Filarial diseases represent a significant social and economic burden to over 120 million people worldwide and are caused by endoparasites that require the presence of symbiotic bacteria of the genus Wolbachia for fertility and viability of the host parasite. Targeting Wolbachia for elimination is a therapeutic approach that shows promise in the treatment of onchocerciasis and lymphatic filariasis. Here we demonstrate the use of a biodegradable polyanhydride nanoparticle-based platform for the co-delivery of the antibiotic doxycycline with the antiparasitic drug, ivermectin, to reduce microfilarial burden and rapidly kill adult worms. When doxycycline and ivermectin were co-delivered within polyanhydride nanoparticles, effective killing of adult female Brugia malayi filarial worms was achieved with approximately 4,000-fold reduction in the amount of drug used. Additionally the time to death of the macrofilaria was also significantly reduced (five-fold) when the anti-filarial drug cocktail was delivered within polyanhydride nanoparticles. We hypothesize that the mechanism behind this dramatically enhanced killing of the macrofilaria is the ability of the polyanhydride nanoparticles to behave as a Trojan horse and penetrate the cuticle, bypassing excretory pumps of B. malayi, and effectively deliver drug directly to both the worm and Wolbachia at high enough microenvironmental concentrations to cause death. These provocative findings may have significant consequences for the reduction in the amount of drug and the length of treatment required for filarial infections in terms of patient compliance and reduced cost of treatment.

Complex biological barriers are major obstacles for preventing and treating disease. Nano-carriers are designed to overcome such obstacles by enhancing drug delivery through physiochemical barriers and improving therapeutic indices. This review critically examines both biological barriers and nano-carrier payloads for a variety of drug delivery applications. A spectrum of nano-carriers is discussed that have been successfully developed for improving tissue penetration for preventing or treating a range of infectious, inflammatory, and degenerative diseases.

No abstract

Drug delivery vehicles can improve the functional efficacy of existing antimicrobial therapies by improving biodistribution and targeting. A critical property of such nanomedicine formulations is their ability to control the release kinetics of their payloads. The combination of (and interactions between) polymer, drug, and nanoparticle properties gives rise to nonlinear behavioral relationships and a large data space. These factors complicate both first-principles modeling and screening of nanomedicine formulations. Predictive analytics may offer a more efficient approach toward rational design of nanomedicines by identifying key descriptors and correlating them to nanoparticle release behavior. In this work, antibiotic release kinetics data were generated from polyanhydride nanoparticle formulations with varying copolymer compositions, encapsulated drug type, and drug loading. Four antibiotics, doxycycline, rifampicin, chloramphenicol, and pyrazinamide, were used. Linear manifold learning methods were used to relate drug release properties with polymer, drug, and nanoparticle properties, and key descriptors were identified that are highly correlated with release properties. However, these linear methods could not predict release behavior. Non-linear multivariate modeling based on graph theory was then used to deconvolute the governing relationships between these properties, and predictive models were generated to rapidly screen lead nanomedicine formulations with desirable release properties with minimal nanoparticle characterization. Release kinetics predictions of two drugs containing atoms not included in the model showed good agreement with experimental results, validating the model and indicating its potential to virtually explore new polymer and drug pairs not included in training data set. The models were shown to be robust after inclusion of these new formulations in that the new inclusions did not significantly change model regression. This approach provides the first steps towards development of a framework that can be used to rationally design nanomedicine formulations by selecting the appropriate carrier for a drug payload to program desirable release kinetics.

Mycobacterium marinum is a waterborne pathogen responsible for tuberculosis-like infections in cold-blooded animals and is an opportunistic pathogen in humans. M. marinum is the closest genetic relative of the Mycobacterium tuberculosis complex and is a reliable surrogate for drug susceptibility testing. We synthesized and evaluated two nanoparticle (NP) formulations for compatibility with rifampicin, isoniazid, pyrazinamide, and ethambutol (PIRE), the front-line antimycobacterial drugs used in combination against active tuberculosis infections. Improved in vitro antimicrobial activity was observed with encapsulated rifampicin alone or in a cocktail of drugs formulated through co-encapsulation in amphiphilic polyanhydride NPs. Broth antimicrobial testing revealed that the encapsulation of PIRE in NP resulted in a significant increase in antimicrobial activity, with the benefit over soluble formulations at biologically relevant concentrations ranging from >10 to >3,000 fold. M. marinum-infected human macrophages treated with NP-PIRE were cleared of viable bacteria in 48 h following a single treatment, representing a >4 log reduction in colony-forming units and a >2,000-fold increase in antimicrobial activity. The amphiphilic polyanhydride nanoparticles demonstrated the ability to co-encapsulate PIRE antibiotics and enhance their antimicrobial activity against M. marinum in infected macrophages in culture and in vitro. These data suggest that polyanhydride nanoparticles are a promising nanotherapeutic for combatting Mycobacterium infections through improved intracellular targeting of encapsulated antibiotics.