Google DeepMind spinoff Isomorphic Labs expects testing on its first AI-designed drugs to begin this year, as tech startups race to turn algorithmic magic into actual treatments.<\/span><\/p>\n \u201cWe\u2019ll hopefully have some AI-designed drugs in clinical trials by the end of the year,\u201d <\/span>the firm\u2019s Nobel Prize-winning CEO <\/span>Demis Hassabis <\/span>told<\/span><\/a> a panel at the World Economic Forum in Davos this week. <\/span>\u201cThat\u2019s the plan.\u201d\u00a0\u00a0<\/span><\/p>\n The potential of AI-powered drug discovery is huge. Instead of spending years or even decades testing chemicals by hand, machine learning algorithms can sift through mountains of data to spot patterns and predict which molecules could make the next miracle drug. This could lead to faster drug development, cheaper costs, and new cures.<\/span><\/p>\n By one <\/span>estimate<\/span><\/a>, there are over 460 AI startups currently working on drug discovery, of which <\/span>over a quarter<\/span><\/a> come from Europe. Globally, more than $60bn has been invested into the space so far, and the funding flood isn\u2019t showing any signs of <\/span>letting up<\/span><\/a>.\u00a0<\/span><\/p>\n Yet discovering the drugs is merely one step in the process. <\/span>it\u2019s only when big pharma decides they\u2019re worth manufacturing, marketing, and distributing that it\u2019ll make a real difference to the likes of you and me.\u00a0<\/span><\/p>\n The next big thing? It might be you\u2026<\/p>\n TNW Conference is here to support startups & scaleups to become the next big thing. Be part of the journey. Price increase on Friday.<\/p>\n<\/div>\n<\/div>\n That\u2019s what makes some of the recent hookups between pharma behemoths and AI startups particularly exciting.<\/span><\/p>\n Last year, Isomorphic Labs <\/span>inked a $45mn <\/span>deal<\/span><\/a> with Eli Lilly to collaborate on AI-based research into small molecule therapeutics. Under the agreement, Isomorphic is also eligible to receive up to $1.7bn in \u201cperformance-based milestones.\u201d The company also signed a similar <\/span>collaboration<\/span><\/a> with Swiss biotech Novartis.<\/span><\/p>\n \u201cWe\u2019re already working on real drug programs,\u201d Hassabis told Bloomberg Television in an <\/span>interview<\/span><\/a> shortly following the announcements. \u201cI would expect in the next couple of years the first AI-designed drugs in the clinic.\u201d<\/span><\/p>\n Exscientia, which spun out from Dundee University in 2012, was among the first to app<\/a>ly AI to drug discovery. In 2024, the company advanced its first AI-designed drug candidate into human clinical trials, achieving this milestone in just 12 months \u2014 a process that typically takes around five years. <\/span>US rival Recursion acquired <\/span>the Oxford-based company for $688mn in November.\u00a0<\/span><\/p>\n These are two big examples of an AI-driven drug discovery market that\u2019s booming, and increasingly, consolidating. However, there are also plenty of early-stage companies working on more niche applications of the technology<\/a>. These include Cambridge, UK-based CardiaTec, which is using AI to find new drugs to <\/span>treat heart conditions<\/span>, and London-headquartered <\/span>Multiomic Health, which is working on formulas to treat metabolic diseases.\u00a0<\/span><\/p>\n Despite all the potential though, AI isn\u2019t a silver bullet for drug discovery. While it can drastically speed up finding the right compounds needed to make new drugs, the most time-consuming steps \u2014 like wet lab tests with physical samples, clinical trials, and FDA approvals \u2014 aren\u2019t going anywhere. Still, AI\u2019s real power lies in that critical first phase: zeroing in on targets that might\u2019ve otherwise slipped through the cracks, saving researchers time and possibly even unlocking new treatments. <\/span><\/p>\n<\/p><\/div>\n If you liked the article, do not forget to share it with your friends. Follow us on\u00a0Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n If you want to read more like this article, you can visit our Technology category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n\n
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