Tuning and Controlling the Release
Profiles of Functional Biomolecules
through Optimal Learning
Jesse Goodman
Summer 2014
McAlpine Group
McAlpine Research Group
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Nanotechnology
Biology
Energy
Worked closely with:
– Dr. Maneesh Gupta
My Project
• Switch from encapsulating phase change materials
• Protein loaded microspheres
– Drug delivery, tissue engineering, etc.
– Controlling release rate is difficult…
http://www.pharmaceutical-int.com/upload/image_files/news/0_multilayered-particlesfor-drug-delivery-and-artificial-tissues_content_Multilayered-Particles-Drug-Delivery.jpg
http://www.rsc.org/images/Figure%201_tcm18-35157.jpg
Need for customizable release profiles
• Literature is very application specific
PLGA-Based Microparticles for the Sustained Release of BMP-2 (Kirby et al., 2011)
Controlled Release of Dexamethasone from PLGA Microspheres
Embedded Within Polyacid-Containing PVA Hydrogels (Galeska et al., 2005)
• Lack of discussion re the ability to create any desired release
profile by altering certain parameters
Particle Formulation
Double Emulsion Solvent Evaporation
W1/O Emulsification
W1/O/W2 Emulsification
Drying Process
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W1/O Volume Fraction
Polymer Concentration
Payload Concentration
Dispersion Speed
(W1/O)/W2 Volume Fraction
External PVA Concentration
Dispersion Speed
Dilution Ratio
Temperature
Varying Parameters
• Affects particle size & polydispersity
• Should also affect release profile
• Settle on modifying only certain parameters
– W1/O ratio, PLGA conc, BSA and HRP conc.
Measuring protein release
8.5.14: Standard Curve for HRP
2
y = 18.914x - 0.0251
R² = 0.9991
1.8
1.6
Absorbance
1.4
1.2
1
0.8
0.6
0.4
0.2
0
0
0.02
0.04
0.06
HRP Concentration (U/ml)
0.08
0.1
0.12
Release Profiles
7.29.14: HRP release profile
40
30
25
20
15
10
5
0
0
5
10
15
20
25
30
Time (hours)
8.4.14: HRP release profile
14
12
% HRP released
% HRP released
35
10
8
6
4
2
0
0
5
10
15
Time (hours)
20
25
30
Optimization Process
Use chosen parameters to
create particles & release profile
Email release profile data to Kris
& Si in ORFE collaboration group
Plug into model & chose
parameters (optimized to
develop model) for another
experiment
Optimization Predictions &
Comparisons
Further research
• Target release profiles in order to develop
certain medicines
• Apply this optimal learning technique to
similar projects
http://www.pro
cessingmagazine
.com/ext/resour
ces/NewsPhotos/2013/08
13/TS_16226425
3_715x400.jpg
Acknowledgements
• Thanks to:
– Dr. Maneesh Gupta for working with me on this
project throughout the summer
– Dr. Kris Reyes and Si Chen for collaborating with
me and working on the optimization portion of
this project
– Professor McAlpine for hosting me in his lab and
guiding me through this project
– PEI for making this internship possible