparticle approaches. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

Automated summary

This study analyzed 64 pre-clinical studies on EV-based therapeutics and found variations in dosing strategies regardless of EV purification method. Disease models influenced dose discrepancies, showing a need for qualitative consideration in EV dosing. Recommendations were made to focus on qualitative aspects like therapeutic cargo potency for better reliability and reproducibility in EV-based therapeutics.