Research questions effectiveness of MS medications in slowing disability progression

The medication, called daraxonrasib, is the first drug that targets cancer-causing mutations in pancreas cells. The drug targets a mutation in the KRAS gene, part of the RAS genetic family. KRAS mutations are present in 92% of pancreatic cancers. KRAS genes normally act as an "on-off" switch for cell growth. Mutated KRAS genes are stuck in the "on" position and send out a signal that causes cells to divide and grow uncontrollably, allowing cancer to form. Daraxonrasib blocks the KRAS signal by fitting into a keyhole-type spot on the gene. That spot has a complex shape and is difficult to reach within the cell. The drug gets around this problem by using a "passenger protein" as a Trojan horse. When the cell allows this protein in, daraxonrasib tags along.

Uncertainty and model limitations are critical in safety assessment. There is clearly greater potential for animal or human harm from an incorrect safety assessment than from making the wrong molecule in early discovery, although uncertainty matters in both contexts. It is important to distinguish different types of uncertainty. Aleatoric uncertainty reflects irreducible randomness in a task, while epistemic uncertainty is model-related, such as hallucinations or lack of knowledge. For LLM systems, we use multiple methods to measure consistency and we have built fact-checking approaches in which a separate LLM independently verifies the primary engine's outputs. For QSAR models, including our SAR work around seizure liability, we can use statistical metrics such as confidence intervals to quantify and communicate uncertainty. Understanding that uncertainty exists and communicating it in both safety and discovery is critical. Uncertainty metrics tell us where potential blind spots may exist in our modelling allowing us to take action to improve over time. This applies to both safety and discovery. The aim is not to pretend AI removes uncertainty, but to make uncertainty visible so scientists can make better-informed decisions. Download the Full PDF to Revisit James McDonagh's Insights on AI in Drug Safety Discovery

I think we're only just scratching the surface at the moment. I think over the next couple of years, we'll start to see some major strides. Obviously, showing the effects on target identification takes some time with new molecules but, certainly, the repositioning effects should be seen in a few years. I think there is great promise in terms of being able to really tap into a much broader chemical space, so we can have a much wider and more varied chemical palette to be able to pick the best molecules for drug discovery from. Also, accelerating the ways in which we can look at the data and glean much more information from it can help us both in terms of patient selection for clinical trials and in terms of being able to pick up signals of efficacy and safety much earlier.

Algae are photosynthetic aquatic creatures that grow through the consumption of nutrients, light, and carbon dioxide. They are a diverse group of creatures that include tiny single-celled algae and enormous kelp, as well as seaweed 1. Numerous prokaryotic and eukaryotic algae species are desirable food sources for humans due to their inherent qualities 2,3. Human intake of macroalgae such as seaweed and microalgae like phytoplankton dates back many years. Multicellular macroscopic aquatic plants, or macroalgae, are classified into three taxa: Phaeophyceae, or brown algae, Rhodophyta or red algae, and Chlorophyta or green algae. Microalgae, the unicellular counterpart of macroalgae, are categorized in a broader framework that includes prokaryotic cyanobacteria (blue-green algae), Euglenophyta, and Chlorophyta, which are genetically distinct from one another. The ancient populations of Chad and the Aztec culture were already familiar with the cyanobacteria spirulina, which is currently advertised as a superfood in the West 4. In Burma, Vietnam, and India, other cyanobacteria/microalgae, like Spirogyra and Oedogonium, were eaten as food or as a supplement 4. Seaweed is a staple of daily meals in many Asian and Pacific civilizations, including Korea, Japan, and Indonesia, as well as Hawaii and New Zealand 5.

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.