{"id":8631,"date":"2023-12-25T11:55:31","date_gmt":"2023-12-25T11:55:31","guid":{"rendered":"https:\/\/dailyai.com\/?p=8631"},"modified":"2023-12-25T11:55:31","modified_gmt":"2023-12-25T11:55:31","slug":"mit-researchers-identify-new-class-of-antibiotics-using-ai","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/12\/mit-researchers-identify-new-class-of-antibiotics-using-ai\/","title":{"rendered":"MIT-forskere identificerer ny klasse af antibiotika ved hj\u00e6lp af AI"},"content":{"rendered":"

MIT-forskere brugte deep learning-modeller til at opdage den f\u00f8rste nye klasse af antibiotika i \u00e5rtier. De resulterende antibiotika kan vende str\u00f8mmen mod l\u00e6gemiddelresistente bakterier.<\/strong><\/p>\n

Da Alexander Fleming opdagede penicillin, verdens f\u00f8rste antibiotikum, var han klar over de farer, der var forbundet med det.<\/p>\n

I sin nobelpristale i 1945 sagde Fleming: \"S\u00e5 er der faren for, at den uvidende mand let kan underdosere sig selv og ved at uds\u00e6tte sine mikrober for ikke-d\u00f8delige m\u00e6ngder af stoffet g\u00f8re dem resistente.\"<\/p>\n

Efterh\u00e5nden som nyere antibiotika blev udviklet, f\u00f8rte misbrug og forkerte recepter til, at de bakterier, de var rettet mod, gradvist blev resistente over for disse tidligere effektive l\u00e6gemidler.<\/p>\n

Det team, som Dr. Jim Collins leder p\u00e5 Collins-laboratoriet<\/a> p\u00e5 MIT startede Antibiotics-AI Project tilbage i 2020 for at l\u00f8se dette problem. Projektet har en syv\u00e5rig plan om at udvikle syv nye klasser af antibiotika til behandling af syv af verdens mest d\u00f8dbringende bakterielle patogener.<\/p>\n

Deres indsats med maskinl\u00e6ring er begyndt at give pote, da deres papir<\/a> annoncerede deres opdagelse af en ny klasse af antibiotika, der kan dr\u00e6be methicillinresistente Staphylococcus aureus (MRSA)-bakterier. Medicinresistente MRSA-infektioner dr\u00e6ber op til 10.000 mennesker hvert \u00e5r alene i USA.<\/p>\n

Medicinalvirksomheder bruger ikke meget af deres forskning p\u00e5 antibiotika, fordi det ikke er s\u00e5 lukrativt som andre l\u00e6gemidler. Det er ogs\u00e5 blevet stadig sv\u00e6rere at opdage nye antibiotika. AI har lige gjort det meget nemmere.<\/p>\n

Modeller for dyb l\u00e6ring<\/h2>\n

Udfordringen med at skabe et nyt antibiotikum er, at der findes n\u00e6sten uendeligt mange molekyl\u00e6re arrangementer, og det er sv\u00e6rt at vide, hvilke af dem der vil dr\u00e6be en bestemt bakterie. For at g\u00f8re det endnu mere kompliceret skal forskerne sikre sig, at det nye stof heller ikke dr\u00e6ber sunde celler.<\/p>\n

MIT-teamet oprettede en database med 39.000 forskellige forbindelser og deres virkning p\u00e5 Staphylococcus aureus. De indarbejdede ogs\u00e5 stoffernes cytotoksicitet ved at spore deres virkning p\u00e5 lever-, skeletmuskel- og lungeceller fra mennesker.<\/p>\n

Oplysninger om forbindelsernes kemiske strukturer blev ogs\u00e5 f\u00f8jet til datas\u00e6ttet, som derefter blev brugt til at tr\u00e6ne en AI-model med dyb l\u00e6ring.<\/p>\n

Baseret p\u00e5 det store datas\u00e6t var modellen i stand til at l\u00e6re, hvilke kemiske strukturer der med st\u00f8rst sandsynlighed ville dr\u00e6be bakterierne og samtidig undg\u00e5 skadelige virkninger p\u00e5 sunde celler.<\/p>\n

Da AI-modellen var tr\u00e6net, blev den brugt til at screene 12 millioner kommercielt tilg\u00e6ngelige stoffer. Modellen identificerede molekyler fra fem forskellige klasser, som den forudsagde ville dr\u00e6be MRSA-bakterierne.<\/p>\n

Baseret p\u00e5 den betydeligt indsn\u00e6vrede liste over kandidatforbindelser fik forskerne 280 forbindelser til at teste mod MRSA-bakterier dyrket i en laboratoriesk\u00e5l. Deres tests f\u00f8rte til opdagelsen af, at to af stofferne reducerede MRSA med en faktor 10.<\/p>\n

Forklarlig AI<\/h2>\n

AI-modeller giver os ofte nyttige svar, men de kan v\u00e6re uigennemskuelige sorte bokse, der ikke giver os indsigt i, hvordan de n\u00e5r frem til svaret.<\/p>\n

Felix Wong, postdoc ved MIT og Harvard og en af unders\u00f8gelsens hovedforfattere sammen med Erica Zheng, sagde: \"Det, vi satte os for at g\u00f8re i denne unders\u00f8gelse, var at \u00e5bne den sorte boks. Disse modeller best\u00e5r af et meget stort antal beregninger, der efterligner neurale forbindelser, og ingen ved rigtig, hvad der foreg\u00e5r under motorhjelmen.\"<\/p>\n

At forst\u00e5, hvad der fik modellen til at v\u00e6lge de stoffer, den gjorde, ville give forskerne en bedre id\u00e9 om, hvor de skal lede efter mere effektive l\u00e6gemidler. Forskerholdet brugte en tilpasset Monte Carlo-tr\u00e6-s\u00f8gealgoritme til at f\u00e5 et indblik i deres deep learning-models beslutningsproces.<\/p>\n

Dr. Collins forklarede: \"Indsigten her var, at vi kunne se, hvad modellerne l\u00e6rte for at komme med deres forudsigelser om, at visse molekyler ville v\u00e6re gode antibiotika.\"<\/p>\n

Sammen med MIT havde forskningen ogs\u00e5 bidrag fra Broad Institute, Integrated Biosciences, Wyss Institute for Biologically Inspired Engineering og Leibniz Institute of Polymer Research i Dresden, Tyskland.<\/p>\n

Brug af AI til at gennemg\u00e5 millioner af potentielle kemiske arrangementer har en massiv indvirkning p\u00e5 opdagelse af l\u00e6gemidler<\/a>. For Collins Lab er det et tilf\u00e6lde af 'en nede, seks tilbage', og det ser ud til, at deres syv \u00e5r lange projekt kan have tid til overs.<\/p>","protected":false},"excerpt":{"rendered":"

MIT-forskere brugte deep learning-modeller til at opdage den f\u00f8rste nye klasse af antibiotika i \u00e5rtier. De resulterende antibiotika kan vende udviklingen mod medicinresistente bakterier. Da Alexander Fleming opdagede penicillin, verdens f\u00f8rste antibiotikum, var han klar over de dermed forbundne farer. I sin nobelpristale i 1945 sagde Fleming: \"S\u00e5 er der faren for, at den uvidende mand let kan underdosere sig selv og ved at uds\u00e6tte sine mikrober for ikke-d\u00f8delige m\u00e6ngder af stoffet g\u00f8re dem resistente.\" Efterh\u00e5nden som nyere antibiotika blev udviklet, f\u00f8rte misbrug og forkerte recepter til, at de bakterier, de var rettet mod, gradvist blev resistente over for disse tidligere antibiotika.<\/p>","protected":false},"author":6,"featured_media":8632,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[150,203,105],"class_list":["post-8631","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-benefits","tag-biotech","tag-machine-learning"],"yoast_head":"\nMIT researchers identify new class of antibiotics using AI | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/da\/2023\/12\/mit-researchers-identify-new-class-of-antibiotics-using-ai\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MIT researchers identify new class of antibiotics using AI | DailyAI\" \/>\n<meta property=\"og:description\" content=\"MIT researchers used deep learning models to discover the first new class of antibiotics in decades. The resulting antibiotics could turn the tide against drug-resistant bacteria. When Alexander Fleming discovered penicillin, the world\u2019s first antibiotic, he was aware of the associated dangers. In his Nobel Prize acceptance speech in 1945, Fleming said, \u201cThen there is the danger that the ignorant man may easily underdose himself and by exposing his microbes to non-lethal quantities of the drug, make them resistant.\u201d As newer antibiotics were developed, misuse and incorrect prescriptions led to the bacteria they targeted gradually becoming resistant to these previously\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/da\/2023\/12\/mit-researchers-identify-new-class-of-antibiotics-using-ai\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2023-12-25T11:55:31+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/Antimicrobial-susceptibility-resistance-test.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"526\" \/>\n\t<meta property=\"og:image:type\" 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