Finding New Drugs Is Laborious. Potential Sciences, a startup backed by the UK government, is betting that training AI models on computer-generated biochemical data can speed up the plodding process of developing new drugs. Drug discovery is a needle in a haystack problem. This AI startup wants to simulate the haystack to speed the process up.Photo-Illustration: Jobanny Cabrera; Getty Images A new British startup believes that artificial intelligence is the key to speedrunning the slow and temperamental process of drug design. Potential Sciences plans to build large-scale chemical datasets by using basic principles of physics to simulate interactions between atoms, then small molecules, then complex amino acids and proteins.

Gift Ideas For Everyone On Your List Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable @Home In My Bag Safety Net Look Up Versus Trending Now Say More Creator Playbook Mashable Selects Getting Technical with Mashable All Series Where did life on Earth come from? Elisha Sauers writes about space for Mashable, taking deep dives into NASA's moon and Mars missions, chatting up astronauts and history-making discoverers, and jetting above the clouds . Through 17 years of reporting, she's covered a variety of topics, including health, business, and government, with a penchant for public records requests. She previously worked for in Norfolk, Virginia, and in Annapolis, Maryland. Her work has earned numerous state awards, including the Virginia Press Association's top honor, Best in Show, and national recognition for narrative storytelling.

Like scientists, AI models don't yet have the data to properly decode it. Researchers have only scratched the surface of the messy, three dimensional knots that influence how our genomes function.Courtesy of Quanta The original version of this story appeared in Quanta Magazine. Since its molecular structure was deduced in the 1950s, DNA has been hailed by many biologists as the secret of life. They've read and studied the information stored in the DNA found in the cells of living organisms, known as their genomes, and claimed that this genetic database must be some kind of blueprint, code script, or computer. But if DNA really does harbor some greater secret about how life works, biologists have yet to find it. In fact, the human genome is less a script than a puzzle that gets harder the closer they look. Knowing the entire sequence--the order of all 3 billion or so of our DNA's chemical building blocks, nearly fully deduced by the international Human Genome Project between 1990 and 2003--hasn't helped much. That investigation showed that barely 2 percent of the human genome consists of actual genes, the information-coding sequences of DNA.

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Bill Gates says we've passed AI's danger thresholds. In a new interview, the billionaire philanthropist sounds an alarm on the urgency of getting our AI policies in order. The temperature is in the mid-80s, and the sky is incapable of being any more blue. The view from the Gates Ventures conference room overlooks the Carillon Point Marina, where a flotilla of expensive boats bob in the water, and across the lake to the Olympic Mountains that define the horizon. Because if the scene is placid, the messenger is not. Seated across from me at a conference room table, Bill Gates is rocking back and forth in his chair, totally animated. And the more he has to say--about the threats of terror or economic collapse or just losing control of our AI systems--the more agitated I find myself becoming, too. The philanthropist and former Microsoft CEO says he has been growing increasingly alarmed by the rate of change at which AI technology is advancing, especially since guardrails are not keeping pace. In a new essay published today, Gates argues that we have passed the points where multiple potential dangers should have been checked. "We've crossed the threshold in terms of [AI's] bio-capabilities, cyber-capabilities, psychosocial capabilities, job-market-destruction capabilities, and even the lack of control," he said in an interview with about his new memo "I'm just stunned at the lack of concern and discussion outside of the industry." In an effort to wake the world up to what he sees as a rapidly growing societal disrupter, the 70-year-old tech titan has begun sounding the alarm as a "shrill voice," both publicly with his new essay (the first of multiple he plans on the topic) and in meetings with the press, and privately in conversations with industry, government, and civil society leaders. And while Gates is calling attention to a number of issues, his warnings about the bio-capabilities of the current frontier models are especially chilling. "Any model that can make novel molecules should be monitored," he says.

Trending Now Look Up Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Say More Mashable Selects Mashable Voices Safety Net Creator Hub Versus Gift Ideas For Everyone On Your List Switch Off In My Bag All Series This innovation could help address both pollution and hunger. But would you eat one? Amanda Yeo is an Assistant Editor at Mashable, covering entertainment, culture, tech, science, and social good. Based in Australia, she writes about everything from video games and K-pop to movies and gadgets. Scientists have transformed PET plastic into nutritious edible cookies, an innovation that could help address both pollution and hunger in one fell swoop.

Researchers found that a metabolite produced by gut bacteria can weaken the barrier that protects the brain and promote changes associated with the cognitive disease. For years, scientists have known that the gut microbiome of people with Alzheimer's differs from that of healthy people. What remains unclear is whether these differences are a consequence of the disease, contribute to it, or simply accompany it. It is possible that part of the puzzle lies not in the gut bacteria themselves but in the molecules they produce, which end up circulating throughout the body. A team of scientists believes it has found one such molecule.

As generative AI captures public attention, a different kind of AI is reshaping drug discovery. Machine learning models are helping to compress decade-long timelines and cracking problems that were previously unsolvable. Designing and developing a new medicine is an expensive, failure-prone scientific challenge. A new drug can take many years to develop, at the cost of a significant investment. And even then, most possible candidates never reach the patient. For biologic medicines, therapies made from engineered proteins rather than synthetic chemistry (which are often used to treat conditions across most major acute and chronic diseases), the complexity is even greater.

Check your subscription status, update your details and more. Drug development must change too. In this New Scientist CoLab podcast, experts from global life sciences leader Cytiva explain the hidden, high-stakes science of purification that is required to close the gap between drug discovery and the pharmacy shelf. Artificial intelligence and big data are flooding discovery pipelines with high-potential drug candidates, but this rapid innovation has created a new challenge. Simply put, our capability to design miracle molecules is vastly outstripping our technology to mass-manufacture them safely for the global public.

Similarly sweet molecules may have jumpstarted life on Earth over 4 billion years ago. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. The molecular cloud is located about 27,000 light-years from Earth. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .