A biomimicry approach to nanonetworks is proposed
here for targeted cancer drug delivery (TDD). The swarm of bioinspired
nanomachines utilizes the blood distribution network and
chemotaxis to carry drug through the vascular system to the cancer
site, recognized by a high concentration of vascular endothelial
growth factor (VEGF). Our approach is multi-scale and includes
processes that occur both within cells and with their neighbors. The
proposed bionanonetwork takes advantage of several organic processes,
some of which already occur within the human body, such
as a plate-like structure similar to those of red blood cells for more
environmental contact; a berry fruit architecture for its internal
multi-foams architecture; the penetrable structure of cancer cells,
tissue, as well as the porous structure of the capillaries for drug
penetration; state of glycocalyx for ligand-receptor adhesion; as
well as changes in pH state of blood and release for nanomachine
communication. For a more appropriate evaluation, we compare
our work with a conventional chemotherapy approach using a
mathematical model of cancer under actual experimental parameter
settings. Simulation results show the merits of the proposed
method in targeted cancer therapy by improving the densities of
the relevant cancer cell types and VEGF concentration, while following
more organic and natural processes.
Index Terms—Bioinspired, biomimicry, chemotaxis, glycocalyx,
nanonetworks, targeted cancer therapy.
I. INTRODUCTION H UMAN BODY works as a society. In order to reach its
goal of survival, all of its parts need to collaborate gainfully.
The smallest body member is a cell that reproduces by
cell division and organizes into collaborative assemblies called
tissues. Such collaboration requires coordination; so cells send,
receive and interpret a set of extracellular signals as “social controls”
[1]. In following this socially responsible manner, each
cell organizes its behaviors, such as resting, growing, dividing,
differentiating, and even dying [2]. Any disturbance to this sophisticated
collaboration can shatter this harmony. One of these
disturbances is cancer, which is the most cellular rule breaker.
Manuscript received March 19, 2015; revised July 13, 2015; accepted
September 07, 2015. Date of publication October 26, 2015; date of current
version January 07, 2016. Asterisk indicates corresponding author.
N. Rady Raz is with Department of Computer Engineering, Center of Excellence
on Soft Computing and Intelligent Information Processing, Ferdowsi University
of Mashhad, Mashhad 91775-1111, Iran (e-mail: radyraz@stu.um.ac.ir).
• M.-R. Akbarzadeh-T. is with Departments of Electrical Engineering
and Computer Engineering, Center of Excellence on Soft Computing and
Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad
91775-1111, Iran (e-mail: akbazar@um.ac.ir).
M. Tafaghodi is with Department of Pharmaceutical Nanotechnology, Nanotechnology
Research Center and School of Pharmacy, Mashhad University of
Medical Sciences, Mashhad 91775-1365, Iran (e-mail: tafaghodim@mums.ac.
ir).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org .
Digital Object Identifier 10.1109/TNB.2015.2489761
Conventional cancer therapies include: surgery, stem cell
transplant [7]–[9], chemotherapy, radiation, as well as immunotherapy
and photodynamic therapies. There are also
those therapies that are considered complementary such as
nutritional and spiritual. A hidden problem in all of these
therapies is the lack of intelligence. For instance, all drugs used
in chemotherapy affect all cells with high proliferative rate. In
our body, there are some cells with naturally high proliferation
such as hair follicles, bone marrow cells and cells of digestive
system. Hence, chemotherapeutic drugs not only affect cancer
cells but also affect these healthy cells. This intensifies the need
for new types of approaches such as targeted cancer therapies.
Targeted cancer therapy, also known as “personalized cancer
medicine,” [10] is a type of treatment that interferes with
specific cell molecules required for carcinogenesis and tumor
growth, rather than by simply interfering with all rapidly dividing
cells that is common in traditional chemotherapy [11].
For a successful solution, this type of therapy requires perspectives
from various domains such as biology, engineering, as
well as chemistry. For instance, Alexander-Bryant et al. [12]
mentioned bioengineering strategies for designing targeted
cancer therapies. They divided the strategies for targeted cancer
therapies into delivering a high dose of anticancer drug directly
to a cancer tumor, enhancing the drug uptake by malignant
cells, and minimizing the drug uptake by nonmalignant cells.
Furthermore, Keratz et al. [13] mentioned combination cancer
therapy. According to Cree et al. [14], understanding the
genome alone is not sufficient to guarantee success of target
therapy, and the challenge of target therapy is how to use
advanced molecular understanding with limited cellular assay
information to improve both drug development and the design
of companion diagnostics to guide their use.
Silva et al. [15] reviewed the immunological mechanisms
behind cancer vaccines, including the role of DCs in the stimulation
of T lymphocytes and the use of Toll-like receptors
(TLR) ligands as adjuvants. Hryniewicz-Jankowska et al.
[16] reviewed several growth factor receptor signaling pathways
on membrane rafts which are distinct plasma membrane
micro-domains enriched in sphingolipids and cholesterol.
They organized receptors and their downstream molecules and
regulated a number of intracellular signaling pathways.
Target drug delivery systems for cancer therapy has been actively
studied in recent years, and a number of corresponding
mathematical models and computational frameworks are developed.
Akbarzadeh and his colleague in [17] proposed a proportional
drug-encapsulated nanoparticle (PDENP) to target the
LDL concentration in the interior of the arterial wall using a
simple piecewise-proportional controller to do the swarm feedback
control. In [18] experiments and modeling of untethered