(725c) Computational Modeling for the Comprehensive Drug Release of an Implantable, Bioresorbable Drug Delivery Device | AIChE

(725c) Computational Modeling for the Comprehensive Drug Release of an Implantable, Bioresorbable Drug Delivery Device


Giolando, P. - Presenter, Purdue University
Kinzer-Ursem, T. L., Purdue University
Solorio, L., University of Michigan
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Patrick Giolando Normal Patrick Giolando 2 5 2019-04-11T20:47:00Z 2019-04-11T20:47:00Z 1 423 2413 20 5 2831 16.00

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modeling for the comprehensive drug release of an implantable, bioresorbable
drug delivery device

Patrick A.
Giolando1, Kelsey Hopkins1, Barrett Davis1,
Joseph Rispoli1, Nicole Vike1, Tamara L. Kinzer-Ursem1*,
Luis Solorio1*

1 Weldon School of Biomedical
Engineering, Purdue University   

bioresorbable drug delivery systems offer a unique alternative to current drug
administration techniques, and allows for a patient tailored drug dosage, while
also increasing patient compliance. In
forming implants (ISFIs) undergo a phenomenally complicated
solidification, and degradation process when introduced into the aqueous
environment of the body, which allows for the drug release rate of the
encapsulated drug to be reliably controlled. Developing and solving a
comprehensive mathematical model not only allows for the acceleration of the
ISFI design process, but to predict physical anomalies that are not intuitive
and might otherwise elude discovery. This study utilizes a multi-scale modeling
approach to investigate both the precipitation of polymer into a solid implant
in the first few days, and the degradation and erosion of the ISFI over the
next few weeks; thereby allowing for the accurate prediction of the drug
release profile from ISFIs of varying molecular weight. Initial drug burst
dynamics were modeled by applying the analytical solution of diffusion as a
weighting function for the solidification of the polymer. Finite difference
methods were used to solve the degradation and erosion of the polymer due to
the hydrolysis of ester bonds, which produce carboxylic acid terminate
oligomers. These acidic oligomers along with acidic drug further catalyze the
degradation of the polymer, therefore it becomes necessary to evaluate the acid
dissociation on a much smaller timescale. Comparing to experimental data for
varying PLGA copolymer molecular weight (Fig. 1), the computational model was
able to accurately predict the drug release with a 6.7% error, and a negligible
2.0 % in predicting the immediate drug burst. The model thus accurately
predicts drug release of various molecular weight polymers and provides
mechanistic explanation for non-intuitive increases in drug release seen in
some polymer mixtures. Future work will focus on developing mechanistic
insights into the relationship between polymer diffusivity and molecular weight
as well as developing a more complete model of the solidification process of
the implant.

107%;font-family:" helvetica>Fig 1. Verification of Drug Release
" helvetica>The model was parameterized with a combination of
experimental and literature data, and plotted against
previous literature data for the drug release profile of a 15, 29, and 53 kDa ISFI


height:286px"> line-height:107%;font-family:" helvetica>. Normalized drug concentration
is plotted in the small contour plots for 1, 5, 13, and 16 days after