  In recent years, there has been tremendous progress in the development of
quantum computing hardware, algorithms and services leading to the expectation
that in the near future quantum computers will be capable of performing
simulations for natural science applications, operations research, and machine
learning at scales mostly inaccessible to classical computers. Whereas the
impact of quantum computing has already started to be recognized in fields such
as cryptanalysis, natural science simulations, and optimization among others,
very little is known about the full potential of quantum computing simulations
and machine learning in the realm of healthcare and life science (HCLS).
Herein, we discuss the transformational changes we expect from the use of
quantum computation for HCLS research, more specifically in the field of
cell-centric therapeutics. Moreover, we identify and elaborate open problems in
cell engineering, tissue modeling, perturbation modeling, and bio-topology
while discussing candidate quantum algorithms for research on these topics and
their potential advantages over classical computational approaches.
