  In this paper we propose a data-driven methodology to gain insight into the
formation of different types of pseudopalisade structures. To this end, we
start from a state of the art macroscopic model for the dynamics of GBM, that
is coupled with the dynamics of extracellular pH, and formulate a terminal
value optimal control problem. Thus, given a specific, observed pseudopalisade
pattern, we determine the evolution of parameters (bio-mechanisms) that are
responsible for its emergence. Random histological images exhibiting
pseudopalisade-like structures are chosen to serve as target pattern. Having
identified the optimal model parameters that generate the specified target
pattern, we then formulate two different types of pattern counteracting
ansatzes in order to determine possible ways to impair or obstruct the process
of pseudopalisade formation. This provides the basis for designing active or
live control of malignant GBM. Furthermore, we also provide a simple, yet
insightful, mechanism to synthesize new pseudopalisade patterns by linearly
combining the optimal model parameters responsible for generating different
known target patterns. This particularly provides a hint that complex
pseudopalisade patterns could be synthesized by a linear combination of
parameters responsible for generating simple patterns. Going even further, we
ask ourselves if complex therapy approaches can be conceived by linearly
combining such that are able to reverse or disrupt simple pseudopalisade
patterns, which is then positively answered with the help of numerical
simulations.
