{"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\/fr\/2023\/12\/mit-researchers-identify-new-class-of-antibiotics-using-ai\/","title":{"rendered":"Des chercheurs du MIT identifient une nouvelle classe d'antibiotiques gr\u00e2ce \u00e0 l'IA"},"content":{"rendered":"

Des chercheurs du MIT ont utilis\u00e9 des mod\u00e8les d'apprentissage profond pour d\u00e9couvrir la premi\u00e8re nouvelle classe d'antibiotiques depuis des d\u00e9cennies. Les antibiotiques qui en r\u00e9sultent pourraient permettre de lutter contre les bact\u00e9ries r\u00e9sistantes aux m\u00e9dicaments.<\/strong><\/p>\n

Lorsque Alexander Fleming a d\u00e9couvert la p\u00e9nicilline, le premier antibiotique au monde, il \u00e9tait conscient des dangers qui y \u00e9taient associ\u00e9s.<\/p>\n

Dans son discours d'acceptation du prix Nobel en 1945, Fleming a d\u00e9clar\u00e9 : \"Ensuite, il y a le danger que l'homme ignorant puisse facilement se sous-doser et, en exposant ses microbes \u00e0 des quantit\u00e9s non mortelles du m\u00e9dicament, les rendre r\u00e9sistants\".<\/p>\n

Au fur et \u00e0 mesure de la mise au point de nouveaux antibiotiques, les bact\u00e9ries qu'ils ciblaient sont devenues progressivement r\u00e9sistantes \u00e0 ces m\u00e9dicaments auparavant efficaces, en raison d'une mauvaise utilisation et de prescriptions erron\u00e9es.<\/p>\n

L'\u00e9quipe que Jim Collins dirige \u00e0 la Le laboratoire Collins<\/a> au MIT a lanc\u00e9 le projet Antibiotics-AI en 2020 pour rem\u00e9dier \u00e0 ce probl\u00e8me. Ce projet, qui s'\u00e9tale sur sept ans, vise \u00e0 mettre au point sept nouvelles classes d'antibiotiques pour traiter sept des bact\u00e9ries pathog\u00e8nes les plus mortelles au monde.<\/p>\n

Leurs efforts en mati\u00e8re d'apprentissage automatique ont commenc\u00e9 \u00e0 porter leurs fruits. leur document<\/a> ont annonc\u00e9 leur d\u00e9couverte d'une nouvelle classe d'antibiotiques capables de tuer les bact\u00e9ries Staphylococcus aureus r\u00e9sistantes \u00e0 la m\u00e9thicilline (SARM). Les infections \u00e0 SARM r\u00e9sistantes aux m\u00e9dicaments tuent jusqu'\u00e0 10 000 personnes chaque ann\u00e9e rien qu'aux \u00c9tats-Unis.<\/p>\n

Les entreprises pharmaceutiques n'orientent pas beaucoup leurs recherches vers les antibiotiques, car ce secteur n'est pas aussi lucratif que d'autres m\u00e9dicaments. Il est \u00e9galement devenu de plus en plus difficile de d\u00e9couvrir de nouveaux antibiotiques. L'IA vient de rendre les choses beaucoup plus faciles.<\/p>\n

Mod\u00e8les d'apprentissage profond<\/h2>\n

Le d\u00e9fi que pose la cr\u00e9ation d'un nouvel antibiotique est qu'il existe une infinit\u00e9 d'arrangements mol\u00e9culaires et qu'il est difficile de savoir lequel d'entre eux tuera une bact\u00e9rie sp\u00e9cifique. Pour compliquer les choses, les chercheurs doivent s'assurer que le nouveau compos\u00e9 ne tue pas non plus les cellules saines.<\/p>\n

L'\u00e9quipe du MIT a cr\u00e9\u00e9 une base de donn\u00e9es de 39 000 compos\u00e9s diff\u00e9rents et de leurs effets sur le staphylocoque dor\u00e9. Ils ont \u00e9galement int\u00e9gr\u00e9 la cytotoxicit\u00e9 des compos\u00e9s en suivant les effets qu'ils ont sur les cellules humaines du foie, des muscles squelettiques et des poumons.<\/p>\n

Des informations sur les structures chimiques des compos\u00e9s ont \u00e9galement \u00e9t\u00e9 ajout\u00e9es \u00e0 l'ensemble de donn\u00e9es, qui a ensuite \u00e9t\u00e9 utilis\u00e9 pour former un mod\u00e8le d'apprentissage profond de l'IA.<\/p>\n

Sur la base du vaste ensemble de donn\u00e9es, le mod\u00e8le a \u00e9t\u00e9 en mesure d'apprendre quelles structures chimiques \u00e9taient les plus susceptibles de tuer les bact\u00e9ries tout en \u00e9vitant les effets n\u00e9fastes sur les cellules saines.<\/p>\n

Une fois form\u00e9, le mod\u00e8le d'IA a \u00e9t\u00e9 utilis\u00e9 pour passer au crible 12 millions de compos\u00e9s disponibles dans le commerce. Le mod\u00e8le a identifi\u00e9 des mol\u00e9cules de cinq classes diff\u00e9rentes qui, selon lui, tueraient la bact\u00e9rie MRSA.<\/p>\n

Sur la base de cette liste consid\u00e9rablement r\u00e9duite de compos\u00e9s candidats, les chercheurs ont obtenu 280 compos\u00e9s \u00e0 tester contre les bact\u00e9ries MRSA cultiv\u00e9es en laboratoire. Leurs tests ont permis de d\u00e9couvrir que deux des compos\u00e9s r\u00e9duisaient le SARM d'un facteur 10.<\/p>\n

L'IA explicable<\/h2>\n

Les mod\u00e8les d'IA nous donnent souvent des r\u00e9ponses utiles, mais ils peuvent \u00eatre des bo\u00eetes noires imp\u00e9n\u00e9trables, qui ne nous permettent pas de comprendre comment ils parviennent \u00e0 la r\u00e9ponse.<\/p>\n

Felix Wong, postdoc au MIT et \u00e0 Harvard et l'un des principaux auteurs de l'\u00e9tude avec Erica Zheng, a d\u00e9clar\u00e9 : \"Ce que nous avons voulu faire dans cette \u00e9tude, c'est ouvrir la bo\u00eete noire. Ces mod\u00e8les consistent en un tr\u00e8s grand nombre de calculs qui imitent les connexions neuronales, et personne ne sait vraiment ce qui se passe sous le capot\".<\/p>\n

Comprendre ce qui a conduit le mod\u00e8le \u00e0 s\u00e9lectionner les compos\u00e9s qu'il a choisis donnerait aux chercheurs une meilleure id\u00e9e de l'endroit o\u00f9 chercher des m\u00e9dicaments plus efficaces. L'\u00e9quipe de recherche a utilis\u00e9 un algorithme de recherche arborescente Monte Carlo adapt\u00e9 pour se faire une id\u00e9e du processus d\u00e9cisionnel de leur mod\u00e8le d'apprentissage profond.<\/p>\n

Le Dr Collins explique : \"L'id\u00e9e \u00e9tait de voir ce que les mod\u00e8les apprenaient pour pr\u00e9dire que certaines mol\u00e9cules feraient de bons antibiotiques\".<\/p>\n

Outre le MIT, la recherche a \u00e9galement b\u00e9n\u00e9fici\u00e9 de contributions du Broad Institute, d'Integrated Biosciences, du Wyss Institute for Biologically Inspired Engineering et du Leibniz Institute of Polymer Research de Dresde, en Allemagne.<\/p>\n

L'utilisation de l'IA pour passer au crible des millions d'arrangements chimiques potentiels a un impact massif sur les activit\u00e9s de l'UE. d\u00e9couverte de m\u00e9dicaments<\/a>. Pour le laboratoire Collins, il s'agit d'un cas de \"un de moins, six de plus\" et il semble que leur projet de sept ans puisse avoir du temps \u00e0 perdre.<\/p>","protected":false},"excerpt":{"rendered":"

Des chercheurs du MIT ont utilis\u00e9 des mod\u00e8les d'apprentissage profond pour d\u00e9couvrir la premi\u00e8re nouvelle classe d'antibiotiques depuis des d\u00e9cennies. Les antibiotiques qui en r\u00e9sultent pourraient permettre de lutter contre les bact\u00e9ries r\u00e9sistantes aux m\u00e9dicaments. Lorsque Alexander Fleming a d\u00e9couvert la p\u00e9nicilline, le premier antibiotique au monde, il \u00e9tait conscient des dangers associ\u00e9s. Dans son discours d'acceptation du prix Nobel en 1945, Fleming a d\u00e9clar\u00e9 : \"Ensuite, il y a le danger que l'homme ignorant puisse facilement se donner une dose insuffisante et, en exposant ses microbes \u00e0 des quantit\u00e9s non l\u00e9tales du m\u00e9dicament, les rendre r\u00e9sistants\". Au fur et \u00e0 mesure de la mise au point de nouveaux antibiotiques, l'utilisation abusive et les prescriptions incorrectes ont conduit les bact\u00e9ries vis\u00e9es \u00e0 devenir progressivement r\u00e9sistantes \u00e0 ces nouveaux m\u00e9dicaments.<\/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\/fr\/2023\/12\/mit-researchers-identify-new-class-of-antibiotics-using-ai\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\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\/fr\/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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