AIMC Topic: Liposomes

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'Applications of machine learning in liposomal formulation and development'.

Pharmaceutical development and technology
Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly in the design and optimization of liposomal formulations. This review focuses on the intersection of ML and liposomal technology, highlighting how advanced algo...

Deep Learning for the Accurate Prediction of Triggered Drug Delivery.

IEEE transactions on nanobioscience
The need to mitigate the adverse effects of chemotherapy has driven the exploration of innovative drug delivery approaches. One emerging trend in cancer treatment is the utilization of Drug Delivery Systems (DDSs), facilitated by nanotechnology. Nano...

Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.

Nature communications
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial i...

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

Journal of controlled release : official journal of the Controlled Release Society
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 manufa...

Review of machine learning for lipid nanoparticle formulation and process development.

Journal of pharmaceutical sciences
Lipid nanoparticles (LNPs) are a subset of pharmaceutical nanoparticulate formulations designed to encapsulate, stabilize, and deliver nucleic acid cargoes in vivo. Applications for LNPs include new interventions for genetic disorders, novel classes ...

Rational Design of Lipid Nanoparticles for Enhanced mRNA Vaccine Delivery via Machine Learning.

Small (Weinheim an der Bergstrasse, Germany)
Since the coronavirus pandemic, mRNA vaccines have revolutionized the field of vaccinology. Lipid nanoparticles (LNPs) are proposed to enhance mRNA delivery efficiency; however, their design is suboptimal. Here, a rational method for designing LNPs i...

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.

Journal of colloid and interface science
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 de...

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Nature communications
Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this ...

Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Scientific reports
Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effec...