{"id":8669,"date":"2023-07-21T11:13:46","date_gmt":"2023-07-21T11:13:46","guid":{"rendered":"https:\/\/komorebi.ai\/?page_id=8669"},"modified":"2024-01-10T10:14:04","modified_gmt":"2024-01-10T10:14:04","slug":"ai-in-drug-development","status":"publish","type":"page","link":"https:\/\/komorebi.ai\/en\/ai-in-drug-development\/","title":{"rendered":"AI in drug development: a multidisciplinary perspective"},"content":{"rendered":"
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AI to streamline and reduce the cost of drug development<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Molecular Diversity<\/span>, 2021<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This review discusses the application of artificial intelligence tools, particularly Bayesian approaches, in<\/strong> streamlining the lengthy and costly process of new drug development.<\/strong> \n

\nBy aiding in tasks like identifying molecular targets and predicting targets such as ADME-Tox, Machine Learning models are utilized in all stages from basic research to post-marketing. \n

\nThis review aims to bridge the gap between chemists and mathematicians, focusing on molecular modeling and decision-support applications often overlooked in similar research.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Streamlining Drug Development Process using Bayesian Approaches in Artificial Intelligence<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Where does it apply?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The use of Bayesian approaches is applicable across the entire drug development process,<\/strong> from basic research for drug discovery, the pre-clinical phase, the clinical phase, and even the post-marketing phase. \n

\nIt can be used to identify molecular targets, search for hit and lead compounds, synthesize drug-like compounds, predict ADME-Tox, and support decision-making processes.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Why does it matter?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine Learning can significantly expedite and reduce the cost of the process<\/strong> which traditionally is lengthy and costly. Specifically, the use of Bayesian approaches aids in better decision-making and molecular modeling, thus potentially leading to more effective and safer drugs. \n

\nFurthermore, a better understanding between chemists and mathematicians can yield improved collaboration and integration of AI into the drug development process.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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AI in drug development: a multidisciplinary perspective<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Molecular Diversity, 2021<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\tVictor Gallego <\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tChief Research Officer<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tDrug development, Decision support<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Other publications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Current Advances In Neural Networks\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Inclusive dijet hadroproduction with a rapidity veto constraint\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Joint association of physical activity and body mass index with cardiovascular risk<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The article reviews neural networks\u2019 progress emphasizing Bayesian approaches and highlights relevance in predictive analytics, customer behavior analysis, and risk management in business sectors.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The study explores parameters for perturbative expansion in particle collisions, helping in the understanding of particle physics. In the long term, this applies to fields like quantum computing, health technology, nuclear energy, and environmental monitoring.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The study refutes the 'fat but fit' paradox, stressing the importance of weight loss in combination with physical activity to alleviate risks of cardiovascular diseases.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tNeural networks, customer behavior analysis<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tParticle Physics, Big Data<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Learn More >><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

IA para acelerar y reducir el coste de desarrollo de f\u00e1rmacos Molecular Diversity, 2021 Resumen Esta revisi\u00f3n analiza la aplicaci\u00f3n de herramientas de inteligencia artificial, en particular los enfoques bayesianos, para agilizar el largo y costoso proceso de desarrollo de nuevos f\u00e1rmacos. Al ayudar en tareas como la identificaci\u00f3n de dianas moleculares y la predicci\u00f3n […]<\/p>","protected":false},"author":1,"featured_media":8734,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"yoast_head":"\nAI in drug development: a multidisciplinary perspective - Komorebi AI<\/title>\n<meta name=\"description\" content=\"The use of AI, particularly Bayesian approaches, in speeding up and reducing the cost of drug development across all stages.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/komorebi.ai\/en\/ai-in-drug-development\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI in drug development: a multidisciplinary perspective - Komorebi AI\" \/>\n<meta property=\"og:description\" content=\"The use of AI, particularly Bayesian approaches, in speeding up and reducing the cost of drug development across all stages.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/komorebi.ai\/en\/ai-in-drug-development\/\" \/>\n<meta property=\"og:site_name\" content=\"Komorebi AI\" \/>\n<meta property=\"article:modified_time\" content=\"2024-01-10T10:14:04+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/komorebi.ai\/wp-content\/uploads\/2023\/07\/drugs-2-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1707\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/komorebi.ai\/ai-in-drug-development\/\",\"url\":\"https:\/\/komorebi.ai\/ai-in-drug-development\/\",\"name\":\"AI in drug development: a multidisciplinary perspective - 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