Cambridge Healthtech Institute’s Inaugural
SYMPOSIUM: AI/ML Approaches in Immunogenicity Prediction
Accelelerating Immunogenicity Insights with AI/ML Precision
January 19, 2026
The AI/ML Approaches in Immunogenicity Prediction symposium brings together leading experts from biotechnology, pharmaceutical research, academia, and regulatory bodies to explore the transformative potential of artificial intelligence (AI) and machine learning (ML) in immunogenicity assessment. This one-day symposium focuses on the prediction and mitigation of immune responses to biotherapeutics and highlights how AIML technologies are being leveraged to improve the accuracy, scalability, and personalization of immunogenicity risk assessments across the drug development pipeline.
Attendees gain insight into cutting-edge tools, algorithms, and frameworks that are redefining the way researchers approach risk evaluation. The symposium emphasizes scalability, showcasing how machine-learning models can efficiently handle vast immunological datasets, and personalization, illustrating how predictive analytics can inform individualized therapeutic strategies and reduce adverse events.
Coverage will include, but is not limited to:
- The integration of bioinformatics and systems immunology with AI-driven methodologies
- Predictive modeling for immunogenicity risk assessment
- Combining empirical and computational data
- Benchmarking in silico predictions with wet-lab data
- Novel data curation and model training practices for improving prediction reliability
- Regulatory challenges and considerations for the validation and acceptance of AIML-derived insights
The deadline for priority consideration is June 27, 2025.
All proposals are subject to review by session chairpersons and/or the Scientific Advisory Committee to ensure the overall quality of the conference program. Additionally, as per Cambridge Healthtech Institute’s policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.
Opportunities for Participation: