The FDA has cleared the first Alzheimer's blood test for symptomatic patients as young as 40. The test measures amyloid and tau biomarkers from a single blood draw and identified positive biomarkers with 97.6% accuracy in a validation study. New Atlas reports: PrecivityAD2 is a single blood test that quickly assesses the proteins amyloid and tau, using mass spectrometry to measure plasma AB42/40 and p-tau217/np-tau217. The results are then scored, qualifying as negative, likely positive, or positive for AD. "Just over a year ago, there were no FDA-cleared blood tests for Alzheimer's, and now we have three," Isobel Coleman, chief executive officer of the Alzheimer's Drug Discovery Foundation (ADDF), said in a statement. "This is a proof point that sustained, early investment in translational science plays a catalytic role in moving promising ideas from the lab to patients." In a recent clinical validation study, 1,142 symptomatic adults were tested using PrecivityAD2. The process accurately identified 97.6% of positive biomarkers. What's more, the results remained consistent even in patients with comorbidities like chronic kidney disease and diabetes, which can distort plasma amyloid samples. It's worth noting that the test isn't intended for general health screenings, but for patients who already show some cognitive decline. "As PrecivityAD2 and tools like it move further into clinical practice, they will enable earlier detection, sharpen clinical trials, and build the foundation for precision medicine and combination therapies," Coleman added.

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An anonymous reader quotes a report from The Guardian: Scientists have made the first viruses designed by artificial intelligence in a milestone that raises hopes for new medicines but also concerns over how to ensure the technology remains safe. The viruses are specific kinds known as bacteriophages, which only infect bacteria and are used around the world to treat patients with persistent infections. In lab tests, a cocktail of the AI-designed viruses killed E coli bugs that were resistant to natural bacteriophages. Dr Brian Hie, a chemical engineer at Stanford University in California, used genome language models, the genetic equivalent of the large language models behind AI chatbots, to design functioning genomes for bacteriophages. The viruses were then made in the laboratory and pitted against E coli in a dish. The ability to "rapidly design" genomes and tune them for specific bugs while overcoming resistance could "transform phage therapy" and "expand biotechnological toolkits," the researchers wrote in the journal Science. But beyond the potential benefits, the scientists said the work raised "important biosafety, biocontainment and biosecurity considerations" and urged others who were designing whole genomes to "consult both safety and security professionals throughout the project." In an accompanying article, Prof Tom Inglesby and Dr Moritz Hanke at the Center for Health Security at Johns Hopkins University in Baltimore, reinforced the warning, writing: "Although this is promising for life sciences applications, it also raises urgent biosafety and biosecurity questions. The ability to compose viral genomes using generative AI now exists; the governance to safely steer it does not." Tom Ellis, a professor of synthetic genome engineering at Imperial College London, said the work was impressive, but revealed how hard it would be to make more complex genomes. "This is literally the smallest and easiest genome to make," he said. An AI trained on the genetic code of dangerous bugs could be used to design more harmful viruses, Ellis said, but controlling access to genetic data and having restrictions on making genomes that look dangerous would help. "Governments are working hard to do this already," he added. "But honestly," he said, "the threat from full AI design and writing of a genome of a virus or bacteria is very overblown when we consider that just taking existing pathogens and making gain-of-function changes to their genomes is so much easier and much more likely to be a real pathogenic threat." Dr Filippa Lentzos, a reader in science and international security at King's College London, said the most important point to intervene at the moment was when DNA was being manufactured. "It's important to see the bigger governance picture and not focus regulation solely on the AI model," she said. "A layered approach makes more sense: safeguards around model development and access, responsible research review, synthesis screening, and established laboratory biosafety and biosecurity."

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The FDA has approved the first mRNA flu vaccine in the United States after a clinical trial found it was about 27% more effective than a standard flu shot. Manufactured by Moderna and marketed as mFlusiva, the vaccine is expected to be available this fall for adults ages 50 to 64 and those 65 and older, though approval for the older group is conditional on Moderna conducting an additional clinical trial, NBC News reports. From the report: Many scientists and public health experts have touted the idea of an mRNA-based flu vaccine, which uses the same messenger RNA platform as the Covid vaccines from Moderna and Pfizer. That's because mRNA vaccines can be manufactured much faster than traditional vaccines, allowing scientists to better match circulating influenza strains. Moderna said it takes two to three months from picking the strain to rolling out its flu shot, compared with about six months for traditional flu shots.

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