{"id":14258,"date":"2024-09-17T20:09:29","date_gmt":"2024-09-17T20:09:29","guid":{"rendered":"https:\/\/dailyai.com\/?p=14258"},"modified":"2024-09-18T08:42:03","modified_gmt":"2024-09-18T08:42:03","slug":"ai-accelerates-the-discovery-of-cryoprotectant-compounds-for-medicine-transport-and-storage","status":"publish","type":"post","link":"https:\/\/dailyai.com\/it\/2024\/09\/ai-accelerates-the-discovery-of-cryoprotectant-compounds-for-medicine-transport-and-storage\/","title":{"rendered":"L'intelligenza artificiale accelera la scoperta di composti crioprotettori per il trasporto e la conservazione dei farmaci"},"content":{"rendered":"

Gli scienziati hanno sviluppato un nuovo sistema di apprendimento automatico che potrebbe aiutare a conservare vaccini, sangue e altri trattamenti medici.\u00a0<\/b><\/p>\n

Il <\/span>ricerca<\/span><\/a>pubblicato su Nature Communications, \u00e8 stato condotto dall'Universit\u00e0 di Warwick e dall'Universit\u00e0 di Manchester.<\/span><\/p>\n

Il sistema di intelligenza artificiale aiuta a identificare le molecole chiamate crioprotettori - composti che prevengono i danni durante il congelamento dei materiali biologici.\u00a0<\/span><\/p>\n

I crioprotettori sono sostanze speciali che aiutano a proteggere le cellule e i tessuti viventi da eventuali danni quando vengono congelati.<\/p>\n

Agiscono prevenendo la formazione di dannosi cristalli di ghiaccio, che essenzialmente rompono i tessuti quando li si congela, e aiutano le cellule a mantenere la loro struttura in condizioni di freddo estremo.<\/p>\n

Questi composti sono di fondamentale importanza per la conservazione di oggetti come vaccini, campioni di sangue e cellule riproduttive per lo stoccaggio o il trasporto a lungo termine.<\/p>\n

I criopresevatori potrebbero un giorno essere utilizzati per conservare organi, tessuti complessi o addirittura interi esseri umani.<\/p>\n

Attualmente, la ricerca di nuovi crioprotettori \u00e8 un processo lento, basato su tentativi ed errori. Questo nuovo approccio guidato da ML consente ai ricercatori di vagliare rapidamente e virtualmente centinaia di potenziali molecole.<\/span><\/p>\n

Ecco alcuni punti chiave dello studio:<\/span><\/p>\n

    \n
  1. Il team ha creato un modello di apprendimento automatico addestrato sui dati dei crioprotettori esistenti.<\/span><\/li>\n
  2. Questo modello \u00e8 in grado di prevedere l'efficacia delle nuove molecole come crioprotettori.<\/span><\/li>\n
  3. I ricercatori hanno utilizzato il modello per esaminare una libreria di circa 500 aminoacidi.<\/span><\/li>\n
  4. Il sistema ha identificato diversi composti promettenti, tra cui un estere di aminooxazolo che ha superato molti crioprotettori noti.<\/li>\n
  5. I test di laboratorio hanno confermato le previsioni dell'intelligenza artificiale: il nuovo composto ha mostrato una forte prevenzione dei cristalli di ghiaccio.<\/span><\/li>\n
  6. La molecola scoperta ha migliorato la conservazione dei globuli rossi quando \u00e8 stata combinata con le tecniche standard.<\/span><\/li>\n<\/ol>\n

    L'estere amino-ossazolico identificato dallo studio ha dimostrato qualit\u00e0 particolarmente notevoli di inibizione della ricristallizzazione del ghiaccio (IRI). Ha impedito quasi completamente ai cristalli di ghiaccio di ingrandirsi durante il processo di congelamento.<\/p>\n

    Il composto \u00e8 rimasto efficace anche quando i ricercatori ne hanno abbassato la concentrazione. Inoltre, ha mantenuto le sue propriet\u00e0 di inibizione del ghiaccio anche nella soluzione salina tamponata con fosfati (PBS), una soluzione che riproduce la concentrazione di sale nel corpo umano.<\/p>\n

    Il dottor Matt Warren, il dottorando che ha guidato il progetto, ha descritto come il modello acceleri l'efficienza: \"Dopo anni di raccolta di dati ad alta intensit\u00e0 di lavoro in laboratorio, \u00e8 incredibilmente eccitante avere ora un modello di apprendimento automatico che consente un approccio guidato dai dati per prevedere l'attivit\u00e0 crioprotettiva\".<\/span><\/p>\n

    Il professor Matthew Gibson di Manchester ha aggiunto: \"I risultati del modello computerizzato sono stati sorprendenti e hanno identificato molecole attive che non avrei mai scelto, nemmeno con i miei anni di esperienza\".<\/span><\/p>\n

    Il professor Gabriele Sosso, che ha guidato il team di Warwick, <\/span>ha spiegato in un post sul blog<\/span><\/a> che, per quanto impressionante, l'apprendimento automatico non \u00e8 una panacea per questo tipo di problemi di ricerca: \"\u00c8 importante capire che l'apprendimento automatico non \u00e8 una soluzione magica per ogni problema scientifico. In questo lavoro, lo abbiamo usato come uno strumento tra i tanti\".<\/span><\/p>\n

    I ricercatori hanno combinato le previsioni dell'intelligenza artificiale con simulazioni molecolari ed esperimenti di laboratorio: un approccio su pi\u00f9 fronti che ha contribuito a convalidare i risultati e a perfezionare il modello.<\/span><\/p>\n

    Ci\u00f2 contribuisce a una serie di studi guidati dall'intelligenza artificiale per la scoperta di farmaci e la progettazione di materiali. I ricercatori hanno costruito modelli di IA per generare interessanti composti medicinali<\/a>, uno dei quali \u00e8 stato portato alla sperimentazione clinica<\/a>.<\/p>\n

    DeepMind ha anche creato un modello denominato GNoME<\/a> in grado di generare e sintetizzare automaticamente i materiali.<\/p>\n

    I nuovi composti crioprotettori scoperti potrebbero avere un ampio impatto sul mondo reale.<\/span><\/p>\n

    Per esempio, i ricercatori descrivono come il miglioramento della crioconservazione potrebbe prolungare la durata di conservazione dei vaccini e rendere pi\u00f9 facile il trasporto di trattamenti medici sensibili in aree remote.\u00a0<\/span><\/p>\n

    La tecnica potrebbe anche accelerare le trasfusioni di sangue riducendo i tempi di lavorazione del sangue congelato.<\/span><\/p>\n

    Sebbene i risultati siano promettenti, il team avverte che \u00e8 necessario un ulteriore lavoro per comprendere appieno il funzionamento di questi nuovi composti e per garantire la sicurezza e la stabilit\u00e0 medica.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Gli scienziati hanno sviluppato un nuovo sistema di apprendimento automatico che potrebbe aiutare a conservare vaccini, sangue e altri trattamenti medici. La ricerca, pubblicata su Nature Communications, \u00e8 stata condotta dall'Universit\u00e0 di Warwick e dall'Universit\u00e0 di Manchester. Il sistema di intelligenza artificiale aiuta a identificare le molecole chiamate crioprotettori - composti che prevengono i danni durante il congelamento dei materiali biologici. I crioprotettori sono sostanze speciali che aiutano a proteggere le cellule e i tessuti viventi da danni quando vengono congelati. Impediscono la formazione di cristalli di ghiaccio dannosi, che essenzialmente rompono i tessuti quando vengono congelati, e aiutano le cellule a mantenere la loro struttura in condizioni di freddo estremo. Questi composti<\/p>","protected":false},"author":2,"featured_media":14259,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[203,178],"class_list":["post-14258","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biotech","tag-medicine"],"yoast_head":"\nAI accelerates the discovery of cryoprotectant compounds for medicine transport and storage | 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\/it\/2024\/09\/ai-accelerates-the-discovery-of-cryoprotectant-compounds-for-medicine-transport-and-storage\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI accelerates the discovery of cryoprotectant compounds for medicine transport and storage | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Scientists have developed a new machine learning system that could help preserve vaccines, blood, and other medical treatments.\u00a0 The research, published in Nature Communications, was led by the University of Warwick and the University of Manchester. 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