Top news stories in 2019 on RxNet
In this article, we share a round-up of the top 10 news stories, you, our members, enjoyed reading this past year on RxNet, including some exciting advancements in drug discovery from 2019.
Before we enter 2020, and begin a new decade, we’re taking a look at some of the most exciting news stories we covered over the past year. From novel HIV therapies to antibiotics and machine learning, take a look at our round-up of the most read articles from 2019.
Functional inhibitors of ASM, typically used as an antidepressant, are being investigated to treat a range of intracellular bacterial diseases. Research suggests that this method has a lower risk of resistance developing. Not only is bacterial resistance a major issue in drug discovery and development, but infections that reside within the host cell are notoriously difficult to treat due to difficulties in transporting small molecules through the cell membrane to their target site.
Cannabidiol-based medical products are already approved in the US for the treatment of certain types of epilepsy. Earlier this year, researchers discovered that this non-psychoactive chemical compound is active against Gram-positive bacteria. Interestingly, previously research indicated that cannabidiol can kill bacteria but until this work, it had never been investigated as a fully-fledged antibiotic.
In this news story, we reported on research taking a novel approach to tackling antibiotic resistance. Instead of developing newer and hopefully more effective antibiotics, researchers have looked to a more long-term approach of stopping bacteria from evolving in the first place. Using already FDA-approved drugs, researchers inhibited the process that leads to drug-resistance mutations in bacteria—triggering the generation of high levels of reactive oxygen species.
For those living with Type 2 diabetes, they often have to rely on self-administration of daily injections of insulin to manage the condition. In February, we reported on a drug capsule, which contains a small needle that, after the capsule reaches the stomach, injects itself into the stomach wall and allows the insulin to be dissolved at a rate determine by the researchers during the preparation of the capsule.
Halichondrin is a proven potent anti-cancer agent that, although found naturally in sea sponges, is only found in tiny quantities. In a landmark development – researchers for the first time discovered a way to synthesize substantial quantities of E7130, a drug candidate from the halichondrin class. Synthesizing larger quantities of this compound will allow them to perform detailed studies on its biological activity, pharmacological properties and efficacy.
Applying the mathematical principle – random matrix theory – researchers have developed an algorithm that can be used to separate pharmacologically relevant patterns from irrelevant ones. This will aid researchers when predicting whether a molecular will activate a particular physiological process. It has already been used to identify new molecules that activate protein thought to be relevant for the symptoms of Alzheimer’s disease and schizophrenia.
A microfluidic-based drug screening chip was developed by researchers from Korea that allows for the comparison of critical pharmacological patterns – identifying synergistic interactions –between antibiotics. The device allows researchers to explore the combinatorial testing in the process of finding the antibiotic pairs that together work best against pathogens.
Drug repurposing was a major topic on RxNet in 2019. In this story, pantothenamide, which was originally developed as a psoriasis therapy, was discovered to have a similar structure to a naturally occurring molecule in malaria. Since the malaria parasite will use pantothenamide in the same way as it does the natural compound, the drug will be able to interfere with its metabolism – leading to its death.
This machine-learning algorithm boasts an accuracy of 90% when predicting the outcome of chemical reactions. Typically, trained human chemists only have an accuracy of 80%, hence this could help researchers reduce the time spent in preclinical work and allow for many to avoid the ‘trial-and-error’ nature of making molecules used today.
Building on the idea that 0.3% of patients with HIV can control the virus without antiretroviral therapy (ART), researchers identified genetic differences between this group and majority of other patients – for whom ART is crucial to their survival – that could provide new avenues of therapy development to complement ART.