AI-Guided Epitope Prediction and Neoantigen Vaccine Design
Revolutionizing Personalized Vaccines Through Machine Learning and Immunoinformatics
Skills you will gain:
About Program:
In the era of precision medicine, the development of personalized vaccines targeting patient-specific neoantigens has become a breakthrough in immunotherapy. This 3-day live virtual workshop is designed to bridge the gap between immunoinformatics and artificial intelligence, focusing on the intelligent prediction and validation of B-cell and T-cell epitopes, crucial for vaccine development.
Participants will explore cutting-edge AI models such as DeepVacPred, NetMHCpan, DeepImmuno, and VaxiJen, alongside hands-on training in integrated workflows for predicting, ranking, and designing multi-epitope vaccine constructs. Real-world case studies on cancer neoantigen prediction and in silico validation techniques will prepare learners for impactful contributions in biotech and biopharma R&D.
Aim: This workshop aims to equip participants with foundational and advanced knowledge of AI-powered epitope prediction and neoantigen vaccine design. It focuses on integrating immunoinformatics, machine learning, and structural bioinformatics tools for designing personalized vaccines, especially in oncology and infectious diseases.
Program Objectives:
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Understand the principles of epitope prediction and neoantigen biology
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Gain familiarity with key AI tools used for epitope analysis
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Implement ML models for antigenicity and MHC binding prediction
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Design multi-epitope vaccines and validate them using in silico tools
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Evaluate real-world applications and challenges in AI-driven vaccinology
What you will learn?
Day 1: Fundamentals of Epitope Prediction & Neoantigen Biology
- Introduction to Vaccinology and Immunoinformatics
- Overview of Epitopes: B-cell vs. T-cell
- Concept of Neoantigens and Personalized Vaccines
- Introduction to Key Tools: IEDB, NetMHC, VaxiJen
- Demo: Using IEDB for Basic Epitope Prediction
Day 2: AI and ML in Epitope Prediction
- Machine Learning for Epitope Prediction – An Overview
- Deep Learning Models for Antigenicity & MHC Binding
- Tools: DeepVacPred, NetMHCpan, DeepImmuno, ABCpred
- Case Study: Cancer-specific Neoantigen Prediction
- Hands-on: AI-based Workflow for Epitope Ranking
Day 3: Vaccine Design and In Silico Validation
- Constructing Multi-epitope Vaccines: Linkers, Adjuvants
- Population Coverage & Allergenicity Prediction
- Validation Tools: AllerTOP, ToxinPred, PEP-FOLD
- Real-World Applications & Challenges
- Final Demo: Design a Candidate Vaccine Using AI Tools
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!
Intended For :
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Undergraduate or postgraduate degree in Biotechnology, Bioinformatics, Computational Biology, or related life science disciplines.
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Professionals working in immunology, vaccine research, or computational drug design.
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Individuals with a keen interest in AI applications in healthcare and personalized medicine.
Career Supporting Skills
Program Outcomes
By the end of the workshop, participants will:
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Grasp the biological fundamentals of epitopes and neoantigens
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Use AI tools to predict and analyze antigenic peptides
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Build and validate a personalized multi-epitope vaccine model
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Analyze population coverage and allergenicity
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Gain hands-on experience with ML models and real-world datasets