One strategy to reduce a patient's risk of transplant rejection would be the use of tailored immunosuppresant drugs. Before such drugs can be used, a better understanding of the levels of each type of antibody a transplant can tolerate is needed. In my recent mini-project thesis I presented the use of existing mathematical models and new mathematical models to evaluate the dynamics of antibody binding in surface plasmon resonance (SPR) experiments with commercial anti-A monoclonal IgM. These fits and models are one of the necessary steps towards identifying and characterising potential risks in individual patients, and allowing tailored immunosuppresant drugs.

These models could potentialy be used in the future to estimate the binding kinetics of a patients antibodies with a donor organ, and help doctors better assess the risk of rejection.

This research can be read about here Thesis.

The identifiability analysis can be read about here Identifiability 1 Identifiability 2 Identifiability 3.

The programs that were used to fit models to the data can be downloaded in a zip file here programs. There is a password protecting the .zip file. This can be requested via email.

H. Moyse demonstrating the importance of chalkboards in mathematics.