Professor Ales Prokop

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Professor Ales Prokop

• Research Professor
• Vanderbilt University Department
• of Chemical Engineering

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Multifunctional nanoparticulate vehicles for
targeted drug delivery and systems
biology By Ales Prokop and Jeffrey M Davidson
Vanderbilt University, Nashville, TN 1st Annual
Unither Nanomedical Telemedical Technology
Conference Hotel Manoir Des Sables 90, av. Des
Jardins Orford (Quebec) J1X 6M6 April 1-4, 2008
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• This
  presentation will provide an
• Overview of principles and challenges relevant to
  drug or gene transport, cellular accumulation and
  retention by means of nanovehicles. Differential
  localization and targeting means will be
  discussed, together with a limited discussion on
  pharmacokinetics and pharmacodynamics. Newer
  developments in nanovehicle technologies and
  future applications are stressed.
• We also briefly review the existing modeling
  tools and approaches to quantitatively describe
  the behavior of targeted nanovehicles within the
  vascular and tumor compartments, an area of
  particular importance. In addition, we will
  consider elementary strategies related to the
  complexity of tumor delivery, we will also stress
  the importance of multi-scale modeling and a
  bottom-up, systems biology approach to
  understanding nanovehicle dynamics. This
  discipline is now called Computational Systems
  Biology

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Part I Overview of NanoDelivery technology

• NanoDeliverys technology represents unique
  method to deliver medication by controlled
  release over extended periods of time with a
  possibility of intracellular drug uptake
• Nanoparticles (NP) are made from a mixture of
  natural polymers
• Size and charge of nanoparticles allows access to
  bodily sites that current technologies do not and
  cannot address
• Small size is critical for accessing body cells
  and internalization
• Small-size cavity of NPs allows only an
  efficacious delivery of biological modifiers with
  a high potency

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Delivery Vehicles

• Nanoparticle Assembly, Structure and Production
• Polymeric nanoparticles (PEC polyelectrolyte
  complexes) are produced by electrostatic
  interaction between anionic and cationic
  solutions (polymeric complexing)
• Nanoparticles usually have an neutral core with a
  cationic corona (shell)
• This charge could be reversed (with anionic
  corona)
• The cationically-charged formulation is
  desirable for many delivery applications using
  anionically charged (or uncharged) drugs.

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Nanoparticles

• Size, Charge and Stability Data
• Extensive data on nanoparticle size and charge
  (from both batch and continuous production) are
  available
• Diameter of 100-200 nm, charge density 15-40 mV
  (depending on chemistry used)
• Excellent stability of isolated nanoparticles in
  water (no change in certain 226 nm particle size
  over 3 weeks at 4oC)
• Stability in serum very high (no changes over
  2-week period)
• Freeze-drying product in presence of trehalose -
  original size maintained (important for
  shelf-stability of product)

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Nanoparticles

• Nanoparticle Assembly, Structure and Production
• The standard efficiency parameters of processing
  are those of entrapment efficiency (EE) and
  loading efficiency (LE).
• LE is the mass of protein or drug per mass of
  particles
• EE is the amount captured during the production
  process.
• Typical EEs for proteins are in the 25-50 range
  and LEs are between 10-50. This parameter has
  not yet been optimized
• New production method mixes two streams of
  polymer solutions at a molecular scale and high
  pressure. Mixing device available, allowing for
  industrial process scale-up

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NP Production and Molecular Characteristics

• Hypothesis Precursors with similar molecular
  weights, (LMW), will yield
• Size less than 150 nm ideal for cellular uptake
• ZPgt30 mv or ZPlt-30 mV colloidal stability (also
  important, together with hydrophobicity, for NP
  localization cytoplasmic vs nuclear)

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Music City Nanoparticles
PMCG, spermine, Ca, and Pluronic F-68
Corona(Shell)
CS/PMCG
CS
Alginate/Ca
Core (Loaded with drug)

• Anionic core consists of alginate and
  chondroitin/cellulose sulfate
• Cationic shell contains PMCG, Pluronic F-68, and
  Ca
• Hypothesis Precursors with similar molecular
  weights, (LMW), will yield
• Size less than 200 nm ideal for cellular uptake
• pH, media-independent stability for use in
  biological systems

10
Size produced with LMW constitutive polymers is
stable (flat) over a range of pH
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Importance of PEC Size

• Subcellular size allows penetration into tissues
• Internalization is driven by endocytosis
• Concentration, time-dependent
• Saturable
• Preceded by cytoskeletal rearrangement

CYTOPLASM
Mechanism size (nm)
phagocytosis 1000
macropinocytosis 250
clathrin-mediated 120
caveolin-mediated 70
clathrin/caveolae independent 50
NUCLEUS
Optimal size should be between 10 and 120 nm NP
gt 10 nm to avoid single-pass renal
clearance NPlt120 to avoid capturing by RES
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Importance of PEC Zeta Potential

• Marker of colloidal stability
• Develops as a function of excess polymers or
  modification of peripheral groups
• Important in surface modification, size
  retention/aggregation, and targeting

30mV
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Batch Processing
Ultrasonic dispergator power source
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Interim conclusions

• A simple and technology is available to assemble
  nanoparticles
• Constitutive polymers are of GRAS origin and
  their size allows for kidney elimination
• The size is tunable and can be adjusted lt100nm
• Small size important for avoiding RES interaction
• Cationic charge on periphery allows for further
  functionalization
• Production is easily scaleable and amenable for
  aseptic operation

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Part II Uptake and targeting

• NP uptake and internalization
• Internalization is improved via targeting
• NPs are retained as the exocytosis is minimal for
  non-targeted nanoparticles
• The intracellular therapeutic effects are
  enhanced because of minimal exocytosis
• NP periphery free amino groups allow for easy
  functionalization/targeting

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PEC Rapid Binding and Uptake
surface
inside

• HMVEC exposed to fixed PEC concentration for 2 h
• Visualization by confocal microscopy

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Mechanism of uptake Observations LMW PECs and
Endothelial Cells

• PEC physicochemistry in cell growth media
• Size 235.9 nm30.5 nm
• ZP -11.1 mV 2.2 mV
• PECs bind cells rapidly followed by
  internalization presumably through PMCG
• Inhibitor studies reveal
• Actin controlled
• Association needs metabolic and thermodynamic
  energy
• HSPG play a role
• Sensitive to trypsin detachment
• InhibitorsPEC sizegtmacropinocytosis likely
  dominates
• Saturation binding curves never approach a steady
  state
• PECs DO NOT interact specifically with any
  receptor
• Cells function as an anionic sink for positively
  charged PEC surface groups
• Extensive cooperativity

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TSP521 Modified PECs by EDAC/NHSlow-affinity
targeting

• Direct PEC linkage Couple non-PEGylated TSP521
  directly to PEC periphery by EDAC/NHS
  cross-linking link peptide Asp-COOH to PEC NH2
• TSP521 Ac-KRFKQDGGWSHWSPWSSCys-CONH2
• PMCG HO-(CH2-N-C-N-C-NH)x-H

Active site
H
H
O
p521 (Asp-C)
NH
NH
EDAC
p521 (Asp-COOH)
PEC
NHS
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PEGylated TSP521 is deposited on the PEC surface
(entrapped)

• Direct PEC linkage Couple non-PEGylated TSP521
  directly to PEC periphery by EDAC/NHS
  cross-linking link peptide Asp-COOH to PEC NH2
• TSP521 Ac-KRFKQDGGWSHWSPWSSCys-CONH2

Active
(PEG)20000
p521
PEGp521 Anions Cations
PEG presentation is often more efficient and
physiologic (flexible PEG linkage)
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High-affinity targeting

• RGD monovalent and bivalent motifs have been
  incorporated onto the NP periphery for active
  targeting
• RGD motifs serve as ligands for integrin
  associated with vasculature (upregulated at
  cancer)
• In vitro functionality of NPs activity has been
  tested in several in vitro models

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Binding of Cyclo (RGDfC)-targeted FITC-labeled
NPs vs. control NPs at 4C via FACS. Cys and
Cyclo(RGDfC) were conjugated to PEG (20kDa with a
maleimide functionality) that was loaded into the
core solution during NP fabrication.
RGD has affinity to integrins on vasculature
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Exocytosis of non-targeted NPs at 37 and 4 Degrees
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Interim conclusions

• Free surface amino groups can be easily employed
  for functionalization of NPs to allow for
  targeting
• Two methods were devised a physical entrapment
  onto the NP surface b covalent coupling of the
  ligand to the NP periphery
• Physical entrapment seems to be more efficient
  presentation method
• Low-affinity ligands are not much suitable for
  targeting
• The functionalization technology is easily
  adapted for a high-affinity ligands
• Dual-targeting is compatible with the present
  technology
• Ligand facilitate intracellular delivery of NPs
  and of its cargo drugs, antigens, genes
• Knowledge of NP uptake and internalization is a
  pre-requisite for successful development
• Several uptake routes exist and probably shared
  (at least 3 different)
• The functionality and efficacy of such cargo has
  been extensively tested in an in vitro models

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Part III Controlled Releasein the extracellular
niche

• Controlled release is an IP issue
• Entrapped drug could become permanently attached
  to the NP core or released slowly from a
  non-covalent Schiff-base complex
• We tested numerous compounds for their retainment
  and release
• Small drug molecules (eg, gentamycin) must be
  attached to a constitutive polymer in order to
  retain them within the NP core
• Release adjustment is feasible within the
  required bounds (eg, 1 to 30 days)

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Example of slow release In vitro
Permeability control via crosslinking (cytochrome
C)
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Example of slow release without crosslinking
Entrapment release fibroblast growth factor

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30
Cumulative release of
25
bFGF,
20
15
25C
10
5
37C
0
1.00
3.00
5.00
7.00
9.00
11.00
13.00
15.00
17.00
19.00
22.00
Time (days)
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Slow Release Effects

• Biological activity of FGF-2 released from
  nanoparticles in vitro over period of 1-7 days is
  preserved (measured in fibroblast proliferation
  test)
• Demonstrates control of drug (protein)
  permeability and ability to adjust it according
  to needs
• Many intravenous experiments in mice demonstrated
  that application is feasible and no deleterious
  effects determined (organ pathology).

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Slow release effects

• Permeability Data
• Unique chemistry slows release of entrapped
  compounds
• For crosslinking - nonimmunogenic polydextran
  aldehyde (PDA, 40 kDa) is used, non-covalent
• Second possibility is to employ non-covalent
  Schiff-base conjugate of a drug with a
  constitutive polymer (eg PMCG)
• Controlling release from such nanoparticles
  probably due to combined effect of swelling,
  diffusion from the matrix associated complex and
  hydrophobic interactions.

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Small MW drug entrapment and release

• Doxorubicin is a small molecule and has been
  permanently - covalently (or transiently)
  attached to a constitutive polymer component
• Cationic drug, PMCG, has been used (with one
  pendant amino group available per molecule)
• Alginate or chondroitin sulfate have been tested
  for a partial functionalization with drugs prior
  the NP assembly

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Interim conclusions

• Physical status of gelled NPs allow for
  slowed-down release of macromolecules
• Small MW drugs must be conjugated to constitutive
  polymers to allow their retainment and release
  control
• Transitional conjugation via the Schiff-base
  product (non-reduced) allows for efficient
  control of release rate and, often, for drug
  efficacy (tested in both in vitro and in vivo
  models)

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Part IVBiocompatibility
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Histological observations were numerous
liver
lungs
kidney
heart
spleen

• Upper panels PBS injected
• Lower panels AF750 injected (Fluorochrome
  attached to NP)

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Part VTissue and Cellular targeting
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Tumor Targeting

• General principles
• Tumor vasculature has specific cellular
  addresses recognized by peptides
• Tumor vasculature easily accessible to
  intravenous delivery.
• Drugs can be integrated with endothelial cell
  tissue-specific surface markers to induce local
  effects
• Peptide targeting permits delivery of high
  concentrations of (non-toxic) drugs within a
  tumor without affecting normal tissue.
• Targeting to tumor should elevate therapeutic
  index and thereby reduce toxicity of
  (combination) chemotherapy.

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Targeting Endothelial Cells

• Rationale
• Clear correlation between proliferation of tumor
  vessels and tumor growth and malignancy
• Differences between membrane markers on tumor and
  normal endothelial cells can be used for
  targeting
• Tumor endothelial cells accessible to delivery
• Pharmacokinetics suggest targeting tumor
  endothelial cells should give sufficient blood
  residence time for delivery to the tumor and its
  vasculature

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Targeted Delivery
Receptor
Ligand
Blood Flow
Large Pore
Lymph Flow
Anti-angiogenic peptide in nanoparticle
Small Pore
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Part VI

• In vivo data and targeting

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Passive Distribution Studies

• Nanoparticles (100-200nm mean diameter) loaded
  with 125I-labeled ovalbumin
• Particle suspension injected into the mouse-tail
  vein
• Mice sacrificed at 1 and 24h after injection.
  Organs harvested radioactivity determined by
  gamma counting
• Passive distribution into organs normally used to
  eliminate drugs and foreign bodies lungs,
  liver, spleen, etc
• Conclusion passive distribution tends to
  localize to the reticuloendothelial system (RES)
  as expected
• RES uptake presents a major impediment to
  applications of any kind of nanotechnology/deliver
  y

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Active Targeting of a Gene with TSP Fragment
(TSP521)

• TSP-521 sequence conjugated to polyethylene
  glycol to allow retention of relatively small
  targeting peptide
• Conjugate able to inhibit bFGF-stimulated 3T3
  cell proliferation in a dose-dependent fashion
• 4-5 fold increase in the amount of reporter gene
  expression in NIH-3T3 cells with TSP521-PEG
  conjugate
• TSP-521 conjugate incorporated into nanoparticles
  during fabrication
• Nanoparticulate distribution traced by
  incorporation of adenoviral luciferase vector
  into the core and corona (gene delivery)

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Active Targeting with TSP Peptide Fragment TSP521
onto a neovascular model of cancer (sponge, SPG)
SPG LNG SPL LIV HRT KID
BLR SPG LNG SPL LIV HRT
KID BLR SPG LNG SPL LIV HRT
KID BLR
Targeted particles
Non-targeted particle
Free Ad-luc adenovirus
passive
active
Tumor/background T/B ratio for many organs isgt10,
an excellent therapeutically significant result
41
Delivering to radiation-upregulated targets

• Example of combination therapy
• Example of combination of gene delivery with
  another drug (eg, doxorubicin conjugated to PMCG)

42
HVGGSSV peptide

• We are also currently testing a HVGGSSV peptide
  that is homologous to the receptor binding domain
  of angiogenin ligand which participates in
  angiogenesis and to the T-cell surface antigen
  CD5 which also binds to an endothelial receptor
• HVGGSSV peptide-nanoparticle conjugates provide
  tumor specific targeting of drug delivery to
  irradiated tumors
• HVGGSSV is to undergo Clinical trial soon
• Conjugation chemistry doesnt impair the AdV
  activity - recent results confirm biological
  activity in vitro for nanoparticle-entrapped AdV
  vector, surface-conjugated to a targeting peptide
  with EDC 2-step chemistry
• TNFerade is in phase III clinical trials now

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Radiation-inducible molecular receptor targets
for peptide-conjugate binding. We are developing
the HGDPNHVGGSSV peptide which binds to a
radiation-inducible receptor within tumor blood
vessels. Shown is brown staining of nanoparticles
binding within irradiated tumor microvasculature.
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NIR Imaging HVGGSSV peptide-PEG-NP DU145
tumor
Fluorescence imaging results indicate that tumor
binding occurred in the mice treated with a
radiation dose of 3 Gy and targeted NPs.
Biodistribution in these animals still shows
significant uptake in liver, spleen and kidneys.
Binding was 3.2 times greater in irradiated tumor
as compared to un-irradiated tumor. Optimization
is ongoing.
Targeted Non-irradiated
Targeted Irradiated
Renal elimination
Tumor accumulation
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Example of delivering cytokines into the tumor
environment to modulate T cell phenotype

• A mixture of cytokines both entrapped and
  NP-surface adsorbed for slow release
• T cell shift documented (below)
• Positive effect of shift observed on lung tumor
  shrinkage

46
(No Transcript)
47
GM-CSF-loaded NPs induce cytokine production and
shift to Th1 cytokines. Th1 and Th2 cytokines
were measured in allogeneic MLR co-cultures.
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NIR imaging is a standard method to follow the
localization and tumor status

• NPs are conveniently labeled (ligand, polymer,
  drug) to allow for visualization and fate. The
  generic chemistry allows any kind of labeling and
  cargo delivery
• NIR imaging allows better tissue penetration of
  the signal, avoiding a IR absorption outside of
  NIR spectrum
• Mechanistic studies are prerequisite for FDA
  approval
• Organ harvesting on animals are a must for
  obtaining more definitive biodistribution data

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NIR Whole Animal Imaging (passive distribution)
AF750 PEC
liver
kidney
liver
kidney
bladder
heart
bladder
heart
lungs
spleen
lungs
spleen
Saline
liver
lungs
kidney
spleen
PEC NaCl

• AF750 PMCG is incorporated into LMW PECs
• Animals injected retro-orbitally
• Longitudinal biodistribution followed by organ
  extraction at various time points
• PECs going to organs with extensive RES
  (endothelial) networks

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Interim conclusions

• Several in vivo data sets are being presented in
  order to provide proof-of-concept
• Variety of different animal and drug models are
  considered
• Simulation/modeling of pharmacokinetics allows
  faster development
• No systematic development has been undertaken to
  develop one particular drug and targeting process
• The benefits of nanovehicular delivery is due to
  intracellular delivery (not slow release and
  subsequent uptake of a drug entity)

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Part VII

• Executive summary
• Conclusions

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NanoDelivery technology Competitive Advantages

• Versatile
• Multiple drug types (small molecules, peptides,
  proteins, antigens)
• Multiple routes of administration
• Adaptable to targeted delivery
• Adaptable to required dosage regimen (dose
  timing)
• Simple Manufacturing
• No organic solvents
• Easily scaleable and adaptable to contract
  manufacturing
• Patent Position
• Unencumbered patent area covering
• Nanoparticle processing and scale-up
• Permeability control
• Targeting
• Gene transfer

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Interim conclusions

• Nanodelivery Technology competitive edge is
  presented
• Present technology can withstand a competition
  with other similar technologies because of a
  strong IP package (presented as a separate file)
• Many related technologies are described in public
  domain, but are not covered by patents
• A strong competing dendrimer technology has its
  own limitations (complexity at production,
  possible toxicity issues, delivery of largely
  hydrophobic compounds) likewise with liposomes
• Future plans are delineated how to develop it
  further with a suitable commercial partner

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Generic delivery platform Multifunctional PEC
Reporter Agent (AdV)

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Figure above Multifunctional polyelectrolyte
complex (PEC) platform. The multifunctional
polyelectrolyte complex results from minimally
two pairs of oppositely charged polymers. The
PEC core results from a high density of
interacting polymers while the shell (corona) is
developed as a function of both decreasing
polyion concentration and electrostatic
attraction. The core can passively entrap
therapeutic molecules which release from the
complex. In addition reporter agents for
magnetic resonance imaging (MRI) and
luminescence/GFP expressing adenoviral
constructs. Targeting molecules may also
PEGylated and incorporated into the core to both
allow tissue specific direction and increased
complex circulation. The corona is typically
positively charged due to excess cations carrying
primary amine groups The primary amines provide
electrostatic stabilization, in the form of
intraparticle repulsion, but can also be
functionalized with targeting moieties (e.g. a
peptide/oligomer with an affinity to heparin
sulfate receptor molecules). The cationic nature
of the PEC periphery also allows anionic
therapeutic adsorption. Steric stability is also
maintained by protruding PEG/PPO (Pluronic F-68)
groups which do not participate in assembly, but
are associated with the complex (Prokop and
Davidson, 2007).
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Part VIIIComputational Systems BiologyThere is
growing recognition in both academia and industry
that the prevailing trial an error design of drug
delivery techniques is a serious limiting factor
and mathematical modeling has been suggested as
an important tool in the design of drug delivery
protocols. Issues include the rational design of
appropriate agents, strategies for their optimal
application, and technologies for the spatial and
temporal control of their delivery to desired
sites of action for a given disease model.
Systems biology provides the methods,
computational capabilities, and
inter-disciplinary expertise to facilitate such
development.
57
The goal is to develop a therapeutic cancer
systems model, or at least show where we stand
and what else should be done in order to get
there. Although some companies claim to have such
quantitative tools, only the open literature
provides unhindered access to such scenario. As
we will see, while most of elementary
descriptions are available, the systems approach
designed for bottom-up is not available. In a
strict sense, elementary steps are defined as
unidirectional reactions (each enzyme-substrate
may have two, for each reversible direction and
any possible combination of E-S complexes,
including inhibitors, activators, etc.), based on
mass action model. Such approach is useful for
description of metabolic and signaling pathways.
Elementary events (phenomena) in the context of
this article are defined as the simplest physical
or chemical phenomena (reactions) relevant to
each level of hierarchy that describes the whole
organism behavior.
58
We define Systems Biology as quantitative,
postgenomic, postproteomic, dynamic, multi-scale
physiology. Historically, biologists have been
able to focus on one component of a biological
system at a time (e.g., a gene or a protein),
with the expectation that knowledge of the
individual components will eventually enable an
understanding of the entire system. As a result,
individual data are often divorced from the
context of the entire system the functioning
organism. Systems Biology attempts to define
relevant global properties, relations, and
functions of biological systems. Others have used
different terms, including organismic system,
emergent characteristics, emergent (systems)
properties or systemic variables. By making
systematic perturbations (using inhibitors,
activators, changes in external signals, etc.)
and measuring global responses only, one can
discover a network interaction map that can
be expressed in terms of module-to-module
connection strengths. The global network response
to a signal or experimental perturbation can be
predicted and expressed in terms of the
individual (local) responses by using a map of
network connections. The key is to obtain both
the structural (modular, topological) and
functional information. The same reasoning
applies to cancer which could be considered as
another systems biology problem. In the
following, we will briefly review available
elementary steps in terms of availability of
quantitative tools and emergent properties
relevant to cancer biology and its treatment.
59
An example of EP properties at tumor (at the
subcellular level) are proliferation (cancer),
differentiation, apoptosis, etc.  This figure
illustrates a simplified case to be solved by
interrogation. Here the objectives (i) to
discover and identify the actual crosstalk
effects (at the horizontal level) of largely
vertical signaling pathways by means of CSB
(based on huge dynamic data available from
biologists (2) to discover and validate
effective therapies, based on multiple inhibition
of (blocking, knocking out, etc.) the harmful
processes and/or promoting (inducting) the useful
ones. This approach is useful for metabolic,
signaling and transcriptional pathways. The
crosstalk at higher hierarchical levels may
involve interactions between the cells/tissues
and environment (diffusion, mass transfer, etc.)
60
Table 5 List of hierarchical levels and
elementary steps (modular units) relevant to
drug delivery and cancer therapy with
corresponding quantitative models. Prokop and
Davidson JPS 2008
Hierarchy Elementary phenomena and models Description and reference(s)
Drug and Polymer Molecular level properties of drugs (small molecule species, macromolecular drugs, gene vectors, imaging agents) structure, solubility in water and lipid environments, adsorption In415, 416, 417, 418
Drug and Polymer Molecular level properties of constitutive delivery polymers In419
Drug and Polymer Modeling of associative (self-assembling) properties of drugs and polymers In420
Drug and Polymer Transport properties of drugs via lipid structures In421
Drug and Polymer Transport (controlled-release) properties of polymeric-drug superstructures, including hydrogel constructs In422
Drug and Polymer Molecular modeling of in vitro receptor-ligand interaction In423
Subcellular Genetic control model In424, 425
Subcellular Elementary model of cancer metabolism In426-431 cancer stem cells432-433
Subcellular Signaling pathway models In433b, 434-439, 413
Subcellular Models of nanovehicle uptake, trafficking, degradation and efflux Analytical model of nanovehicle ligand-induced internalization441-442, 442b
Cellular Nutrient and oxygen effects Compartmental (subcellular) analysis of nutrient influx and efflux443
Cellular Radiation response In444, 445
Cellular Response to chemotherapy In446-448
Cellular Models of combination therapy In449-451
Cellular Models of cell cycle In452
Cellular Models of tumor invasion and metastasis In453, 454
Cellular Models of hematopoiesis In455
Cellular Capillary network growth In456, 457
Cellular Models of cell growth, quiescence and apoptosis In458-460
Cellular Models of nanovehicle/cell interaction ligand-mediated targeting models In460b Folate targeting of liposomes462 optimal tumor targeting by antibodies463
61
Multicellular/Tissue Nutrient and vehicle/drug transport convective interstitial transport Tumor blood perfusion and oxygen transport464 vascular transport permeable vs. non-permeable capillaries465 tumor spheroid penetration by antibody466 hypoxia model467 interstitial transport468
Multicellular/Tissue Interaction with RES In469
Multicellular/Tissue Interaction with immune system In470
Multicellular/Tissue Interaction within the vascular system (EPR effect) In471
Multicellular/Tissue Interaction with hematopoietic system In455
Multicellular/Tissue Interaction with lymphatics In472
Multicellular/Tissue Physiologically-based pharmacokinetic models compartmental analysis and biodistribution Tumor uptake of antibodies compartmental analysis473, 474 first-pass model475,-477 pharmacokinetic cancer model34
Systems model Solving large-scale, multi-scale metabolic and signaling models coupled with upper system boundary conditions Dynamic cancer network inference model478-480 network model481
Systems model Cancer as a systems disease The most comprehensive models yet available, still very far from ideal situation414, 482, 483
Systems model Cancer systems diagnostics In484
Systems model Cancer systems epidemiology In485
Systems model Bottlenecks in big Pharma and Biotech industries discovery and development Systems biology in drug discovery486
62
Table 6 Identification of possible emergent
phenomena for comprehensive, quantitative cancer
treatment model/drug delivery from Prokop and
Davidson JPS 2008
Level of hierarchy Emergent phenomena

Subcellular Elementary cancer metabolic and signaling quantitative model
Subcellular Elementary model of nanovehicular uptake, targeting, internalization and trafficking
Cellular Cell proliferation vs apoptosis and differentiation Model of tumor invasion and metastasis
Cellular Model of capillary network growth
Tissue Comprehensive pharmacokinetic model
Organism/Systems Comprehensive model of cancer as a systems disease
63
The goal of CSB is to identify emergent
properties and build a THERAPEUTIC DISEASE MODEL.
In our case, a minimal cancer model as a starting
point for more comprehensive, all inclusive model
which would include all levels of complexity of
events involved in cancer initiation, progression
and treatment. Computational network multi-scale
modeling can make predictions that challenge
assumptions and motivate further experimental
efforts. The cycle of model building and
hypotheses testing will lead to a deeper
understanding of metabolic/disease state. The
inclusion of multivariate dependencies among
molecules of complex network can potentially be
used to identify combinatorial targets for
therapeutic interventions and drug delivery. The
challenge is to integrate all of the relevant
knowledge and data in a systematic way to devise
the best therapeutic and diagnostic strategies.
The basic tool is an interrogation of an in
silico model and seek answers. The present
biology cannot handle complicated multivariate
cause-effect relationships
64

• Take home messages
• Nanodelivery methods can open/widen a therapeutic
  window to enable intracellular delivery of agents
• Computational Systems Biology can enhance our
  ability to detect new therapeutic targets and
  rationalize/organize biological data

65
We acknowledge the support of the National
Institutes of Health Grant 1R01EB002825-01
(J.M.D. and A.P) and support from the Department
of Veterans Affairs (J.M.D.) Key
References Hartig S.M., Greene R., Dikov M.M.,
Prokop A., Davidson J.M. Multifunctional
nanoparticulate polyelectrolyte complexes, Pharm
Res 24 2353-2369 (2007) Prokop A, Davidson JM.
Nanovehicular intracellular delivery systems. J
Pharm Sci. 2008 Jan 15 Epub ahead of print