Description:
This course focuses on adjuvant design, vaccine trials, and validation in computational vaccine design. Learners will explore how computational approaches are used to design and optimize adjuvants to enhance the immune response. The course also covers in silico vaccine trials, the integration of computational data with wet lab experiments, and strategies for validating vaccine candidates. Students will work with advanced computational tools like MOE, GROMACS, and Rosetta to design, simulate, and optimize vaccine candidates and adjuvants.
Learning Outcomes:
By the end of this course, learners will be able to:
Design and optimize adjuvants to boost immune responses using computational tools.
Perform in silico vaccine trials and integrate computational results with wet lab trials.
Study adjuvant-antigen interactions and their impact on immune activation.
Use computational methods for validating vaccine candidates before moving to clinical trials.