Space, time and cancer
A recent article suggests that the location, timing and migration patterns of Tumor-associated macrophages (TAMs) (1) open up an interesting research arena. One could envision deploying AI in this modality, perhaps on some continuous monitoring basis that can raise red flags before diagnosis and possible treatment, post. The rich dynamics associated with TAMs and their subsets may allow not only machine learning but also mathematical principles from computational fluid dynamics. If the TAMs have characteristics that alter dynamics, they may allow faster detection. The fact that location, timing and migration patters provide further information make this problem particularly attractive.
Early cancer detection and cure have eluded humans. As they solved most of external threats to their system and let them live longer, autoimmune diseases have started to raise havoc. Of these, cancer, a generic term for a myriad of different diseases, has been particularly difficult to tackle. Most perish, albeit modern medicine has been able to marginally extend life. However, it is unclear if survivors had an increase in quality adjusted life extension. Cancer, thus, remains to be the problem to solve for humanity to reach the next level.
The enemy inside has been difficult to detect and tackle, just like human societies, for they can take the same form and function and integrate with the system. If what the researchers found is true, it may allow detection at a level, hitherto unknown. On the surface, diagnosis appears to be where technologies can be applied first. This could still be a game changer as early detection allows many existing treatment modalities.
Humans are fast reaching a horizon where they can only be defeated by the enemy within. Emerging technologies can identify it and this alone may provide a measurable improvement in quality adjusted lifespan.