The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further /clinical research.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210030PMC
http://dx.doi.org/10.1021/acsomega.2c05511DOI Listing

Publication Analysis

Top Keywords

repurposed drugs
12
drugs identified
8
novel drugs
8
drugs
7
potential repurposed
4
repurposed drug
4
drug candidates
4
candidates tuberculosis
4
tuberculosis treatment
4
treatment progress
4

Similar Publications

Protozoan parasite infections, particularly leishmaniasis, present significant public health challenges in tropical and subtropical regions, affecting socio-economic status and growth. Despite advancements in immunology, effective vaccines remain vague, leaving drug treatments as the primary intervention. However, existing medications face limitations, such as toxicity and the rise of drug-resistant parasites.

View Article and Find Full Text PDF

Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strategy. In this study, we developed a virtual screening workflow that combines multiple machine learning and deep learning models, and 11 576 compounds extracted from the DrugBank database were screened against Mtb.

View Article and Find Full Text PDF

Background & objectives The emergence of drug resistance in leishmaniasis has remained a concern. Even new drugs have been found to be less effective within a few years of their use. Coupled with their related side effects and cost-effectiveness, this has prompted the search for alternative therapeutic options.

View Article and Find Full Text PDF

Targeting iron metabolism has emerged as a novel therapeutic strategy for the treatment of cancer. As such, iron chelator drugs are repurposed or specifically designed as anticancer agents. Two important chelators, deferasirox (Def) and triapine (Trp), attack the intracellular supply of iron (Fe) and inhibit Fe-dependent pathways responsible for cellular proliferation and metastasis.

View Article and Find Full Text PDF

Purpose: This study aimed to develop a solid self-nanoemulsifying drug delivery system (SNEDDS) and surface-coated microspheres to improve the oral bioavailability of niclosamide.

Methods: A solubility screening study showed that liquid SNEDDS, prepared using an optimized volume ratio of corn oil, Cremophor RH40, and Tween 80 (20:24:56), formed nanoemulsions with the smallest droplet size. Niclosamide was incorporated into this liquid SNEDDS and spray-dried with calcium silicate to produce solid SNEDDS.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!