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Towards artificial intelligence-enabled extracellular vesicle precision drug delivery.

Zachary F Greenberg¹, Kiley S Graim², Mei He¹

¹Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.

Advanced Drug Delivery Reviews

|June 25, 2023

Summary

Artificial intelligence (AI) enhances extracellular vesicle (EV) therapies for precision drug delivery. Integrating large-scale EV data with AI addresses heterogeneity challenges, paving the way for AI-directed EV therapies and clinical translation.

Keywords:

Artificial Intelligence Drug Delivery Extracellular Vesicles

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Area of Science:

Nanomedicine
Biotechnology
Artificial Intelligence

Background:

Extracellular Vesicles (EVs), including exosomes, are promising nanomedicine drug delivery vehicles due to biocompatibility and stability.
EV heterogeneity poses a significant challenge for achieving precise molecular targeting in drug delivery.
Identifying molecular drivers for EV tissue targeting specificity is crucial for advancing EV-based therapies.

Purpose of the Study:

To review the integration of Artificial Intelligence (AI) with large-scale Extracellular Vesicle (EV) data for developing advanced drug delivery systems.
To explore the potential of AI-directed EV therapies for precision drug delivery and clinical translation.
To discuss the current limitations, standardization challenges, and future considerations for AI-enhanced EV therapies.

Main Methods:

Review of current literature on EVs in drug delivery, focusing on nanomedicine applications.
Integration of large-scale EV datasets with AI algorithms for predictive modeling.
Analysis of AI's role in engineering EVs for enhanced tissue targeting and precision control.

Main Results:

AI offers powerful predictive capabilities for guiding the rational design of engineered EVs.
AI integration with EV data can overcome heterogeneity challenges, enabling precise molecular targeting.
AI-directed EV therapies demonstrate significant potential for improving drug delivery efficacy and specificity.

Conclusions:

AI is pivotal in advancing EV-based drug delivery towards precision medicine.
Addressing standardization and critical considerations is essential for the successful clinical translation of AI-combined EV therapies.
A collaborative effort between AI and EV research is key to unlocking the full clinical potential of these novel therapies.