Application of Lipid-Based Nanocarriers for Antitubercular Drug Delivery: A Review.
Aristote B BuyaBwalya Angel WitikaAlain Murhimalika BapolisiChiluba MwilaGrady K MukubwaPatrick B MemvangaPedzisai Anotida MakoniChristian Isalomboto NkangaPublished in: Pharmaceutics (2021)
The antimicrobial drugs currently used for the management of tuberculosis (TB) exhibit poor bioavailability that necessitates prolonged treatment regimens and high dosing frequency to achieve optimal therapeutic outcomes. In addition, these agents cause severe adverse effects, as well as having detrimental interactions with other drugs used in the treatment of comorbid conditions such as HIV/AIDS. The challenges associated with the current TB regimens contribute to low levels of patient adherence and, consequently, the development of multidrug-resistant TB strains. This has led to the urgent need to develop newer drug delivery systems to improve the treatment of TB. Targeted drug delivery systems provide higher drug concentrations at the infection site, thus leading to reduced incidences of adverse effects. Lipid-based nanocarriers have proven to be effective in improving the solubility and bioavailability of antimicrobials whilst decreasing the incidence of adverse effects through targeted delivery. The potential application of lipid-based carriers such as liposomes, niosomes, solid lipid nanoparticles, nanostructured lipid carriers, nano and microemulsions, and self-emulsifying drug delivery systems for the treatment of TB is reviewed herein. The composition of the investigated lipid-based carriers, their characteristics, and their influence on bioavailability, toxicity, and sustained drug delivery are also discussed. Overall, lipid-based systems have shown great promise in anti-TB drug delivery applications. The summary of the reviewed data encourages future efforts to boost the translational development of lipid-based nanocarriers to improve TB therapy.
Keyphrases
- drug delivery
- mycobacterium tuberculosis
- cancer therapy
- hiv aids
- fatty acid
- multidrug resistant
- drug release
- stem cells
- escherichia coli
- type diabetes
- emergency department
- staphylococcus aureus
- oxidative stress
- machine learning
- risk factors
- human immunodeficiency virus
- pseudomonas aeruginosa
- metabolic syndrome
- hepatitis c virus
- combination therapy
- current status
- electronic health record
- adipose tissue
- deep learning
- artificial intelligence
- pulmonary tuberculosis
- high resolution
- acinetobacter baumannii