Professor Ales ProkopResearch Professor:

Vanderbilt University Department

of Chemical Engineering

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 Sables90, av. Des Jardins

Orford (Quebec) J1X 6M6April 1-4, 2008

This presentation will provide an

1.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. 2.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

• NanoDelivery’s 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

Part I: Overview of NanoDelivery technology

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.

Delivery Vehicles

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)

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

Nanoparticles

NP Production and Molecular Characteristics

• Hypothesis: Precursors with similar molecular weights, (LMW), will yield:

– Size less than 150 nm: ideal for cellular uptake

– ZP>30 mv or ZP<-30 mV: colloidal stability (also important, together with hydrophobicity, for NP localization: cytoplasmic vs nuclear)

Component

Poly-[Methylene-co-Guanidine](PMCG)Calcium Chloride

Spermine Tetrahydrochloride

HMW

LMW

Anion

Cation

Precursor MW(Da)

HMW, HV Sodium Alginate

Cellulose Sulfate

Chondroitin Sulfate

LMW, LV Sodium Alginate

460000

1200000

15000

12000

348

111

5000

Music City Nanoparticles

CS

Corona(Shell)PMCG, spermine, Ca++, and Pluronic F-68

CS/PMCG

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

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

Importance of PEC Size• Subcellular size allows penetration into

tissues• Internalization is driven by endocytosis

– Concentration, time-dependent– Saturable– Preceded by cytoskeletal rearrangement

NUCLEUS

CYTOPLASM

Mechanism size

(nm)

phagocytosis 1000

macropinocytosis 250

clathrin-mediated 120

caveolin-mediated 70

clathrin/caveolae independent 50

Optimal size should be between 10 and 120 nm:

NP > 10 nm to avoid single-pass renal clearanceNP<120 to avoid capturing by RES

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

Anionic solution with therapeutic

Ultrasonic dispergator: power source

Oscillating tip

Cationic solution

Receiving bath

Moderate stirring

Batch Processing

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 <100nm• Small size important for avoiding RES interaction• Cationic charge on periphery allows for further

functionalization• Production is easily scaleable and amenable for aseptic

operation

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

PEC Rapid Binding and Uptake

• HMVEC exposed to fixed PEC concentration for 2 h

• Visualization by confocal microscopy

surface inside

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Mechanism of uptake: Observations: LMW PECs and Endothelial Cells

• PEC physicochemistry in cell growth media

– Size: 235.9 nm±30.5 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

• Inhibitors+PEC size==>macropinocytosis 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

TSP521 Modified PECs by EDAC/NHS:low-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

H H

NH NH

p521 (Asp-COOH) +

NH2

PECEDAC

NHS

NH

PEC

p521 (Asp-C)

O

Active site

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

PEGp521 + Anions + Cations

NH2

PEC

Active

(PEG)20000

p521

PEG presentation is often more efficient and physiologic (flexible PEG linkage)

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

Binding of Cyclo (RGDfC)-targeted FITC-labeled NPs vs. control NPs at 4°C 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 integrinson vasculature

Exocytosis of non-targeted NPs at 37 and 4 Degrees

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Time (min)

MFI

37 Degrees Total

37 Degrees Internalized

4 Degrees Total

4 Degrees Internalized

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

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)

Permeability control via crosslinking (cytochrome C)

Example of slow releaseIn vitro

Entrapment & release: fibroblast growth factor

Example of slow release without crosslinking

Figure 4: In vitro cumulative release of radio labeled FGFb in PBS. Nanoparticle chemistry - Core: 0.05% alginate, 0.05% cellulose sulfate, ovalbumin 1.8%; Shell: 0.05% spermine, 0.075% PMCG, 0.05% CaCl2,

1% F-68. C/S = 2/20 (ml/ml). Not crosslinked.

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• 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).

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.

Slow release effects

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

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)

Part IV

Biocompatibility

Histological observations were numerous

Upper panels: PBS injected

Lower panels: AF750 injected (Fluorochrome attached to NP)

liver lungs kidney heart spleen

Part V

Tissue and Cellular 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.

Tumor Targeting

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

Targeting Endothelial Cells

Targeted DeliveryTargeted Delivery

Blood FlowBlood Flow

Small PoreSmall Pore

Large PoreLarge Pore

Lymph FlowLymph FlowAnti-angiogenic Anti-angiogenic peptide in peptide in nanoparticlenanoparticle

LigandLigand

ReceptorReceptor

Part VI

In vivo data and targeting

• Nanoparticles (100-200nm mean diameter) loaded with Nanoparticles (100-200nm mean diameter) loaded with 125125I-labeled ovalbuminI-labeled ovalbumin

• Particle suspension injected into the mouse-tail veinParticle suspension injected into the mouse-tail vein

• Mice sacrificed at 1 and 24h after injection. Organs Mice sacrificed at 1 and 24h after injection. Organs harvested; radioactivity determined by gamma countingharvested; radioactivity determined by gamma counting

• Passive distribution into organs normally used to eliminate Passive distribution into organs normally used to eliminate drugs and foreign bodies : lungs, liver, spleen, etcdrugs and foreign bodies : lungs, liver, spleen, etc

• Conclusion:Conclusion: passive distribution tends to localize to the passive distribution tends to localize to the reticuloendothelial system (RES) as expectedreticuloendothelial system (RES) as expected

• RES uptake presents a major impediment to applications RES uptake presents a major impediment to applications of any kind of nanotechnology/deliveryof any kind of nanotechnology/delivery

Passive Distribution StudiesPassive Distribution Studies

• TSP-521 sequence conjugated to polyethylene glycol to TSP-521 sequence conjugated to polyethylene glycol to allow retention of relatively small targeting peptideallow retention of relatively small targeting peptide

• Conjugate able to inhibit bFGF-stimulated 3T3 cell Conjugate able to inhibit bFGF-stimulated 3T3 cell proliferation in a dose-dependent fashionproliferation in a dose-dependent fashion

• 4-5 fold increase in the amount of reporter gene expression 4-5 fold increase in the amount of reporter gene expression in NIH-3T3 cells with TSP521-PEG conjugatein NIH-3T3 cells with TSP521-PEG conjugate

• TSP-521 conjugate incorporated into nanoparticles during TSP-521 conjugate incorporated into nanoparticles during fabricationfabrication

• Nanoparticulate distribution traced by incorporation of Nanoparticulate distribution traced by incorporation of adenoviral luciferase vector into the core and corona (gene adenoviral luciferase vector into the core and corona (gene delivery)delivery)

Active Targeting of a Gene Active Targeting of a Gene with TSP Fragment with TSP Fragment

(TSP521)(TSP521)

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1000

Luciferase expression/Total protein

Targeted particles Non-targeted particle Free Targeted particles Non-targeted particle Free Ad-luc adenovirus Ad-luc adenovirus

SPG LNG SPL LIV HRT KID BLRSPG LNG SPL LIV HRT KID BLR SPG LNG SPL LIV HRT KID BLR SPG LNG SPL LIV HRT KID SPG LNG SPL LIV HRT KID BLR SPG LNG SPL LIV HRT KID BLRBLR

Active Targeting with TSP Peptide Fragment Active Targeting with TSP Peptide Fragment TSP521 onto a neovascular model of cancer (sponge, SPG)TSP521 onto a neovascular model of cancer (sponge, SPG)

passivepassiveactiveactiveTumor/background T/B ratio for many organs is>10,

an excellent therapeutically significant result

Delivering to radiation-upregulated targets

• Example of combination therapy

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

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 doesn’t 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

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.

NIR Imaging: HVGGSSV peptide-PEG-NP & DU145 tumor

Targeted & Non-irradiated Targeted & Irradiated

Renal elimination Tumor accumulation

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.

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

GM-CSF-loaded NPs induce cytokine production and shift to Th1 cytokines. Th1 and Th2 cytokines were measured in

allogeneic MLR co-cultures.

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

NIR Whole Animal Imaging (passive distribution)

lungsspleen

bladderheart

liverkidney

liver lungs kidney spleen

AF750 PEC

Saline

lungs spleen

bladderheart

liver kidney

PEC NaCl

AF750 PMCG is incorporated into LMW PECsAnimals injected retro-orbitallyLongitudinal biodistribution followed by organ extraction at various time pointsPECs going to organs with extensive RES (endothelial) networks

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tal

Flu

x x1

07 (

p/s

) t=3 ht=6 ht=24 ht=48 h

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)

Part VII

• Executive summary

• Conclusions

• 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

NanoDelivery technology Competitive Advantages

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

Generic delivery platform: Multifunctional PEC Generic delivery platform: Multifunctional PEC

PEC Core

PEG Coupled Targeting Moiety

MRI Imaging Agent(e.g. gadolinium polymer)

++ +

+

+

+++

Cationic Head for Molecular Target and Adsorption of Therapeutics

+

Steric Stabilizer (PEG/PPO Coat)

Reporter Agent

(AdV)

Therapeutic Molecule(released from core)

PEC Shell (Corona)

Cellular Receptor

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).

Part VIIIComputational Systems Biology

There 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.

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.

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.

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.)

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

Molecular level properties of constitutive delivery polymers In419

Modeling of associative (self-assembling) properties of drugs and polymers In420

Transport properties of drugs via lipid structures In421

Transport (controlled-release) properties of polymeric-drug superstructures, including hydrogel constructs

In422

Molecular modeling of in vitro receptor-ligand interaction In423

Subcellular Genetic control model In424, 425

“Elementary” model of cancer metabolism In426-431; cancer stem cells432-433 Signaling pathway models In433b, 434-439, 413

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

Radiation response In444, 445

Response to chemotherapy In446-448

Models of combination therapy In449-451

Models of cell cycle In452

Models of tumor invasion and metastasis In453, 454

Models of hematopoiesis In455 Capillary network growth In456, 457

Models of cell growth, quiescence and apoptosis In458-460

Models of nanovehicle/cell interaction; ligand-mediated targeting models In460b; Folate targeting of liposomes462; optimal tumor targeting by antibodies463

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

Interaction with RES In469

Interaction with immune system In470

Interaction within the vascular system (EPR effect) In471

Interaction with hematopoietic system In455

Interaction with lymphatics In472

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

Cancer as a systems disease The most comprehensive models yet available, still very far from ideal situation414, 482, 483

Cancer systems diagnostics In484

Cancer systems epidemiology In485

Bottlenecks in big Pharma and Biotech industries: discovery and development Systems biology in drug discovery486

Level of hierarchy Emergent phenomena

Subcellular Elementary cancer metabolic and signaling quantitative modelElementary model of nanovehicular uptake, targeting, internalization and trafficking

Cellular Cell proliferation vs apoptosis and differentiation & Model of tumor invasion and metastasisModel of capillary network growth

Tissue Comprehensive pharmacokinetic model

Organism/Systems Comprehensive model of cancer as a systems disease

Table 6 Identification of possible emergent phenomena for comprehensive, quantitative cancer treatment model/drug delivery; from Prokop and Davidson JPS 2008

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

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

We acknowledge the support of the National Institutes ofHealth Grant 1R01EB002825-01 (J.M.D. and A.P) and supportfrom 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]