  The aim of this research review is to propose the logic and search mechanism
for the development of an artificially intelligent automaton (AIA) that can
find affected cells in a 3-dimensional biological system. Research on the
possible application of such automatons to detect and control cancer cells in
the human body are greatly focused MRI and PET scans finds the affected regions
at the tissue level even as we can find the affected regions at the cellular
level using the framework. The AIA may be designed to ensure optimum
utilization as they record and might control the presence of affected cells in
a human body. The proposed models and techniques can be generalized and used in
any application where cells are injured or affected by some disease or
accident. The best method to import AIA into the body without surgery or
injection is to insert small pill like automata, carrying material viz drugs or
leukocytes that is needed to correct the infection. In this process, the AIA
can be compared to nano pills to deliver or support therapy. NanoHive
simulation software was used to validate the framework of this paper. The
existing nanomedicine models such as obstacle avoidance algorithm based models
(Hla K H S et al 2008) and the framework in this model were tested in different
simulation based experiments. The existing models such as obstacle avoidance
based models failed in complex environmental conditions (such as changing
environmental conditions, presence of semi-solid particles, etc) while the
model in this paper executed its framework successfully.Come systems biology,
this field of automatons deserves a bigger leap of understanding especially
when pharmacogenomics is at its peak. The results also indicate the importance
of artificial intelligence and other computational capabilities in the proposed
model for the successful detection of affected cells.
