AIMC Topic: Vaccine Development

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Innovations and challenges in vaccine development: Lessons from the SARS-CoV-2 pandemic and prospects.

Biochemical and biophysical research communications
Vaccination stands as one of the most significant achievements in public health, dramatically reducing the incidence of infectious diseases worldwide. The COVID-19 pandemic has catalyzed revolutionary advancements in vaccinology, particularly through...

Legal questions of AI-generated immunological products for infectious diseases.

Human vaccines & immunotherapeutics
Artificial intelligence (AI) has potential to surpass human capabilities to reshape vaccine design. However, its integration raises legal, ethical, and intellectual property challenges. Transparency in AI-driven immunological products is crucial for ...

Overcoming Immune Evasion in : Strategies for Rational Vaccine Design.

ACS infectious diseases
remains one of the most elusive targets in bacterial vaccinology, primarily due to its complex immune evasion strategies and the phenomenon of immune imprinting. Despite decades of research and numerous clinical trials, no vaccine has demonstrated p...

Accelerating vaccine development: Plug-and-play platforms for emerging infectious diseases.

Virus research
Emerging pathogens underscore an urgent need for rapidly developed vaccines to minimize mortality and societal disruption. Traditional vaccine development requires time spans of years, making it ill-suited to fast evolving viruses that can overwhelm ...

Advances in vaccine adjuvant development and future perspectives.

Drug delivery
Use of highly purified antigens to improve vaccine safety has led to reduced immunogenicity and efficacy, resulting in the need for adjuvants to increase and/or modulate the immunogenicity of the vaccine. Despite the need for potent and safe vaccine ...

Bayesian optimization and machine learning for vaccine formulation development.

PloS one
Developing vaccines with a better stability is an area of improvement to meet the global health needs of preventing infectious diseases. With the advancement of data science and artificial intelligence, innovative approaches have emerged. This manusc...

Multi-criteria decision making and its application to in silico discovery of vaccine candidates for Toxoplasma gondii.

Vaccine
Vaccine discovery against eukaryotic parasites is not trivial and few exist. Reverse vaccinology is an in silico vaccine discovery approach, designed to identify vaccine candidates from the thousands of protein sequences encoded by a target genome. P...

Harnessing Computational Strategies to Overcome Challenges in mRNA Vaccines.

Physiology (Bethesda, Md.)
In recent years, the introduction of mRNA vaccines for SARS-CoV2 and respiratory syncytial virus (RSV) has highlighted the success of the mRNA technology platform. Designing mRNA sequences involves multiple components and requires balancing several p...

OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

Frontiers in immunology
The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune system are well established. This study aims to develop a novel machine learning framework for predicting antigen peptide presentation by MHC Class I and I...

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

Frontiers in cellular and infection microbiology
INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge...