{"id":11639,"date":"2024-04-17T11:21:32","date_gmt":"2024-04-17T11:21:32","guid":{"rendered":"https:\/\/dailyai.com\/?p=11639"},"modified":"2024-04-17T12:42:25","modified_gmt":"2024-04-17T12:42:25","slug":"scientists-accelerate-search-for-parkinsons-treatments-using-ai","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2024\/04\/scientists-accelerate-search-for-parkinsons-treatments-using-ai\/","title":{"rendered":"Cientistas aceleram a procura de tratamentos para a doen\u00e7a de Parkinson utilizando a IA"},"content":{"rendered":"

Os investigadores da Universidade de Cambridge utilizaram a IA para acelerar drasticamente a procura de novas terapias para a doen\u00e7a de Parkinson.\u00a0<\/b><\/p>\n

Utilizando t\u00e9cnicas de aprendizagem autom\u00e1tica, conseguiram analisar milh\u00f5es de potenciais compostos de medicamentos e identificar os candidatos mais promissores dez vezes mais depressa e com uma rela\u00e7\u00e3o custo-benef\u00edcio 1000 vezes superior \u00e0 dos m\u00e9todos convencionais.<\/span><\/p>\n

A doen\u00e7a de Parkinson \u00e9 uma doen\u00e7a neurodegenerativa complexa e progressiva que afecta cerca de 6 milh\u00f5es de pessoas em todo o mundo. Prev\u00ea-se que este n\u00famero triplique at\u00e9 2040. <\/span><\/p>\n

Atualmente, nenhum tratamento pode retardar ou parar a progress\u00e3o da doen\u00e7a de forma fi\u00e1vel.\u00a0<\/span><\/p>\n

O processo tradicional de sele\u00e7\u00e3o de vastas bibliotecas de produtos qu\u00edmicos para encontrar potenciais candidatos a medicamentos \u00e9 extremamente lento, dispendioso e muitas vezes infrut\u00edfero.<\/span><\/p>\n

\"Uma via para procurar potenciais tratamentos para a doen\u00e7a de Parkinson requer a identifica\u00e7\u00e3o de pequenas mol\u00e9culas que possam inibir a agrega\u00e7\u00e3o da alfa-sinucle\u00edna, que \u00e9 uma prote\u00edna estreitamente associada \u00e0 doen\u00e7a\", afirmou a investigadora principal, a Professora Michele Vendruscolo <\/span>disse \u00e0 Universidade de Cambridge.<\/span><\/a><\/p>\n

\"Mas este \u00e9 um processo extremamente moroso - a simples identifica\u00e7\u00e3o de um candidato principal para testes adicionais pode levar meses ou mesmo anos\".<\/span><\/p>\n

Para enfrentar este desafio, Vendruscolo e a sua equipa desenvolveram uma abordagem de aprendizagem autom\u00e1tica em 5 etapas. Os <\/span>estudo<\/span><\/a> foi publicado em Natureza Biologia Qu\u00edmica<\/em>.\u00a0<\/span><\/p>\n

    \n
  1. Comece com um pequeno conjunto de compostos, identificados atrav\u00e9s de simula\u00e7\u00f5es, que mostram potencial para bloquear a aglutina\u00e7\u00e3o da prote\u00edna alfa-sinucle\u00edna, que \u00e9 a principal causa da doen\u00e7a de Parkinson. Depois, testar experimentalmente a sua efic\u00e1cia.<\/span><\/li>\n
  2. Utilize os resultados para treinar um modelo de aprendizagem autom\u00e1tica para prever quais as estruturas e propriedades moleculares que tornam um composto eficaz na preven\u00e7\u00e3o da agrega\u00e7\u00e3o de prote\u00ednas.<\/span><\/li>\n
  3. Implementar o modelo treinado para analisar rapidamente uma biblioteca virtual com milh\u00f5es de compostos e prever os concorrentes mais potentes.<\/span><\/li>\n
  4. Validar experimentalmente os principais candidatos seleccionados pela IA no laborat\u00f3rio. Introduzir estes resultados no modelo para aperfei\u00e7oar ainda mais as suas capacidades de previs\u00e3o.<\/span><\/li>\n
  5. Repetir este ciclo de previs\u00e3o computacional e testes experimentais, com o modelo de IA a tornar-se mais inteligente em cada ronda, concentrando-se nos compostos mais potentes.<\/span><\/li>\n<\/ol>\n
    \"AI
    O sistema iterativo de descoberta de medicamentos para a doen\u00e7a de Parkinson da Universidade de Cambridge. Fonte: Natureza Biologia Qu\u00edmica<\/a> (acesso livre)<\/figcaption><\/figure>\n

    Ao longo de v\u00e1rias itera\u00e7\u00f5es, a taxa de otimiza\u00e7\u00e3o - a percentagem de compostos testados que inibiram a aglutina\u00e7\u00e3o de alfa-sinucle\u00edna associada \u00e0 doen\u00e7a de Parkinson - aumentou de 4% para mais de 20%.\u00a0<\/span><\/p>\n

    Al\u00e9m disso, os compostos encontrados pela IA eram, em m\u00e9dia, muito mais potentes do que qualquer outro anteriormente identificado. Alguns mostraram uma atividade promissora em doses oito vezes inferiores. Eram tamb\u00e9m mais diversificados do ponto de vista qu\u00edmico, tendo o modelo descoberto compostos eficazes que diferiam das estruturas conhecidas.<\/span><\/p>\n

    \"A aprendizagem autom\u00e1tica est\u00e1 a ter um impacto real na descoberta de medicamentos - est\u00e1 a acelerar todo o processo de identifica\u00e7\u00e3o dos candidatos mais promissores\", afirmou Vendruscolo. <\/span><\/p>\n

    \"Utilizando os conhecimentos que adquirimos no rastreio inicial com o nosso modelo de aprendizagem autom\u00e1tica, conseguimos treinar o modelo para identificar as regi\u00f5es espec\u00edficas destas pequenas mol\u00e9culas respons\u00e1veis pela liga\u00e7\u00e3o, para podermos voltar a rastrear e encontrar mol\u00e9culas mais potentes\".<\/span><\/p>\n

    \"Para n\u00f3s, isto significa que podemos come\u00e7ar a trabalhar em v\u00e1rios programas de descoberta de medicamentos - em vez de apenas um. Muito \u00e9 poss\u00edvel devido \u00e0 enorme redu\u00e7\u00e3o de tempo e custo - \u00e9 um momento emocionante.\"<\/span><\/p>\n

    Os investigadores sublinham que isto \u00e9 apenas o in\u00edcio do que as abordagens baseadas na IA poder\u00e3o permitir na descoberta de medicamentos para a doen\u00e7a de Parkinson e outras doen\u00e7as caracterizadas pelo desdobramento e agrega\u00e7\u00e3o de prote\u00ednas.\u00a0<\/span><\/p>\n

    Com um maior desenvolvimento e conjuntos de dados de treino mais alargados, a capacidade de previs\u00e3o destes modelos s\u00f3 dever\u00e1 melhorar.<\/span><\/p>\n

    Embora ainda exista um longo caminho a percorrer para transformar estes candidatos identificados pela IA em tratamentos aprovados, este estudo demonstra como a aprendizagem autom\u00e1tica, inteligentemente combinada com a biologia experimental, pode acelerar consideravelmente as fases iniciais da descoberta de medicamentos.<\/span><\/p>\n

    Esta iniciativa baseia-se numa s\u00e9rie de investiga\u00e7\u00f5es que abordam o desafio de localizar tratamentos medicamentosos novos e inovadores, incluindo <\/span>do MIT e da Tufts<\/span><\/a>que construiu recentemente um modelo capaz de analisar diariamente cerca de 100 milh\u00f5es de compostos. <\/span><\/p>\n

    V\u00e1rios <\/span>modelos de descoberta de antibi\u00f3ticos<\/span><\/a> produziram compostos experimentais, alguns dos quais s\u00e3o rumo aos ensaios cl\u00ednicos<\/a>.<\/span><\/p>\n

    Outro <\/span>projeto de grande envergadura<\/span><\/a> em colabora\u00e7\u00e3o com o Moorfields Eye Hospital, no Reino Unido, utilizou, no ano passado, exames oftalmol\u00f3gicos para identificar os primeiros sinais da doen\u00e7a de Parkinson - um m\u00e9todo inovador possibilitado pela IA.\u00a0<\/span><\/p>\n

    Com este novo estudo que tem como objetivo descobrir tratamentos eficazes para a doen\u00e7a de Parkinson, os m\u00e9todos de IA revelam-se imensamente promissores na redefini\u00e7\u00e3o da medicina e dos cuidados de sa\u00fade.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Os investigadores da Universidade de Cambridge utilizaram a IA para acelerar drasticamente a procura de novas terapias para a doen\u00e7a de Parkinson. Utilizando t\u00e9cnicas de aprendizagem autom\u00e1tica, conseguiram analisar milh\u00f5es de potenciais compostos de medicamentos e identificar os candidatos mais promissores dez vezes mais depressa e com uma rela\u00e7\u00e3o custo-efic\u00e1cia 1000 vezes superior \u00e0 dos m\u00e9todos convencionais. A doen\u00e7a de Parkinson \u00e9 uma doen\u00e7a neurodegenerativa complexa e progressiva que afecta cerca de 6 milh\u00f5es de pessoas em todo o mundo. Prev\u00ea-se que este n\u00famero triplique at\u00e9 2040. Atualmente, nenhum tratamento pode retardar ou parar a progress\u00e3o da doen\u00e7a de forma fi\u00e1vel. O processo tradicional de sele\u00e7\u00e3o de vastas bibliotecas qu\u00edmicas para encontrar potenciais candidatos a medicamentos \u00e9 extremamente<\/p>","protected":false},"author":2,"featured_media":11641,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[204,178],"class_list":["post-11639","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-healthcare","tag-medicine"],"yoast_head":"\nScientists accelerate the search for Parkinson's treatments 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\/pt\/2024\/04\/scientists-accelerate-search-for-parkinsons-treatments-using-ai\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Scientists accelerate the search for Parkinson's treatments using AI | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers at the University of Cambridge have harnessed AI to dramatically accelerate the search for new Parkinson’s disease therapies.\u00a0 By using machine learning techniques, they were able to screen millions of potential drug compounds and identify the most promising candidates ten times faster and 1000 times more cost-effectively than conventional methods. Parkinson’s disease is a complex, progressive neurodegenerative disease that afflicts approximately 6 million people worldwide. That figure is expected to triple by 2040. 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