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

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 study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry.

Combinatorial design of ionizable lipid nanoparticles for muscle-selective mRNA delivery with minimized off-target effects.

Ionizable lipid nanoparticles (LNPs) pivotal to the success of COVID-19 mRNA (messenger RNA) vaccines hold substantial promise for expanding the landscape of mRNA-based therapies. Nevertheless, the risk of mRNA delivery to off-target tissues highlights the necessity for LNPs with enhanced tissue selectivity. The intricate nature of biological systems and inadequate knowledge of lipid structure-activity relationships emphasize the significance of high-throughput methods to produce chemically diverse lipid libraries for mRNA delivery screening.

Spatiotemporally sequential delivery of biomimetic liposomes potentiates glioma chemotherapy.

As one of the most challenging cancers, glioma still lacks efficient therapeutic treatment in clinics. The dilemmas of nanodrug-based therapies for glioma are due not only the limited permeability of the blood-brain barrier (BBB) but also the deficiency of targeting tumor lesions. Thus, spatiotemporally sequential delivery of therapeutics from BBB-crossing to glioma accumulation is considered a strategy to obtain better outcomes.

Sequentially sustained release of anticarcinogens for postsurgical chemoimmunotherapy.

Postsurgical treatment is of great importance to combat tumor recurrence and metastasis. Anti-CD47 antibodies (aCD47) can block the CD47-signal regulatory protein-alpha (CD47-SIRPα) pathway to restore immunity. Here, an in-situ gel implantation was engineered by crosslinking chitosan (CS) and pullulan (Pul) for postsurgical treatment.

Design and validation of a simple device for insufflation of dry powders in a mice model.

Delivery of inhalational dry powders (DPs) to the lung of mice is pivotal for pre-clinical pharmacokinetic and pharmacodynamic investigations. Although several devices have been reported, their application is always limited by many factors, including complicated design, high price, commercially discontinued status, as well as requirement of special skills. Here, we have introduced a simple device for non-invasive and precise delivery of DPs in mice.