Novel approaches for vaccine development.

Vaccines are critical tools for maintaining global health. Traditional vaccine technologies have been used across a wide range of bacterial and viral pathogens, yet there are a number of examples where they have not been successful, such as for persistent infections, rapidly evolving pathogens with high sequence variability, complex viral antigens, and emerging pathogens. Novel technologies such as nucleic acid and viral vector vaccines offer the potential to revolutionize vaccine development as they are well-suited to address existing technology limitations. In this review, we discuss the current state of RNA vaccines, recombinant adenovirus vector-based vaccines, and advances from biomaterials and engineering that address these important public health challenges.

Identification of a therapeutic interfering particle-A single-dose SARS-CoV-2 antiviral intervention with a high barrier to resistance.

Viral-deletion mutants that conditionally replicate and inhibit the wild-type virus (i.e., defective interfering particles, DIPs) have long been proposed as single-administration interventions with high genetic barriers to resistance. However, theories predict that robust, therapeutic DIPs (i.e., therapeutic interfering particles, TIPs) must conditionally spread between cells with R0 >1. Here, we report engineering of TIPs that conditionally replicate with SARS-CoV-2, exhibit R0 >1, and inhibit viral replication 10- to 100-fold. Inhibition occurs via competition for viral replication machinery, and a single administration of TIP RNA inhibits SARS-CoV-2 sustainably in continuous cultures. Strikingly, TIPs maintain efficacy against neutralization-resistant variants (e.g., B.1.351). In hamsters, both prophylactic and therapeutic intranasal administration of lipid-nanoparticle TIPs durably suppressed SARS-CoV-2 by 100-fold in the lungs, reduced pro-inflammatory cytokine expression, and prevented severe pulmonary edema. These data provide proof of concept for a class of single-administration antivirals that may circumvent current requirements to continually update medical countermeasures against new variants.

Messenger RNA vaccines against SARS-CoV-2.

The first two vaccines proven to be effective for inhibiting COVID-19 illness were both mRNA, achieving 95% efficacy (and safety) among 74,000 participants (half receiving placebo) after intramuscular delivery of two shots, 3-4 weeks apart. To view this Bench to Bedside, open or download the PDF.

Endocytosis Inhibition in Humans to Improve Responses to ADCC-Mediating Antibodies.

A safe and controlled manipulation of endocytosis in vivo may have disruptive therapeutic potential. Here, we demonstrate that the anti-emetic/anti-psychotic prochlorperazine can be repurposed to reversibly inhibit the in vivo endocytosis of membrane proteins targeted by therapeutic monoclonal antibodies, as directly demonstrated by our human tumor ex vivo assay. Temporary endocytosis inhibition results in enhanced target availability and improved efficiency of natural killer cell-mediated antibody-dependent cellular cytotoxicity (ADCC), a mediator of clinical responses induced by IgG1 antibodies, demonstrated here for cetuximab, trastuzumab, and avelumab. Extensive analysis of downstream signaling pathways ruled out on-target toxicities. By overcoming the heterogeneity of drug target availability that frequently characterizes poorly responsive or resistant tumors, clinical application of reversible endocytosis inhibition may considerably improve the clinical benefit of ADCC-mediating therapeutic antibodies.

Programmable protein delivery with a bacterial contractile injection system.

Endosymbiotic bacteria have evolved intricate delivery systems that enable these organisms to interface with host biology. One example, the extracellular contractile injection systems (eCISs), are syringe-like macromolecular complexes that inject protein payloads into eukaryotic cells by driving a spike through the cellular membrane. Recently, eCISs have been found to target mouse cells1-3, raising the possibility that these systems could be harnessed for therapeutic protein delivery. However, whether eCISs can function in human cells remains unknown, and the mechanism by which these systems recognize target cells is poorly understood. Here we show that target selection by the Photorhabdus virulence cassette (PVC)-an eCIS from the entomopathogenic bacterium Photorhabdus asymbiotica-is mediated by specific recognition of a target receptor by a distal binding element of the PVC tail fibre. Furthermore, using in silico structure-guided engineering of the tail fibre, we show that PVCs can be reprogrammed to target organisms not natively targeted by these systems-including human cells and mice-with efficiencies approaching 100%. Finally, we show that PVCs can load diverse protein payloads, including Cas9, base editors and toxins, and can functionally deliver them into human cells. Our results demonstrate that PVCs are programmable protein delivery devices with possible applications in gene therapy, cancer therapy and biocontrol.

Regulated control of gene therapies by drug-induced splicing.

So far, gene therapies have relied on complex constructs that cannot be finely controlled1,2. Here we report a universal switch element that enables precise control of gene replacement or gene editing after exposure to a small molecule. The small-molecule inducers are currently in human use, are orally bioavailable when given to animals or humans and can reach both peripheral tissues and the brain. Moreover, the switch system, which we denote Xon, does not require the co-expression of any regulatory proteins. Using Xon, the translation of the desired elements for controlled gene replacement or gene editing machinery occurs after a single oral dose of the inducer, and the robustness of expression can be controlled by the drug dose, protein stability and redosing. The ability of Xon to provide temporal control of protein expression can be adapted for cell-biology applications and animal studies. Additionally, owing to the oral bioavailability and safety of the drugs used, the Xon switch system provides an unprecedented opportunity to refine and tailor the application of gene therapies in humans.

Modeling of spatiotemporal dynamics of ligand-coated particle flow in targeted drug delivery processes.

Nanoparticles tethered with vasculature-binding epitopes have been used to deliver the drug into injured or diseased tissues via the bloodstream. However, the extent that blood flow dynamics affects nanoparticle retention at the target site after adhesion needs to be better understood. This knowledge gap potentially underlies significantly different therapeutic efficacies between animal models and humans. An experimentally validated mathematical model that accurately simulates the effects of blood flow on nanoparticle adhesion and retention, thus circumventing the limitations of conventional trial-and-error-based drug design in animal models, is lacking. This paper addresses this technical bottleneck and presents an integrated mathematical method that derives heavily from a unique combination of a mechanics-based dispersion model for nanoparticle transport and diffusion in the boundary layers, an asperity model to account for surface roughness of endothelium, and an experimentally calibrated stochastic nanoparticle-cell adhesion model to describe nanoparticle adhesion and subsequent retention at the target site under external flow. PLGA-b-HA nanoparticles tethered with VHSPNKK peptides that specifically bind to vascular cell adhesion molecules on the inflamed vascular wall were investigated. The computational model revealed that larger particles perform better in adhesion and retention at the endothelium for the particle sizes suitable for drug delivery applications and within physiologically relevant shear rates. The computational model corresponded closely to the in vitro experiments which demonstrates the impact that model-based simulations can have on optimizing nanocarriers in vascular microenvironments, thereby substantially reducing in vivo experimentation as well as the development costs.

Curvature-mediated rapid extravasation and penetration of nanoparticles against interstitial fluid pressure for improved drug delivery.

Elevated interstitial fluid pressure (IFP) within pathological tissues (e.g., tumors, obstructed kidneys, and cirrhotic livers) creates a significant hindrance to the transport of nanomedicine, ultimately impairing the therapeutic efficiency. Among these tissues, solid tumors present the most challenging scenario. While several strategies through reducing tumor IFP have been devised to enhance nanoparticle delivery, few approaches focus on modulating the intrinsic properties of nanoparticles to effectively counteract IFP during extravasation and penetration, which are precisely the stages obstructed by elevated IFP. Herein, we propose an innovative solution by engineering nanoparticles with a fusiform shape of high curvature, enabling efficient surmounting of IFP barriers during extravasation and penetration within tumor tissues. Through experimental and theoretical analyses, we demonstrate that the elongated nanoparticles with the highest mean curvature outperform spherical and rod-shaped counterparts against elevated IFP, leading to superior intratumoral accumulation and antitumor efficacy. Super-resolution microscopy and molecular dynamics simulations uncover the underlying mechanisms in which the high curvature contributes to diminished drag force in surmounting high-pressure differentials during extravasation. Simultaneously, the facilitated rotational movement augments the hopping frequency during penetration. This study effectively addresses the limitations posed by high-pressure impediments, uncovers the mutual interactions between the physical properties of NPs and their environment, and presents a promising avenue for advancing cancer treatment through nanomedicine.

Simultaneous targeting of peripheral and brain tumors with a therapeutic nanoparticle to disrupt metabolic adaptability at both sites.

Brain metastasis of advanced breast cancer often results in deleterious consequences. Metastases to the brain lead to significant challenges in treatment options, as the blood-brain barrier (BBB) prevents conventional therapy. Thus, we hypothesized that creation of a nanoparticle (NP) that distributes to both primary tumor site and across the BBB for secondary brain tumor can be extremely beneficial. Here, we report a simple targeting strategy to attack both the primary breast and secondary brain tumors utilizing a single NP platform. The nature of these mitochondrion-targeted, BBB-penetrating NPs allow for simultaneous targeting and drug delivery to the hyperpolarized mitochondrial membrane of the extracranial primary tumor site in addition to tumors at the brain. By utilizing a combination of such dual anatomical distributing NPs loaded with therapeutics, we demonstrate a proof-of-concept idea to combat the increased metabolic plasticity of brain metastases by lowering two major energy sources, oxidative phosphorylation (OXPHOS) and glycolysis. By utilizing complementary studies and genomic analyses, we demonstrate the utility of a chemotherapeutic prodrug to decrease OXPHOS and glycolysis by pairing with a NP loaded with pyruvate dehydrogenase kinase 1 inhibitor. Decreasing glycolysis aims to combat the metabolic flexibility of both primary and secondary tumors for therapeutic outcome. We also address the in vivo safety parameters by addressing peripheral neuropathy and neurobehavior outcomes. Our results also demonstrate that this combination therapeutic approach utilizes mitochondrial genome targeting strategy to overcome DNA repair-based chemoresistance mechanisms.

Patient Centricity Driving Formulation Innovation: Improvements in Patient Care Facilitated by Novel Therapeutics and Drug Delivery Technologies.

Innovative formulation technologies can play a crucial role in transforming a novel molecule to a medicine that significantly enhances patients' lives. Improved mechanistic understanding of diseases has inspired researchers to expand the druggable space using new therapeutic modalities such as interfering RNA, protein degraders, and novel formats of monoclonal antibodies. Sophisticated formulation strategies are needed to deliver the drugs to their sites of action and to achieve patient centricity, exemplified by messenger RNA vaccines and oral peptides. Moreover, access to medical information via digital platforms has resulted in better-informed patient groups that are requesting consideration of their needs during drug development. This request is consistent with health authority efforts to upgrade their regulations to advance age-appropriate product development for patients. This review describes formulation innovations contributingto improvements in patient care: convenience of administration, preferred route of administration, reducing dosing burden, and achieving targeted delivery of new modalities.

PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction.

MOTIVATION: Effective drug delivery systems are paramount in enhancing pharmaceutical outcomes, particularly through the use of cell-penetrating peptides (CPPs). These peptides are gaining prominence due to their ability to penetrate eukaryotic cells efficiently without inflicting significant damage to the cellular membrane, thereby ensuring optimal drug delivery. However, the identification and characterization of CPPs remain a challenge due to the laborious and time-consuming nature of conventional methods, despite advances in proteomics. Current computational models, however, are predominantly tailored for balanced datasets, an approach that falls short in real-world applications characterized by a scarcity of known positive CPP instances. RESULTS: To navigate this shortfall, we introduce PractiCPP, a novel deep-learning framework tailored for CPP prediction in highly imbalanced data scenarios. Uniquely designed with the integration of hard negative sampling and a sophisticated feature extraction and prediction module, PractiCPP facilitates an intricate understanding and learning from imbalanced data. Our extensive computational validations highlight PractiCPP's exceptional ability to outperform existing state-of-the-art methods, demonstrating remarkable accuracy, even in datasets with an extreme positive-to-negative ratio of 1:1000. Furthermore, through methodical embedding visualizations, we have established that models trained on balanced datasets are not conducive to practical, large-scale CPP identification, as they do not accurately reflect real-world complexities. In summary, PractiCPP potentially offers new perspectives in CPP prediction methodologies. Its design and validation, informed by real-world dataset constraints, suggest its utility as a valuable tool in supporting the acceleration of drug delivery advancements. AVAILABILITY AND IMPLEMENTATION: The source code of PractiCPP is available on Figshare at https://doi.org/10.6084/m9.figshare.25053878.v1.

Recent Developments in Aerosol Pulmonary Drug Delivery: New Technologies, New Cargos, and New Targets.

There is nothing like a global pandemic to motivate the need for improved respiratory treatments and mucosal vaccines. Stimulated by the COVID-19 pandemic, pulmonary aerosol drug delivery has seen a flourish of activity, building on the prior decades of innovation in particle engineering, inhaler device technologies, and clinical understanding. As such, the field has expanded into new directions and is working toward the efficient delivery of increasingly complex cargos to address a wider range of respiratory diseases. This review seeks to highlight recent innovations in approaches to personalize inhalation drug delivery, deliver complex cargos, and diversify the targets treated and prevented through pulmonary drug delivery. We aim to inform readers of the emerging efforts within the field and predict where future breakthroughs are expected to impact the treatment of respiratory diseases.

Chandipura viral glycoprotein (CNV-G) promotes Gectosome generation and enables delivery of intracellular therapeutics.

Overexpression of vesicular stomatitis virus G protein (VSV-G) elevates the secretion of EVs known as gectosomes, which contain VSV-G. Such vesicles can be engineered to deliver therapeutic macromolecules. We investigated viral glycoproteins from several viruses for their potential in gectosome production and intracellular cargo delivery. Expression of the viral glycoprotein (viral glycoprotein from the Chandipura virus [CNV-G]) from the human neurotropic pathogen Chandipura virus in 293T cells significantly augments the production of CNV-G-containing gectosomes. In comparison with VSV-G gectosomes, CNV-G gectosomes exhibit heightened selectivity toward specific cell types, including primary cells and tumor cell lines. Consistent with the differential tropism between CNV-G and VSV-G gectosomes, cellular entry of CNV-G gectosome is independent of the Low-density lipoprotein receptor, which is essential for VSV-G entry, and shows varying sensitivity to pharmacological modulators. CNV-G gectosomes efficiently deliver diverse intracellular cargos for genomic modification or responses to stimuli in vitro and in the brain of mice in vivo utilizing a split GFP and chemical-induced dimerization system. Pharmacokinetics and biodistribution analyses support CNV-G gectosomes as a versatile platform for delivering macromolecular therapeutics intracellularly.

Engineering small-molecule and protein drugs for targeting bone tumors.

Bone cancer is common and severe. Both primary (e.g., osteosarcoma, Ewing sarcoma) and secondary (e.g., metastatic) bone cancers lead to significant health problems and death. Currently, treatments such as chemotherapy, hormone therapy, and radiation therapy are used to treat bone cancer, but they often only shrink or slow tumor growth and do not eliminate cancer completely. The bone microenvironment contributes unique signals that influence cancer growth, immunogenicity, and metastasis. Traditional cancer therapies have limited effectiveness due to off-target effects and poor distribution on bones. As a result, therapies with improved specificity and efficacy for treating bone tumors are highly needed. One of the most promising strategies involves the targeted delivery of pharmaceutical agents to the site of bone cancer by introduction of bone-targeting moieties, such as bisphosphonates or oligopeptides. These moieties have high affinities to the bone hydroxyapatite matrix, a structure found exclusively in skeletal tissue, and can enhance the targeting ability and efficacy of anticancer drugs when combating bone tumors. This review focuses on the engineering of small molecules and proteins with bone-targeting moieties for the treatment of bone tumors.

Targeting lipid nanoparticles to the blood-brain barrier to ameliorate acute ischemic stroke.

Effective delivery of mRNA or small molecule drugs to the brain is a significant challenge in developing treatment for acute ischemic stroke (AIS). To address the problem, we have developed targeted nanomedicine to increase drug concentrations in endothelial cells of the blood-brain barrier (BBB) of the injured brain. Inflammation during ischemic stroke causes continuous neuronal death and an increase in the infarct volume. To enable targeted delivery to the inflamed BBB, we conjugated lipid nanocarriers (NCs) with antibodies that bind cell adhesion molecules expressed at the BBB. In the transient middle cerebral artery occlusion mouse model, NCs targeted to vascular cellular adhesion molecule-1 (VCAM) achieved the highest level of brain delivery, nearly two orders of magnitude higher than untargeted ones. VCAM-targeted lipid nanoparticles with luciferase-encoding mRNA and Cre-recombinase showed selective expression in the ischemic brain. Anti-inflammatory drugs administered intravenously after ischemic stroke reduced cerebral infarct volume by 62% (interleukin-10 mRNA) or 35% (dexamethasone) only when they were encapsulated in VCAM-targeted NCs. Thus, VCAM-targeted lipid NCs represent a new platform for strongly concentrating drugs within the compromised BBB of penumbra, thereby ameliorating AIS.

Lung-selective mRNA delivery of synthetic lipid nanoparticles for the treatment of pulmonary lymphangioleiomyomatosis.

Safe and efficacious systemic delivery of messenger RNA (mRNA) to specific organs and cells in vivo remains the major challenge in the development of mRNA-based therapeutics. Targeting of systemically administered lipid nanoparticles (LNPs) coformulated with mRNA has largely been confined to the liver and spleen. Using a library screening approach, we identified that N-series LNPs (containing an amide bond in the tail) are capable of selectively delivering mRNA to the mouse lung, in contrast to our previous discovery that O-series LNPs (containing an ester bond in the tail) that tend to deliver mRNA to the liver. We analyzed the protein corona on the liver- and lung-targeted LNPs using liquid chromatography-mass spectrometry and identified a group of unique plasma proteins specifically absorbed onto the surface that may contribute to the targetability of these LNPs. Different pulmonary cell types can also be targeted by simply tuning the headgroup structure of N-series LNPs. Importantly, we demonstrate here the success of LNP-based RNA therapy in a preclinical model of lymphangioleiomyomatosis (LAM), a destructive lung disease caused by loss-of-function mutations in the Tsc2 gene. Our lung-targeting LNP exhibited highly efficient delivery of the mouse tuberous sclerosis complex 2 (Tsc2) mRNA for the restoration of TSC2 tumor suppressor in tumor and achieved remarkable therapeutic effect in reducing tumor burden. This research establishes mRNA LNPs as a promising therapeutic intervention for the treatment of LAM.

Virus-Inspired Glucose and Polydopamine (GPDA)-Coating as an Effective Strategy for the Construction of Brain Delivery Platforms.

The ability of drugs to cross the blood-brain barrier (BBB) is crucial for treating central nervous system (CNS) disorders. Inspired by natural viruses, here we report a glucose and polydopamine (GPDA) coating method for the construction of delivery platforms for efficient BBB crossing. Such platforms are composed of nanoparticles (NPs) as the inner core and surface functionalized with glucose-poly(ethylene glycol) (Glu-PEG) and polydopamine (PDA) coating. Glu-PEG provides selective targeting of the NPs to brain capillary endothelial cells (BCECs), while PDA enhances the transcytosis of the NPs. This strategy is applicable to gold NPs (AuNPs), silica, and polymeric NPs, which achieves as high as 1.87% of the injected dose/g of brain in healthy brain tissues. In addition, the GPDA coating manages to deliver NPs into the tumor tissue in the orthotopic glioblastoma model. Our study may provide a universal strategy for the construction of delivery platforms for efficient BBB crossing and brain drug delivery.

Probing the Impact of Surface Functionalization Module on the Performance of Mitoxantrone Prodrug Nanoassemblies: Improving the Effectiveness and Safety.

Prodrug nanoassemblies are emerging as a novel drug delivery system for chemotherapy, comprising four fundamental modules: a drug module, a modification module, a response module, and a surface functionalization module. Among these modules, surface functionalization is an essential process to enhance the biocompatibility and stability of the nanoassemblies. Here, we selected mitoxantrone (MTO) as the drug module and DSPE-PEG2K as surface functionalization module to develop MTO prodrug nanoassemblies. We systematically evaluated the effect of surface functionalization module ratios (10%, 20%, 40%, and 60% of prodrug, WDSPE-mPEG2000/Wprodrug) on the prodrug nanoassemblies. The results indicated that 40% NPs significantly improved the self-assembly stability and cellular uptake of prodrug nanoassemblies. Compared with MTO solution, 40% NPs showed better tumor specificity and pharmacokinetics, resulting in potent antitumor activity with a good safety profile. These findings highlighted the pivotal role of the surface functionalization module in regulating the performance of mitoxantrone prodrug nanoassemblies for cancer treatment.

Toward the Scalable, Rapid, Reproducible, and Cost-Effective Synthesis of Personalized Nanomedicines at the Point of Care.

Organic nanoparticles are used in nanomedicine, including for cancer treatment and some types of COVID-19 vaccines. Here, we demonstrate the scalable, rapid, reproducible, and cost-effective synthesis of three model organic nanoparticle formulations relevant to nanomedicine applications. We employed a custom-made, low-cost fluid mixer device constructed from a commercially available three-dimensional printer. We investigated how systematically changing aqueous and organic volumetric flow rate ratios determined liposome, polymer nanoparticle, and solid lipid nanoparticle sizes, size distributions, and payload encapsulation efficiencies. By manipulating inlet volumes, we synthesized organic nanoparticles with encapsulation efficiencies approaching 100% for RNA-based payloads. The synthesized organic nanoparticles were safe and effective at the cell culture level, as demonstrated by various assays. Such cost-effective synthesis approaches could potentially increase the accessibility to clinically relevant organic nanoparticle formulations for personalized nanomedicine applications at the point of care, especially in nonhospital and low-resource settings.

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG-PLGA Polymer Nanoparticles.

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.