Key points from article :
The immune system, a complex network of organs, tissues, and cells, is crucial in protecting the body from infections and diseases. Artificial Intelligence (AI) and computational modelling are being used to better understand its mechanisms. Johannes Textor, a researcher in computational immunology, highlights the challenges and potential of AI in replicating parts of the immune system, such as T-cell responses, which could inform future diagnostics and therapies.
The field of computational immunology began in the 1990s and has evolved, integrating machine learning and statistical analysis to model immune responses. Textor explains that while models of the immune system can help predict reactions to infections or treatments, the system's complexity, with its various subsystems and adaptive learning mechanisms, makes accurate modelling difficult. AI and increased data availability may eventually solve these challenges.
Textor also discusses how immune systems differ from other information-processing systems like the brain. Unlike neurons, immune cells are more genetically complex and distributed. The interaction between the immune and nervous systems, especially during sleep, remains an exciting area of research.
Finally, Textor touches on the immune system's role in ageing and chronic diseases, and the growing importance of data science in medical research. While AI is expected to play a larger role in healthcare, it is unlikely to replace doctors but instead support their work, particularly in easing administrative tasks and enhancing diagnostic tools.
