690 likes | 729 Views
Week #5 Micro- and Nano- Particle Synthesis and Processing for Pharmaceutical, Biomedical, and Food Applications (Part 3). Chi-Hwa Wang
E N D
Week #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: chewch@nus.edu.sg.
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 with coumarin6-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.
Ultimate Aim Establishing a simulation platform, which will optimize key process parameters to help surgeons in executing a successful treatment. 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.
J. Controlled Release, 61 21-41 (1999).
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).
Distribution of velocity and drug concentration Chem. Eng. Sci., 53(20), 3579-3600 (1998).
Methodology • Construct a brain tumor geometry consisting of cavity (with wafers implanted), tumor and normal tissue zones. • Solving the transport equations of mass, momentum and species (drug), using Computational Fluid Dynamics Simulation to obtain a steady state condition prior to surgery. • Perturbing the steady state solution to simulate the transient effects: • assess the fluid flow pattern and its effects on the drug delivery • 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 Pressure Distribution 3-D Computational Geometry
Model Geometry C (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.
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. 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). 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.
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).
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).
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).
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). The superscripts 1 and 2 refer to gravity in the z (as shown in above figure) and x directions, respectively.
Temporal Evolution of Drug Concentration Wafer Tumor
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).
Legend: • Linear release • 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).
Figure LR-2 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. 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).
N2 N1 B A F E C W1 C/T 1 1 2 3 T C/N N N3 1 mm Open Tumor: Transient Variations Model Geometry used for open tumor simulation 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). Transient variation of velocity and pressure in the tumor zone, summarizing the developing transient profiles of the open tumor.
At the onset, fluid flows into the cavity zones, causing a pressure depression in all zones. Pressure slowly equilibrates leading to a bi-directional flow of fluid in the tumor zone which persisted for the remaining part of the simulation. However, the high interstitial central pressure which is crucial for efficient drug delivery is never restored, undermining the efficacy of the treatment. (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).
Open Tumor: Effects on Treatment Efficacy 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) Temporal variation of the normalized ratio of Pe and /Pe in the Cavity. Ratio(/Pe) is defined as (/Pe)op/(/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).
Mass fraction Drug contour plot showing the uneven drug distribution in the tumor zone due to the tumor opening. Open Tumor: Effects of Opening Sizes 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 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.
PLLA + DCM Etanidazole + DCM Ultrasonication PLGA Ultrasonication Water + Poly Vinyl Alcohol (PVA) Solvent Evaporation Filtration + Freeze Drying 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.
A B C D 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) 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). A: PLLA/PLGA 1:1; B,C: PLLA/PLGA 2:1; D: PLLA/PLGA 2.5:1
A B • 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. 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. 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).