Elsevier eBooks, Год журнала: 2024, Номер unknown
Опубликована: Янв. 1, 2024
Язык: Английский
Journal of Microbiological Methods, Год журнала: 2024, Номер 224, С. 106998 - 106998
Опубликована: Июль 15, 2024
Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity mortality. However, traditional vaccine methods are often time-consuming, costly, inefficient. The advent artificial intelligence (AI) has ushered new era design, offering unprecedented opportunities to expedite the process. This narrative review explores role AI development, focusing on antigen selection, epitope prediction, adjuvant identification, optimization strategies. algorithms, including machine learning deep learning, leverage genomic data, protein structures, immune system interactions predict antigenic epitopes, assess immunogenicity, prioritize antigens for experimentation. Furthermore, AI-driven approaches facilitate rational design immunogens identification novel candidates with optimal safety efficacy profiles. Challenges such data heterogeneity, model interpretability, regulatory considerations must be addressed realize full potential development. Integrating emerging technologies, single-cell omics synthetic biology, promises enhance precision scalability. underscores transformative impact highlights need interdisciplinary collaborations harmonization accelerate delivery safe effective vaccines against diseases.
Язык: Английский
Процитировано
18
International Reviews of Immunology, Год журнала: 2024, Номер 43(6), С. 361 - 380
Опубликована: Июль 10, 2024
Computational biology involves applying computer science and informatics techniques in to understand complex biological data. It allows us collect, connect, analyze data at a large scale build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used various fields of sciences such as biochemistry, structural biology, immunology, microbiology, genomics handle massive for decision-making, including applications drug design vaccine development, one major areas focus human animal welfare. The knowledge available AI-enabled tools development can improve our ability conduct cutting-edge research. Therefore, this review article aims summarize important AI-based tools. Further, discusses limitations AI development.
Язык: Английский
Процитировано
6
Journal of Pharmaceutical and Biological Sciences, Год журнала: 2025, Номер 12(2), С. 109 - 118
Опубликована: Янв. 9, 2025
Because of their diverse clinical manifestations and intricate pathophysiology, autoimmune diseases which are defined by the immune system wrongly attacking healthy tissues present serious difficulties. Artificial intelligence (AI) has shown revolutionary promise in this field, especially improving diagnostic precision, facilitating tailored treatment plans, offering real-time illness tracking. This paper highlights AI's role assessing various datasets pertaining to function pathology while critically examining applications AI therapy diseases. In order find new biomarkers enable early accurate detection disorders, advanced approaches such as machine learning deep have proven essential. AI-powered predictive models demonstrated predicting periods remission disease flares, allowing for prompt focused modifications. Furthermore, accelerating identification promising therapeutic candidates lowering related costs, is transforming drug discovery repurposing. However, issues including data heterogeneity, algorithmic transparency, patient confidence AI-driven suggestions limit full potential need ethical frameworks interdisciplinary collaboration these limits suggesting solutions. shows transform diagnosis, treatment, management disorders combining recent developments future applications. will pave way a where healthcare solutions proactive, accurate, individualized.
Язык: Английский
Процитировано
0
The Microbe, Год журнала: 2025, Номер unknown, С. 100324 - 100324
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0
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
Vaccines, Год журнала: 2024, Номер 12(12), С. 1345 - 1345
Опубликована: Ноя. 28, 2024
The development of vaccines against RNA viruses has undergone a rapid evolution in recent years, particularly driven by the COVID-19 pandemic. This review examines key roles that viruses, with their high mutation rates and zoonotic potential, play fostering vaccine innovation. We also discuss both traditional modern platforms impact new technologies, such as artificial intelligence, on optimizing immunization strategies. evaluates various platforms, ranging from approaches (inactivated live-attenuated vaccines) to technologies (subunit vaccines, viral bacterial vectors, nucleic acid mRNA DNA, phage-like particle vaccines). To illustrate these platforms’ practical applications, we present case studies developed for SARS-CoV-2, influenza, Zika, dengue. Additionally, assess role intelligence predicting mutations enhancing design. underscore successful application RNA-based fight COVID-19, which saved millions lives. Current clinical trials dengue continue show promise, highlighting growing efficacy adaptability platforms. Furthermore, is driving improvements candidate optimization providing predictive models evolution, our ability respond future outbreaks. Advances technology, success highlight potential combating viruses. Ongoing demonstrate platform adaptability, while enhances design mutations. Integrating innovations One Health approach, unites human, animal, environmental health, essential strengthening global preparedness virus threats.
Язык: Английский
Процитировано
2
Bioengineering, Год журнала: 2024, Номер 11(9), С. 915 - 915
Опубликована: Сен. 13, 2024
Artificial Intelligence (AI) refers to the creation of computer systems capable performing tasks typically requiring human intelligence [...].
Язык: Английский
Процитировано
1
IntechOpen eBooks, Год журнала: 2024, Номер unknown
Опубликована: Сен. 19, 2024
Vaccinology, the scientific discipline focused on vaccines, has evolved from combating infectious diseases to addressing a wide array of broad spectrum health concerns, including autoimmune disorders, neurodegenerative diseases, and allergies, with promising therapeutic vaccines for cancer utilizing tumor-infiltrating lymphocytes (TILs) adoptive cell therapy, like chimeric antigen receptor T-cell (CAR-T-cells), CAR-natural killer cells (CAR-NK cells), CAR-macrophages (CAR-M), as well necrotic necroptotic cells. Additionally, ongoing research endeavors aim develop anti-addiction vaccines. This chapter offers comprehensive exploration vaccinology, encompassing fundamental immunity concepts, role adjuvants, various vaccine types. It traces evolution development traditional methods modern innovations messenger ribonucleic acid (mRNA) exemplified by those developed coronavirus disease 2019 (COVID-19), which offer rapid adaptability emerging variants. The significance measuring neutralizing antibodies in assessing efficacy effectiveness, is crucial guiding epidemic responses, underscored. By delving into historical contemporary developments, current challenges, envisioning future directions, this fosters deeper understanding vaccinology encourages critical reflection innovative solutions global challenges.
Язык: Английский
Процитировано
1
Elsevier eBooks, Год журнала: 2024, Номер unknown
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0
Life, Год журнала: 2024, Номер 14(4), С. 489 - 489
Опубликована: Апрель 10, 2024
The specific interaction between cell surface receptors and corresponding antibodies has driven opportunities for developing targeted cancer therapies using nanoparticle systems. It is challenging to design develop such nanomedicines antibody ligands, as the final nanoconjugate's specificity hinges on cohesive functioning of its components. multicomponent nature antibody-conjugated nanoparticles also complicates characterization process. Regardless type nanoparticle, it essential perform physicochemical establish a solid foundation knowledge suitable preclinical studies. A meaningful evaluation should include determining quantity orientation antibodies, confirming antibodies' integrity following attachment, assessing immunoreactivity obtained nanoconjugates. In this review, authors describe various techniques (electrophoresis, spectroscopy, colorimetric assays, immunoassays, etc.) used analyze properties functionalized with discuss main results.
Язык: Английский
Процитировано
0