AI-Guided Epitope Prediction and Neoantigen Vaccine Design
Revolutionizing Personalized Vaccines Through Machine Learning and Immunoinformatics
About This Course
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.
Workshop 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
Workshop Structure
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
Who Should Enrol?
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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.
Important Dates
Registration Ends
08/19/2025
IST 7:00 PM
Workshop Dates
08/19/2025 – 08/21/2025
IST 8:00 PM
Workshop 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
Fee Structure
Student Fee
₹1399 | $50
Ph.D. Scholar / Researcher Fee
₹1699 | $55
Academician / Faculty Fee
₹2199 | $60
Industry Professional Fee
₹2699 | $85
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
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