AI in the development of vaccines for emerging and re-emerging diseases DOI
Rita Elizabeth Velastegui-Hernández, Verónica Gabriela Salinas Velasteguí, Diana Catalina Velasteguí Hernández

и другие.

Salud Ciencia y Tecnología, Год журнала: 2025, Номер 4

Опубликована: Янв. 15, 2025

Introduction: The integration of artificial intelligence (AI) into vaccine development has revolutionized traditional methodologies, significantly enhancing the speed, precision, and scalability immunological research. Emerging re-emerging infectious diseases, driven by zoonotic spillovers, antimicrobial resistance, global environmental changes, pose substantial challenges. Addressing these requires innovative approaches, with AI playing a pivotal role in advancing solutions.Development: applications vaccinology include antigen detection, adjuvant optimization, immune response simulation. Deep learning algorithms streamline identification immunogenic targets conserved antigens, enabling for highly mutable pathogens such as SARS-CoV-2, HIV, influenza. Case studies demonstrate AI's transformative impact, including its rapid creation mRNA vaccines COVID-19, promising antigens malaria, enhanced efficacy influenza through predictive modeling. However, challenges unequal access to technology, biases data models, ethical concerns regarding genomic privacy persist. Recommendations address barriers increasing diversity, strengthening frameworks, investing infrastructure democratize AI-driven innovations.Conclusions: ability reduce time cost, improve enable personalized immunization strategies positions it cornerstone modern vaccinology. With continued advancements equitable implementation, holds potential reshape development, pandemic preparedness, longstanding public health disparities globally.

Язык: Английский

Insights into tumor-derived exosome inhibition in cancer therapy DOI
Ziwei Tang, Cheng Chen, Chen Zhou

и другие.

European Journal of Medicinal Chemistry, Год журнала: 2025, Номер 285, С. 117278 - 117278

Опубликована: Янв. 13, 2025

Язык: Английский

Процитировано

1
The landscape of Artificial Intelligence Driven Digital Platforms in Healthcare and Life Sciences: A Scoping Review Towards Universal Integration (Preprint) DOI

Rahela Penovski,

Stanko Srčič,

Reinhold Scherer

и другие.

Опубликована: Апрель 7, 2025

BACKGROUND Digital platforms are transforming healthcare and life sciences by enhancing operational efficiency, improving patient outcomes, accelerating product development market access. These facilitate telemedicine, remote monitoring, data-driven care delivery, while in sciences, they streamline research, optimize manufacturing, support regulatory compliance. However, current Artificial Intelligence (AI) based solutions remain fragmented domain-specific, lacking the integration necessary to address complex challenges within across these industries. While AI excels specialized areas—such as radiology image analysis, sepsis-detection predictive analytics, AI-driven drug discovery—these often operate isolation. OBJECTIVE This scoping review aims critically analyze landscape of digital identify existing gaps opportunities, explore feasibility developing a comprehensive, universal AI-based platform. METHODS A was conducted following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews Meta-Analyses extension Scoping Reviews) guidelines. comprehensive search peer-reviewed literature, industry reports, documents performed databases including PubMed, Embase, CINAHL, PsycINFO, Scopus, IEEE Xplore, Web Science. Inclusion criteria focused on studies, published from 2014 2024, addressing platforms, integration, science applications, regulations, professional ethics. Data were charted synthesized themes related platform capabilities, gaps, potential. RESULTS The identified seven common types utilized alongside growing trend implementation AI, generative AI. Significant found interoperability, cross-sector collaboration, utilization. technologies showed promise discovery diagnostic accuracy reducing costs. Despite advances, differences data standards, constraints, proprietary formats hinder seamless with electronic health record systems workflows. Moreover, applications neglect personalized treatment plans that integrate genomics, lifestyle factors, comorbidities, social determinants health. Organizations like World Health Organization, Massachusetts Institute Technology, Microsoft exploring integrated solutions, but standardization, privacy, regulatory, ethical considerations remain. CONCLUSIONS could revolutionize research innovation. By fragmentation fostering sectors, such enable continuous improvement innovation delivery development. overcoming compliance, standards is critical. Collaborative efforts sectors essential develop connected, responsive, effective national global systems. Future should focus defining platform's structure scope, design strategies, aligning ethics ensure equitable integration.

Язык: Английский

Процитировано

0
Artificial Intelligence in Central-Peripheral Interaction Organ Crosstalk: The Future of Drug Discovery and Clinical Trials DOI Creative Commons

Yufeng Chen,

Mingrui Yang, Qian Hua

и другие.

Pharmacological Research, Год журнала: 2025, Номер unknown, С. 107734 - 107734

Опубликована: Апрель 1, 2025

Drug discovery before the 20th century often focused on single genes, molecules, cells, or organs, failing to capture complexity of biological systems. The emergence protein-protein interaction network studies in 2001 marked a turning point and promoted holistic approach that considers human body as an interconnected system. This is particularly evident study bidirectional interactions between central nervous system (CNS) peripheral which are critical for understanding health disease. Understanding these complex requires integrating multi-scale, heterogeneous data from molecular organ levels, encompassing both omics (e.g., genomics, proteomics, microbiomics) non-omics imaging, clinical phenotypes). Artificial intelligence (AI), multi-modal models, has demonstrated significant potential analyzing CNS-peripheral by processing vast, datasets. Specifically, AI facilitates identification biomarkers, prediction therapeutic targets, simulation drug effects multi-organ systems, thereby paving way novel strategies. review highlights AI's transformative role research, focusing its applications unraveling disease mechanisms, discovering optimizing trials through patient stratification adaptive trial design.

Язык: Английский

Процитировано

0
AI in the development of vaccines for emerging and re-emerging diseases DOI
Rita Elizabeth Velastegui-Hernández, Verónica Gabriela Salinas Velasteguí, Diana Catalina Velasteguí Hernández

и другие.

Salud Ciencia y Tecnología, Год журнала: 2025, Номер 4

Опубликована: Янв. 15, 2025

Introduction: The integration of artificial intelligence (AI) into vaccine development has revolutionized traditional methodologies, significantly enhancing the speed, precision, and scalability immunological research. Emerging re-emerging infectious diseases, driven by zoonotic spillovers, antimicrobial resistance, global environmental changes, pose substantial challenges. Addressing these requires innovative approaches, with AI playing a pivotal role in advancing solutions.Development: applications vaccinology include antigen detection, adjuvant optimization, immune response simulation. Deep learning algorithms streamline identification immunogenic targets conserved antigens, enabling for highly mutable pathogens such as SARS-CoV-2, HIV, influenza. Case studies demonstrate AI's transformative impact, including its rapid creation mRNA vaccines COVID-19, promising antigens malaria, enhanced efficacy influenza through predictive modeling. However, challenges unequal access to technology, biases data models, ethical concerns regarding genomic privacy persist. Recommendations address barriers increasing diversity, strengthening frameworks, investing infrastructure democratize AI-driven innovations.Conclusions: ability reduce time cost, improve enable personalized immunization strategies positions it cornerstone modern vaccinology. With continued advancements equitable implementation, holds potential reshape development, pandemic preparedness, longstanding public health disparities globally.

Язык: Английский

Процитировано

0