Drug-resistant SARS-CoV-2 variants found in immunocompromised patients

With the current drug discovery paradigm, it takes up to 15 years to translate an idea, such as hypothesizing a certain protein is important in a disease and testing this with targeting the protein with a drug, all the way through to proof of concept. The drug has to be filed with the regulatory authorities, having done all the safety and efficacy testing. It's a long process and it's also very costly. Estimates vary, but it's currently reckoned to cost over 1 billion dollars per drug. That’s partly because you have to pay for all the drugs that didn't make it. By the time you've taken a protein target and you've made a whole load of molecules that affect that target in the way you want them to, you've probably already spent a couple of years on it and then you have to take the best molecule through the appropriate safety testing in animals before proceeding to phase 1 testing in people. Even if you get to phase 1 testing, where you are just giving it to human volunteers for the first time, not even patients, about 95% of the compounds at the stage then fail to make it all the way through to the market. So, you’ve only got a 5% success rate. The odds are not good and, essentially, it is why so many companies have had to merge because, over time, this is becoming less and less sustainable as a business model.

AI is moving so quickly that in the gap between answering this and publication, I could be proved wrong! With that caveat, there is a lot of hype around AI drug discovery campaigns. AI is certainly a substantial part of many discovery programs today and has been applied in drug discovery for many years. However, we need to be realistic about what AI is doing, where humans remain central, and how that balance may vary. AI agents are an area that has emerged relatively recently and continues to evolve quickly. They can complete tasks for example data extraction and reporting with guidance from experts, helping to generate larger, more standardized datasets over time. They can also help build closed-loop systems that connect computation and experiment directly, with strategic direction still coming from expert scientists. However, care and oversight is needed with these systems to validate their actions. I also think people often equate AI with generative AI, but there are many other AI systems which are underappreciated. For example, the GNN property prediction models and task-specific predictive tools we discussed earlier can be extremely valuable. Some of these methods receive less attention simply because they have already become familiar in drug discovery.

We are now testing the drug in patients with earlier-stage pancreatic cancer, prescribing it while their tumors are still operable and before their cancer spreads.

More specifically, the study showed that the female patient produced very few cathelicidins, which is a natural toxin found in the immune cells of the lungs needed to fight tuberculosis. In most people infected by tuberculosis, tuberculosis bacteria attack the immune cells of the lungs. The immune cells fight the bacteria by eating them. But the tuberculosis bacterium has developed various evasive mechanisms that reduce the immune cells’ ability to digest and thus to kill the Mtb. “You could say that the tuberculosis bacterium has developed a way to lull the immune cells to sleep. This enables the disease the hide inside the immune cells, making it invisible to other parts of the immune system,” Martin Kongsbak-Wismann explains. This is where vitamin D enters the picture. Because vitamin D is able to counteract the soporific effect of the tuberculosis bacteria by making the immune cells produce more of the cathelicidin toxin. “Cathelicidin is like a microscopic needle that is able to pierce the tuberculosis bacteria. And when it does, it weakens the bacteria’s soporific effect on the immune cells. This restores the immune cells’ ability to kill tuberculosis bacteria,” says Martin Kongsbak-Wismann and adds: “We were amazed by the effect of vitamin D. In immune cells from healthy control subjects, vitamin D improved the cells’ ability to fight Mtb, whereas in the female patient’s immune cells we saw no response to vitamin D. This shows that vitamin D is key to the immune system’s ability to fight Mtb and prevent tuberculosis.” Al-Jaberi, F.A.H., et al. (2022) Reduced vitamin D-induced cathelicidin production and killing of Mycobacterium tuberculosis in macrophages from a patient with a non-functional vitamin D receptor: A case report. Frontiers in Immunology. doi.org/10.3389/fimmu.2022.1038960.

The bulk of vitamins and supplements containing fish oil, biotin, and vitamins A, C, and E can potentially promote nail and hair growth. You can find dietary supplements with higher concentrations of vitamins and minerals that aid skin, hair, and nail health. Fish oil supplements make nails and hair shiny. Fish oil also serves as an agent that can decrease signs of aging. If sun exposure damages the skin, the omega-3 fatty acids in fish oil can help. Biotin, also known as B7, increases hair density and strengthens it. It is found naturally in bananas, eggs, and milk. Vitamins are vital for skin health as well. Vitamin A reduces acne flairs and helps with changes due to aging like wrinkling. A vitamin A deficiency may increase the risk of acne because it becomes difficult for dead skin to slough off hair follicles, blocking pores. Vitamin B lowers the risk of precancerous growths and nonmelanoma skin cancer. Vitamin C is an antioxidant. It leads the fight against free radicals to help stimulate collagen and brighten skin. It also helps to prevent the formation of unneeded melanin that causes uneven skin pigmentation.