appendix 5 micro- and nano- particle synthesis and processing...

Appendix 5 Micro- and Nano- Particle

Synthesis and Processing for

Pharmaceutical, Biomedical, and Food

Applications (Part 3)

Chi-Hwa Wang

Department of Chemical and Biomolecular Engineering, National

University of Singapore, 4 Engineering Drive 4, Singapore,

117585, Singapore. E-mail: [email protected].

Computational fluid dynamics simulations

for drug delivery systems

Chi-Hwa Wang1,2

1 Department of Chemical and Biomolecular Engineering, National University of

Singapore, 4 Engineering Drive 4, Singapore 117576

2 Molecular Engineering of Biological and Chemical Systems, Singapore-MIT

Alliance, 4 Engineering Drive 3, Singapore 117576

Confocal fluorescence images of C6 glioma cells incubated 1 hour withcoumarin6-loaded PLGA particles (200-300nm).

Introduction

• Cancer is the number one killer in Singapore since 1996.

• Conventional post-surgery therapies for brain tumors:

Radiation & Intravenous chemotherapy.

Both methods are ineffective due to:

• Elevated interstitial pressure in the tumor center (Baxter & Jain 1989)

• Blood Brain Barrier

A novel way is the controlled drug release using polymers implanted into patients after the

surgery. Gliadel Wafers approved by FDA in 1996

Manufactured by Guilford Pharmaceuticals. Carmustine loaded polyanhydride

polymer (PCPP:SA)

6 months survival rate improved by up to 60%.

• This provides potential benefits of reduced overall toxicity to the entire body and improved survival rate.

Objectives

Current research aims at primarily:

• Developing a simulation platform which uses an engineering approach towards understanding the delivery transport mechanism.

• To derive the transient flow field that occurs after wafer implantation.

• Using simulation to study how wafer’s placement, its release profile, loading and other parameters will affect the efficiency of medical treatments.

Establishing a simulation platform, which will optimize key process

parameters to help surgeons in executing a successful treatment.

Ultimate Aim

Chem. Eng. Sci., 53(20), 3579-3600 (1998).

J. Controlled Release,

61 21-41 (1999).

Temporal variation of

BCNU concentration

profiles:

(a) core implantation,

(b) tumor implantation

(c) systemic bolus

injection.

J. Controlled Release,

61 21-41 (1999).

Chem. Eng. Sci., 53(20), 3579-3600 (1998).

Chem. Eng. Sci., 53(20), 3579-3600 (1998).

Distribution of velocity and drug concentration

J. Controlled Release, 61 21-41 (1999).

Methodology

1. Construct a brain tumor geometry consisting of cavity (with wafers implanted), tumor and normal tissue zones.

2. Solving the transport equations of mass, momentum and species (drug), using Computational Fluid Dynamics Simulation to obtain a steady state condition prior to surgery.

3. Perturbing the steady state solution to simulate the transient effects:

a) assess the fluid flow pattern and its effects on the drug delivery

b) assess how different release profiles affect the efficacy of delivery

3D-Simulation of Enclosed Tumor

Model geometry developed

for the 3D simulation

incorporating 8 wafers and

the effect of gravity. The

table below shows that 2D

results are qualitatively

similar to 3D case. Gravity

does not introduce

significant change in the

flow field of the surgical

cavity.

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient Interstitial Fluid Flow", Chem. Eng. Sci., 60, 4803-4821

(2005).

Post-surgery Chemotherapy and

Radiotherapy

3-D Computational Geometry Pressure Distribution

Model GeometryC (cavity),T (tumor), N (normal

tissues), W (wafers)

1,2,3 – boundaries between

wafers and cavity

1, 2 – internal boundaries

3 – external boundary of

tissue.

Constructed from actual magnetic

resonance images

Governing Equations (Continued)

Adapted from Curry F E, Mechanics and thermodynamics of transcapillary

exchange in Handbook of Physiologyst, 4, 320-327, 1984, Saltzman & Radomsky,

Drugs released from Polymers: Diffusion and Elimination in Brain Tissue, Chem.

Eng. Sci. 1990, Loo T L et al., The Antitumor Agent, 1,3-Bis(2-chloroethyl)-1-

nitrosurea, J. Pharm Sci.,55, 5, 1966.

elsewhere0

tissuesnormalandtumorin

cavityin

cavityin0

tissuesandtumorin1

1

waferin/

Ck

Ck

R

e

PeCC

V

PSCF

eS

F

e

c

Pe

vvvv

t

o

sv

Steady State Fluid Profile

• A solution of the pressure and velocity profile is obtained prior to wafer implantation. This is the initial condition from which the transient profile can be derived.

• Simulation results show:

• High central interstitial pressure (1.2 kPa) agreeable with that of Baxter and Jain (1989).

• Outward flow of interstitial fluid which is detrimental to treatment based on systemic administration.

Bi-directional flow of fluid

(akin to that obtained in

the 2D simulation) in the

tumor zone at a cut section.

The tissue and tumor zones

are depicted by red and

gray meshes, respectively.

Preferential flow of

interstitial fluid around the

wafers (depicted by green

mesh) which is much less

permeable than the surgical

gel filling the cavity. This is

obtained at a cut section

midway in the z-direction.

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of

Drug Delivery to Brain Tumors, Effects of Transient

Interstitial Fluid Flow", Chem. Eng. Sci., 60, 4803-4821

(2005).

0.E+00

1.E-06

2.E-06

3.E-06

4.E-06

5.E-06

6.E-06

0.0 0.3 0.6 0.9 1.2 1.5

Time (hour)

Velo

cit

y (

m/s

)

0

200

400

600

800

1000

1200

Pre

ssu

re (

Pa)

Velocity

Pressure

6.0E-9

8.0E-9

1.0E-8

1.2E-8

1.4E-8

1.2 1.3 1.4 1.5

Transient Flow Field

Transient variation of pressure and velocity in the cavity zone:

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient Interstitial Fluid Flow", Chem. Eng. Sci., 60, 4803-4821

(2005).

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient

Interstitial Fluid Flow", Chem. Eng. Sci., 60, 4803-4821 (2005).

Chemotherapy for Brain Tumor

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient Interstitial Fluid

Flow", Chem. Eng. Sci., 60, 4803-4821 (2005).


C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient

Interstitial Fluid Flow", Chem. Eng. Sci., 60, 4803-4821 (2005).


C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang, "Simulation of Drug Delivery to Brain Tumors, Effects of Transient Interstitial Fluid Flow", Chem. Eng. Sci., 60,

4803-4821 (2005).

3D-Simulation of Enclosed Tumor

Model geometry developed

for the 3D simulation

incorporating 8 wafers and

the effect of gravity. The

table below shows that 2D

results are qualitatively

similar to 3D case. Gravity

does not introduce

significant change in the

flow field of the surgical

cavity.

Cavity Tumor Normal Tissue

3D1 3D2 2D 3D1 3D2 2D 3D1 3D2 2D

Pressure

(kPa)

1.0 1.0 1.1 1.0 1.0 1.1 0.90 0.90 0.95

Velocity (m/s)

5 x 10-9

4 x 10-9

7 x 10-9

2 x 10-10

2 x 10 -10

2 x 10-10

1 x 10-10

1 x 10-10

3 x 10-10

The superscripts 1 and 2 refer to gravity in the z (as shown in above figure) and x directions, respectively.

C.S. Teo, K.H. Tan, T. Lee, and C.H. Wang,

"Simulation of Drug Delivery to Brain Tumors,

Effects of Transient Interstitial Fluid Flow",

Chem. Eng. Sci., 60, 4803-4821 (2005).

Temporal Evolution of Drug

Concentration

Tumor Wafer

Drug distribution at a cut

section in the z-direction

with partial display of the

wafers for clearer

visualization. (Time = 20

hours)

Distribution of drug in the

wafers.

K.H. Tan, F.J. Wang, T. Lee and C.H. Wang, “Delivery

of Etanidazole to Brain Tumor from PLGA Wafers: A

Double Burst Release System”, Biotechnology and

Bioengineering 82(3), 278-288 (2003).

0

2

4

6

8

10

12

0 15 30 45 60 75Time (day)

Th

era

pe

uti

c I

nd

ex

A

B

0

2

4

6

8

10

12

14

16

0 15 30 45 60 75Time (day)

Pe

ne

tra

tio

n D

ista

nc

e (

mm

)

B

A

Legend:

(A) Linear release

(B) Double burst

As shown in these figures,

linear release devices

achieve better therapeutic

index and penetration

depth (14 mm) than its

double burst counterpart.

K.H. Tan, F.J. Wang, T. Lee and C.H. Wang, “Delivery of Etanidazole to Brain Tumor from PLGA Wafers: A Double Burst Release

System”, Biotechnology and Bioengineering 82(3), 278-288 (2003).

0.0E+00

2.0E-09

4.0E-09

6.0E-09

8.0E-09

1.0E-08

1.2E-08

0 15 30 45 60 75

Time (day)

Co

nc

en

tra

tio

n (

mo

l/c

m3) A

B

However, in comparison with a double release wafer (B), linear release (A)

faces:

• a delay of several days in the tumor attaining therapeutic threshold level

(represented by dashed line in Fig LR-2). This is crucial to killing the

malignant cells.

• accumulation of drug concentration leading to increasing drug toxicity

towards later stages of treatment.

Fig

ure

LR

-2

K.H. Tan, F.J. Wang, T. Lee and C.H. Wang, “Delivery of Etanidazole to Brain Tumor from PLGA Wafers: A Double Burst Release

System”, Biotechnology and Bioengineering 82(3), 278-288 (2003).

2

T

N

C

1

3

N1

N2

N3

1 mm

W1

1

C/T

C/N

E

B

AF

Open Tumor: Transient Variations

Model Geometry used for open tumor

simulation

0.0E+00

1.0E-10

2.0E-10

3.0E-10

4.0E-10

5.0E-10

6.0E-10

7.0E-10

8.0E-10

9.0E-10

1.0E-09

0.00 0.20 0.40 0.60 0.80 1.00Time (hour)

Ve

locit

y (

m/s

)

550

600

650

700

750

800

850

900

950

1000

1050

1100

1150

1200

Pre

ssu

re (

Pa

)

Pressure

Velocity

Transient variation of

velocity and pressure in

the tumor zone,

summarizing the

developing transient

profiles of the open

tumor.

K.H. Tan, T. Lee, and C.H. Wang, “Simulation

of Intra-tumoral Release of Etanidazole: Effects

of the Size of Surgical Opening”, J. Pharm. Sci.

92(4) 773-789 (2003).

At the onset, fluid flows into

the cavity zones, causing a

pressure depression in all

zones.

However, the high

interstitial central pressure

which is crucial for efficient

drug delivery is never

restored, undermining the

efficacy of the treatment.

Pressure slowly equilibrates

leading to a bi-directional flow

of fluid in the tumor zone

which persisted for the

remaining part of the

simulation.

(All units in Pa) K.H. Tan, T. Lee, and C.H. Wang, “Simulation of Intra-tumoral

Release of Etanidazole: Effects of the Size of Surgical Opening”,

J. Pharm. Sci. 92(4) 773-789 (2003).

Velocity vector plot showing the

leakage of interstitial fluid in the

newly-attained steady state. Such

leakage causes uneven drug

distribution as well as transporting

the drug through the opening.

(Units in m/s)

Open Tumor: Effects on Treatment Efficacy

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.00 0.50 1.00 1.50 2.00 2.50 3.00Time (hr)

Ra

tio

(

/P

e)

0

2

4

6

8

10

12

14

16

18

20

Ra

tio

(P

e)

Pe

/Pe j j

Temporal variation of the normalized

ratio of Pe and j/Pe in the Cavity.

Ratio(j/Pe) is defined as (j/Pe)op/(j/Pe)cl

and Ratio(Pe) is defined as (Pe)op/(Pe)cl,

where the subscripts “op” and “cl” refer

to the open and enclosed tumor

respectively. The opening has led to

increased convective effect.

K.H. Tan, T. Lee, and C.H. Wang, “Simulation of Intra-tumoral Release of

Etanidazole: Effects of the Size of Surgical Opening”, J. Pharm. Sci. 92(4)

773-789 (2003).

0.0E+00

5.0E-09

1.0E-08

1.5E-08

2.0E-08

2.5E-08

3.0E-08

3.5E-08

4.0E-08

4.5E-08

5.0E-08

0 5 10 15 20% Opening

Mass L

oss (

kg

/s)

0.E+00

1.E-09

2.E-09

3.E-09

4.E-09

5.E-09

6.E-09

7.E-09

8.E-09

Velo

cit

y (

m/s

)

3.64E-10 kg/s

Mass Loss

Velocity

Open Tumor: Effects of Opening Sizes

Drug contour plot showing the

uneven drug distribution in the

tumor zone due to the tumor

opening.

0

200

400

600

800

1000

1200

0.00 0.25 0.50 0.75 1.00 1.25 1.50

Time (Hr)

Pre

ss

ure

(P

a)

Closed

3.75%

6.19%

11.98%

17.99%

Transient variation of pressure in the

cavity due to different opening sizes

Mass loss and fluid flow velocity through the

opening with varying opening sizes

Mass

fraction

K.H. Tan, T. Lee, and C.H. Wang, “Simulation of Intra-tumoral Release of Etanidazole: Effects of the Size of Surgical Opening”, J. Pharm. Sci. 92(4)

773-789 (2003).

Design Strategy

• The double concentration peaks suggested that new formulation strategies are required to optimize the treatment against brain tumor.

Controlled Release of Etanidazole From

Double Walled Microspheres

Fabrication involves a hybrid process that incorporates phase separation

phenomenon when two polymer solutions were mixed and solvent

evaporation. Hence, microspheres with two distinct polymer layers were

formed in the process and were dried through solvent evaporation.

Water + Poly Vinyl Alcohol

(PVA)

Ultrasonication

Solvent Evaporation

Filtration + Freeze Drying

PLGA

Etanidazole + DCM

Ultrasonication

PLLA + DCM

Consistent and reproducible drug loaded double walled microspheres

has been produced in the study. It has also been successful in

manipulating the thickness of the shell wall and core diameter

through the control of the mass ratio of the two polymers. (i.e.

PLLA/PLGA)

A: PLLA/PLGA 1:1; B,C: PLLA/PLGA 2:1; D: PLLA/PLGA 2.5:1

A B

C D

T.H. Lee, J.J. Wang and C.H. Wang.

“Double-walled Microspheres for

Sustained Release of Highly Water

Soluble Drugs: Characterization and

Irradiation Studies”, J. Controlled

Release, 83, 437-452 (2002).

SEM showing microspheres with dissolved cores, ascertained that the core

was made up of PLGA while the shell of PLLA. A: PLLA/PLGA 2:1; B:

PLLA/PLGA 1:1.

•Differentiation by Solubility

PLGA is soluble in organic solvent Ethyl Acetate while PLLA is not. By

dissolving the cross sectional cuts of the microspheres and observing the

resultant structure, the configuration of the 2 polymers in the microspheres can

be determined.

A B

T.H. Lee, J.J. Wang and C.H. Wang. “Double-walled Microspheres for

Sustained Release of Highly Water Soluble Drugs: Characterization and

Irradiation Studies”, J. Controlled Release, 83, 437-452 (2002).

In Vitro Release: With Irradiation

50 Gy

0 Gy

30 kGy

14 days

t50

T.H. Lee, J.J. Wang and C.H. Wang.

“Double-walled Microspheres for

Sustained Release of Highly Water

Soluble Drugs: Characterization and

Irradiation Studies”, J. Controlled

Release, 83, 437-452 (2002).

Transcatheter oily chemoembolizationTreatment Procedure

Liver

Hepatoma

Tube

Majorartery

TubeHepatoma

Doxorubicin droplets

Blood capillaries

Maximum interstitial pressure occurs in the core, reaching a value of 1.55 kPa, in contrast to the value of 1.53 kPa reported by Baxter and Jain (1989)

Radially outward fluid velocity

Pressure and VelocityDistribution

0 153 307 460 613 766 920 1070 1230 1380 1530

(Pa)

Hepatoma

Drug Concentration

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0 2 4 6 8 10 12 14 16 18 20

t (h)

(kg/m3)

Tumor

Core

Tissue

i C

Baseline case:

Hepatoma

F.Y.M. Goh, H.L. Kong, and C. H. Wang, “On the Delivery of Doxorubicin to Hepatoma”,

Pharmaceutical Research, 18(6) 761-770 (2001).

1 minute

kg/m3

Hepatoma



15 minutes

kg/m3

Hepatoma



30 minutes

kg/m3

Hepatoma



1 hour

kg/m3

Hepatoma



Hepatoma

Effect of S/V Ratio

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2 4 6 8 10 12 14 16 18 20

t (h)

Tumor

Core

tissue

0CC /

Lower S/V ratio:



Varying injection volume does not alter amount and distribution of drug significantly

Changing dosage leads to corresponding change in drug concentration

- high dosage gives high concentration in tumor- low dosage gives lower toxicity in tissueoptimal dosage can be found

Lower vascular exchange area leads to lower concentration

Lymphatic drainage in tumor does not result in significant decrease in concentration

Cellular metabolism reduces drug concentration

Summary

Computer Simulation of Delivery

of Gentamicin to Bone

for The Treatment of Osteomyelitis

Osteomyelitis: bone infection commonly

caused by Staphylococcus aureus.

Present treatment involves the use of

antibiotics impregnated in

polymethylmethacrylate (PMMA) beads.

Problem: PMMA beads are non-

biodegradable.

Proposed solution: Biodegradable drug

disc.

PMMA beads

Implantation of PMMA

beads into the tibia

In vivo results

6-week PMMA PLGA disc

Bone formation after a period of 6-weeks

PMMA beads removed after 2-weeks to allow

for tissue growth before PLGA discs are

implanted

PLGA discs being implanted in rabbit femur.

P.K. Naraharisetti, C.G. Lee, Y.C. Fu, D.J. Lee, and C.H. Wang “In Vitro and In Vivo Release of Gentamicin from Biodegradable Discs”, Journal of

Biomedical Materials Research: Part B: Applied Biomaterials, 77B, 329-337, (2006).

Geometry used for simulation

Drug disc dimension: 5 mm diameter, 7 mm length

Surgical opening dimension: 10 mm by 5 mm

Surgical

Opening

(clot)

Marrow

Drug disc

Cortical bone

Periosteum

A

Marrow

Drug

Disc

xy-plane

Results I (Baseline Simulation)

Time = 10 min Time = 1 hour Time = 1 day

1500 Pa 0 Pa

Pressure contour for the yz-plane at different time.

1.27 x 10-1 m/s 2.89 x 10-8 m/s

Velocity vector for the yz-plane at t = 10 min

10 min 1 hour 1 day

C.G. Lee, YC Fu, and C.H. Wang, “Simulation of

Gentamicin Delivery for the Local Treatment of

Osteomyelitis”, Biotechnology and Bioengineering,

91, 622-635 (2005).


10 mins 1 hr

1 day 10 days

20 days 40 days

Change in gentamicin concentration with time (yz-plane):

(Coloured regions have concentration to bacteria MIC)

927 mg/ml 0.25 mg/ml

C.G. Lee, YC Fu, and C.H. Wang, “Simulation of Gentamicin Delivery for the Local Treatment of

Osteomyelitis”, Biotechnology and Bioengineering, 91, 622-635 (2005).


Mean gentamicin concentration in different region

Drug concentration rises

to a maximum 2 days after

implantation before

decreasing exponentially.

Decrease in concentration

is brought about by a

decrease in drug flux with

time and systemic

circulation serving as a

drug sink.

Pressure induced

convective transport also

results in rapid clearance

of drug through surgical

opening initially.

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

0 10 20 30 40 50

Time (Day)

Co

nc

(m

g/m

l)

marrow

clot

cortical bone

C.G. Lee, YC Fu, and C.H. Wang, “Simulation of Gentamicin Delivery for the Local

Treatment of Osteomyelitis”, Biotechnology and Bioengineering, 91, 622-635 (2005).

Results II (Comparison with PMMA beads)

0%

20%

40%

60%

80%

100%

0 20 40 60 80 100Time (Day)

Re

lea

se

of

ge

nta

mic

in (

%)

Experimental

Fitted Curve

Source: Wahlig et. al, The Release Of Gentamicin From

Polymethylmethacrylate Beads, J Bone and Joint Surgery, 60B(2), 1978

Experimental in-vitro drug release profile

from PMMA beads.

Cortical

Bone

PMMA

beads

Surgical Opening

(clot)

Marrow

Periosteum

Marrow

Geometry used incorporating

PMMA beads

(bead diameter = 5mm)

y =0.28823 t 0.2839

Results II (Comparison with PMMA beads)Change in gentamicin concentration with time (yz-plane):

(Coloured regions have concentration to bacteria MIC)

10 mins 1 hr

1 day 10 days

20 days 40 days

1391 mg/ml 0.25 mg/ml

C.G. Lee, YC Fu, and C.H. Wang, “Simulation of Gentamicin Delivery for the Local Treatment of Osteomyelitis”, Biotechnology and Bioengineering, 91, 622-635 (2005).

Summary

Continuous drainage of interstitial fluid from surgical opening in

the initial period of treatment causes drug concentration in marrow

to decrease exponentially.

Increasing clotting duration further depresses the mean drug

concentration in the marrow.

Drug release profile showing double burst exhibits a longer period

of drug concentration above MIC during the second burst.

While using PMMA beads results in an overall increase in drug

concentration, their non-biodegradable nature makes them less

appealing than biodegradable disc. A possible link between carrier

geometry and drug concentration may exist.

appendix 5 micro- and nano- particle synthesis and processing...

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