AI-based Alphafold: Its potential impact on predictive medicine
AlphaFold is an outstanding example of artificial intelligence’s computational capabilities in accurately predicting intricate protein structures. A new Review article explores AlphaFold’s recent advancements and its potential impact on predictive medicine. The article is published in the peer-reviewed journal AI in Precision Oncology. Click to read the articles now. Vivek Subbiah, MD, from the Sarah Cannon Research […]
AlphaFold is an outstanding example of artificial intelligence’s computational capabilities in accurately predicting intricate protein structures. A new Review article explores AlphaFold’s recent advancements and its potential impact on predictive medicine. The article is published in the peer-reviewed journal AI in Precision Oncology. Click to read the articles now.
Vivek Subbiah, MD, from the Sarah Cannon Research Institute, and coauthors, describe a shift toward predictive medicine, in which AI, integrated with genomic data, revolutionizes our understanding of diseases, facilitates drug design, and enables personalized therapies. This evolution comes with challenges, however, and the review emphasizes the importance of predicting protein functions, binding kinetics, and thermodynamic properties for effective drug development.
As AI merges with clinical data, the authors stress that “ethical considerations surrounding patient privacy and responsible AI use become paramount.” The review presents a hypothetical patient journey in colorectal cancer, highlighting how AI-driven predictions could accelerate the development of personalized vaccines and facilitate adaptive clinical trials.
“AlphaFold’s groundbreaking ability to predict protein structures is set to revolutionize predictive medicine, driving forward drug design and personalized therapies. Dr. Vivek Subbiah and coauthors, in a recent AI in Precision Oncology review, illuminate this transformative shift while addressing the crucial challenges and ethical considerations of integrating AI with clinical data.”, says Douglas Flora, MD, Editor-in-Chief of AI in Precision Oncology.
About the Journal
AI in Precision Oncology is the only peer-reviewed journal dedicated to the advancement of artificial intelligence applications in clinical and precision oncology. Spearheaded by Editor-in-Chief Douglas Flora, MD and supported by a diverse and accomplished team of international experts, the Journal provides a high-profile forum for cutting-edge research and frontmatter highlighting important research and industry-related advances rapidly developing within the field. For complete information, visit the AI in Precision Oncology website.
About the Publisher
Mary Ann Liebert, Inc. is a global media company dedicated to creating, curating, and delivering impactful peer-reviewed research and authoritative content services to advance the fields of biotechnology and the life sciences, specialized clinical medicine, and public health and policy. For complete information, please visit the Mary Ann Liebert, Inc. website.
Credit: Mary Ann Liebert, Inc.
AlphaFold is an outstanding example of artificial intelligence’s computational capabilities in accurately predicting intricate protein structures. A new Review article explores AlphaFold’s recent advancements and its potential impact on predictive medicine. The article is published in the peer-reviewed journal AI in Precision Oncology. Click to read the articles now.
Vivek Subbiah, MD, from the Sarah Cannon Research Institute, and coauthors, describe a shift toward predictive medicine, in which AI, integrated with genomic data, revolutionizes our understanding of diseases, facilitates drug design, and enables personalized therapies. This evolution comes with challenges, however, and the review emphasizes the importance of predicting protein functions, binding kinetics, and thermodynamic properties for effective drug development.
As AI merges with clinical data, the authors stress that “ethical considerations surrounding patient privacy and responsible AI use become paramount.” The review presents a hypothetical patient journey in colorectal cancer, highlighting how AI-driven predictions could accelerate the development of personalized vaccines and facilitate adaptive clinical trials.
“AlphaFold’s groundbreaking ability to predict protein structures is set to revolutionize predictive medicine, driving forward drug design and personalized therapies. Dr. Vivek Subbiah and coauthors, in a recent AI in Precision Oncology review, illuminate this transformative shift while addressing the crucial challenges and ethical considerations of integrating AI with clinical data.”, says Douglas Flora, MD, Editor-in-Chief of AI in Precision Oncology.
About the Journal
AI in Precision Oncology is the only peer-reviewed journal dedicated to the advancement of artificial intelligence applications in clinical and precision oncology. Spearheaded by Editor-in-Chief Douglas Flora, MD and supported by a diverse and accomplished team of international experts, the Journal provides a high-profile forum for cutting-edge research and frontmatter highlighting important research and industry-related advances rapidly developing within the field. For complete information, visit the AI in Precision Oncology website.
About the Publisher
Mary Ann Liebert, Inc. is a global media company dedicated to creating, curating, and delivering impactful peer-reviewed research and authoritative content services to advance the fields of biotechnology and the life sciences, specialized clinical medicine, and public health and policy. For complete information, please visit the Mary Ann Liebert, Inc. website.
Journal
AI in Precision Oncology
DOI
10.1089/aipo.2024.0010
Method of Research
Literature review
Subject of Research
People
Article Title
AlphaFold’s Predictive Revolution in Precision Oncology
Article Publication Date
26-Jun-2024
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