The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development

Molecular Biomedicine, Год журнала: 2025, Номер 6(1)

Опубликована: Янв. 3, 2025

Abstract Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates multidimensional role AI in pandemic, which arises as a global health crisis, and its preparedness responses, ranging from enhanced epidemiological modelling to acceleration vaccine development. The confluence technologies guided us new era data-driven decision-making, revolutionizing our ability anticipate, mitigate, treat infectious illnesses. begins by discussing impact on emerging countries worldwide, elaborating critical significance modelling, bringing enabling forecasting, mitigation response pandemic. In epidemiology, AI-driven models like SIR (Susceptible-Infectious-Recovered) SIS (Susceptible-Infectious-Susceptible) are applied predict spread disease, preventing outbreaks optimising distribution. also demonstrates how Machine Learning (ML) algorithms predictive analytics improve knowledge disease propagation patterns. collaborative aspect discovery clinical trials various vaccines is emphasised, focusing constructing AI-powered surveillance networks. Conclusively, presents comprehensive assessment impacts builds AI-enabled dynamic collaborating ML Deep (DL) techniques, develops implements trials. focuses screening, contact tracing monitoring virus-causing It advocates for sustained research, real-world implications, ethical application strategic integration strengthen collective face alleviate effects issues.

Язык: Английский

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Epitope-Based Vaccines: The Next Generation of Promising Vaccines Against Bacterial Infection

Vaccines, Год журнала: 2025, Номер 13(3), С. 248 - 248

Опубликована: Фев. 27, 2025

The increasing resistance of bacteria to antibiotics has underscored the need for new drugs or vaccines prevent bacterial infections. Reducing multidrug is a key objective WHO’s One Health initiative. Epitopes, parts antigen molecules that determine their specificity, directly stimulate body produce specific humoral and/or cellular immune responses. Epitope-based vaccines, which combine dominant epitopes in rational manner, induce more efficient and response than original antigen. While these face significant challenges, such as epitope escape low immunogenicity, they offer advantages including minimal adverse reactions, improved efficacy, optimized protection. As result, epitope-based are considered promising next-generation approach combating This review summarizes latest advancements, future prospects targeting bacteria, with focus on development workflow application antibiotic-resistant pathogens high mortality rates, Staphylococcus aureus, Streptococcus pneumoniae, pyogenes, Klebsiella Acinetobacter baumannii, Pseudomonas aeruginosa. goal this provide insights into vaccination strategies combat infections associated antibiotic rates.

Язык: Английский

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Rethinking Optimal Immunogens to Face SARS‐CoV‐2 Evolution Through Vaccination

Influenza and Other Respiratory Viruses, Год журнала: 2025, Номер 19(1)

Опубликована: Янв. 1, 2025

ABSTRACT SARS‐CoV‐2, which originated in China late 2019, quickly fueled the global COVID‐19 pandemic, profoundly impacting health and economy worldwide. A series of vaccines, mostly based on full SARS‐CoV‐2 Spike protein, were rapidly developed, showing excellent humoral cellular responses high efficacy against both symptomatic infection severe disease. However, viral evolution waning neutralizing strongly challenged vaccine long term effectiveness, mainly infection, making necessary a strategy repeated updated booster shots. In this vaccination context, antibody repertoire diversification was evidenced, although immune imprinting after doses or reinfection also demonstrated identified as major determinant immunological to antigen exposures. Considering that small domain receptor binding (RBD), is target antibodies concentrates most mutations, following text aims provide insights into ongoing debate over best strategies for boosters. We address relevance developing new vaccines evolving RBD, thus focusing relevant antigenic sites variants. combination with immunofusing computerized approaches could minimize imprinting, therefore optimizing efficacy.

Язык: Английский

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Multidrug-resistant hypervirulent Klebsiella pneumoniae : an evolving superbug

Future Microbiology, Год журнала: 2025, Номер unknown, С. 1 - 13

Опубликована: Март 26, 2025

Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) combines high pathogenicity with multidrug resistance to become a new superbug. MDR-hvKP reports continue emerge, shattering the perception that K. (hvKP) strains are antibiotic sensitive. Patients infected have been reported in Asia, particularly China. Although hvKP can acquire drug genes, seems be more easily transformed from classical (cKP), which has strong gene uptake ability. To better understand biology of MDR-hvKP, this review discusses virulence factors, mechanisms, formation pathways, and identification MDR-hvKP. Given their destructive transmissible potential, continued surveillance these organisms enhanced control measures should prioritized.

Язык: Английский

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Opportunities and challenges with artificial intelligence in allergy and immunology: a bibliometric study

Frontiers in Medicine, Год журнала: 2025, Номер 12

Опубликована: Апрель 9, 2025

Introduction The fields of allergy and immunology are increasingly recognizing the transformative potential artificial intelligence (AI). Its adoption is reshaping research directions, clinical practices, healthcare systems. However, a systematic overview identifying current statuses, emerging trends, future hotspots lacking. Methods This study applied bibliometric analysis methods to systematically evaluate global landscape AI applications in immunology. Data from 3,883 articles published by 21,552 authors across 1,247 journals were collected analyzed identify leading contributors, prevalent themes, collaboration patterns. Results Analysis revealed that USA China currently output scientific impact this domain. methodologies, especially machine learning (ML) deep (DL), predominantly drug discovery development, disease classification prediction, immune response modeling, decision support, diagnostics, system digitalization, medical education. Emerging trends indicate significant movement toward personalized systems integration. Discussion findings demonstrate dynamic evolution immunology, highlighting broadening scope basic diagnostics comprehensive Despite advancements, critical challenges persist, including technological limitations, ethical concerns, regulatory frameworks could potentially hinder further implementation Conclusion holds considerable promise for advancing globally enhancing precision, efficiency, accessibility. Addressing existing technological, ethical, will be crucial fully realizing its potential, ultimately improving health outcomes patient well-being.

Язык: Английский

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AI in the development of vaccines for emerging and re-emerging diseases

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

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A meta-analysis of AI and machine learning in project management: Optimizing vaccine development for emerging viral threats in biotechnology

International Journal of Medical Informatics, Год журнала: 2024, Номер 195, С. 105768 - 105768

Опубликована: Дек. 18, 2024

Язык: Английский

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